SCI Makaleler

Bas, E., Egrioglu, E., Cansu, T.

Robust training of median dendritic artificial neural networks for time series forecasting

(2024) Expert Systems with Applications, 238, art. no. 122080, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173838239&doi=10.1016%2fj.eswa.2023.122080&partnerID=40&md5=c7d0476e539467279c5dee4d33e9a309

DOI: 10.1016/j.eswa.2023.122080

Karahasan, O., Bas, E., Egrioglu, E.

New deep recurrent hybrid artificial neural network for forecasting seasonal time series

(2024) Granular Computing, 9 (1), art. no. 19, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181849053&doi=10.1007%2fs41066-023-00445-3&partnerID=40&md5=6e56b77bb18f700c3af6ff77ee589c1f

DOI: 10.1007/s41066-023-00445-3

Kolemen, E., Egrioglu, E., Bas, E., Turkmen, M.

A new deep recurrent hybrid artificial neural network of gated recurrent units and simple seasonal exponential smoothing

(2024) Granular Computing, 9 (1), art. no. 7, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180639381&doi=10.1007%2fs41066-023-00444-4&partnerID=40&md5=fde198f67d3754e615abd9e967e580b0

DOI: 10.1007/s41066-023-00444-4

Yücesoy, E., Egrioglu, E., Bas, E.

A new intuitionistic fuzzy time series method based on the bagging of decision trees and principal component analysis

(2023) Granular Computing, 8 (6), pp. 1925-1935.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169318929&doi=10.1007%2fs41066-023-00416-8&partnerID=40&md5=b060e2e56301323ed0159eed859cde42

DOI: 10.1007/s41066-023-00416-8

Olmez, E., Egrioglu, E., Bas, E.

Bootstrapped Dendritic Neuron Model Artificial Neural Network for Forecasting

(2023) Granular Computing, 8 (6), pp. 1689-1699.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162959713&doi=10.1007%2fs41066-023-00390-1&partnerID=40&md5=91367114e8d1fdd5ca4d0a46ea56bcbe

DOI: 10.1007/s41066-023-00390-1

Cansu, T., Kolemen, E., Karahasan, Ö., Bas, E., Egrioglu, E.

A new training algorithm for long short-term memory artificial neural network based on particle swarm optimization

(2023) Granular Computing, 8 (6), pp. 1645-1658.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161534950&doi=10.1007%2fs41066-023-00389-8&partnerID=40&md5=cdc15e3f83dab129a1b43575f7871dd7

DOI: 10.1007/s41066-023-00389-8

Chen, C.-C., Hung, P.C.K., Egrioglu, E., Chiu, D.K.W., Ho, K.K.W.

Guest editorial: Contemporary learning behaviors on mobile devices and social media

(2023) Library Hi Tech, 41 (5), pp. 1265-1274.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175489981&doi=10.1108%2fLHT-10-2023-589&partnerID=40&md5=709f7ae9000537b6de8c968e3dcb23d8

DOI: 10.1108/LHT-10-2023-589

Sarıkaya, C., Bas, E., Egrioglu, E.

Training Sigma-Pi neural networks with the grey wolf optimization algorithm

(2023) Granular Computing, 8 (5), pp. 981-989.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147568229&doi=10.1007%2fs41066-023-00368-z&partnerID=40&md5=aead365f47d5b71ff5104f0a74b949a8

DOI: 10.1007/s41066-023-00368-z

Egrioglu, E., Bas, E.

Robust intuitionistic fuzzy regression functions approaches

(2023) Information Sciences, 638, art. no. 118992, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153519778&doi=10.1016%2fj.ins.2023.118992&partnerID=40&md5=97ce3eb00413632881bb50f90e1f928e

DOI: 10.1016/j.ins.2023.118992

Bas, E., Eğrioğlu, E.

A new recurrent pi-sigma artificial neural network inspired by exponential smoothing feedback mechanism

(2023) Journal of Forecasting, 42 (4), pp. 802-812.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140384350&doi=10.1002%2ffor.2919&partnerID=40&md5=8ca8ad018645c302fc3c47cf2aa70280

DOI: 10.1002/for.2919

Gul, H.H., Egrioglu, E., Bas, E.

Statistical learning algorithms for dendritic neuron model artificial neural network based on sine cosine algorithm

(2023) Information Sciences, 629, pp. 398-412.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147856202&doi=10.1016%2fj.ins.2023.02.008&partnerID=40&md5=af8bc1b69af16d02a5e7416e18b3cd66

DOI: 10.1016/j.ins.2023.02.008

Egrioglu, E., Grosan, C., Bas, E.

A new genetic algorithm method based on statistical-based replacement for the training of multiplicative neuron model artificial neural networks

(2023) Journal of Supercomputing, 79 (7), pp. 7286-7304.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142673572&doi=10.1007%2fs11227-022-04935-0&partnerID=40&md5=f785c9cd6fc9367784fda1f03130e301

DOI: 10.1007/s11227-022-04935-0

Egrioglu, E., Bas, E., Karahasan, O.

Winsorized dendritic neuron model artificial neural network and a robust training algorithm with Tukey’s biweight loss function based on particle swarm optimization

(2023) Granular Computing, 8 (3), pp. 491-501.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135721758&doi=10.1007%2fs41066-022-00345-y&partnerID=40&md5=a99d0b61b9b51e12af385cc859138f89

DOI: 10.1007/s41066-022-00345-y

Bas, E., Egrioglu, E., Yolcu, U., Chen, M.-Y.

A Robust Learning Algorithm Based on Particle Swarm Optimization for Pi-Sigma Artificial Neural Networks

(2023) Big Data, 11 (2), pp. 105-116.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153123434&doi=10.1089%2fbig.2021.0064&partnerID=40&md5=7c1d6eaf2953fbd812544483cdf9ae4a

DOI: 10.1089/big.2021.0064

Egrioglu, E., Bas, E., Cansu, T., Kara, M.A.

A new nonlinear causality test based on single multiplicative neuron model artificial neural network: a case study for Turkey’s macroeconomic indicators

(2023) Granular Computing, 8 (2), pp. 391-396.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135004907&doi=10.1007%2fs41066-022-00336-z&partnerID=40&md5=b0d36a1715ed878d2b385a36c5a28bae

DOI: 10.1007/s41066-022-00336-z

Chen, M.-Y., Thuraisingham, B., Egrioglu, E., Rubio, J.D.J.

Introduction to the Special Issue on Smart Systems for Industry 4.0 and IoT

(2023) ACM Transactions on Management Information Systems, 13 (4), art. no. 35, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149447159&doi=10.1145%2f3583985&partnerID=40&md5=b9486ef47acaf1abd34d8ac55e6d96ae

DOI: 10.1145/3583985

Kocak, C., Egrioglu, E., Bas, E.

A new explainable robust high-order intuitionistic fuzzy time-series method

(2023) Soft Computing, 27 (3), pp. 1783-1796.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113737233&doi=10.1007%2fs00500-021-06079-4&partnerID=40&md5=3e4d56334b32eb02beb4d19f2ec1dfac

DOI: 10.1007/s00500-021-06079-4

Efendi, R., Yunus, N.W.M., Widyawati, S.R., Susanti, R., Egrioglu, E., Syahri, M., Putra, E.H., Hamzah, A.

Yearly Residential Electricity Forecasting Model Based on Fuzzy Regression Time Series in Indonesia †

(2023) Engineering Proceedings, 39 (1), art. no. 4, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172804292&doi=10.3390%2fengproc2023039004&partnerID=40&md5=a816f370b2c6d44f79909b9510a0b13d

DOI: 10.3390/engproc2023039004

Egrioglu, E., Bas, E.

A new hybrid recurrent artificial neural network for time series forecasting

(2023) Neural Computing and Applications, 35 (3), pp. 2855-2865.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137749647&doi=10.1007%2fs00521-022-07753-w&partnerID=40&md5=4d7270a406cef7e21f57d5be34cb28d8

DOI: 10.1007/s00521-022-07753-w

Egrioglu, E., Bas, E.

Modified Pi Sigma artificial neural networks for forecasting

(2023) Granular Computing, 8 (1), pp. 131-135.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128181300&doi=10.1007%2fs41066-022-00320-7&partnerID=40&md5=9806a520b4e1f8402a1fe51dac3e8602

DOI: 10.1007/s41066-022-00320-7

Bas, E., Egrioglu, E., Tunc, T.

Multivariate Picture Fuzzy Time Series: New Definitions and a New Forecasting Method Based on Pi-Sigma Artificial Neural Network

(2023) Computational Economics, 61 (1), pp. 139-164.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116020930&doi=10.1007%2fs10614-021-10202-w&partnerID=40&md5=2ead388548aa9deed888ac9fec31fe65

DOI: 10.1007/s10614-021-10202-w

Bas, E., Egrioglu, E., Kolemen, E.

A novel intuitionistic fuzzy time series method based on bootstrapped combined pi-sigma artificial neural network

(2022) Engineering Applications of Artificial Intelligence, 114, art. no. 105030, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132235532&doi=10.1016%2fj.engappai.2022.105030&partnerID=40&md5=3244470f996e71388c340f8dc68a2ef9

DOI: 10.1016/j.engappai.2022.105030

Egrioglu, E., Baş, E., Chen, M.-Y.

Recurrent dendritic neuron model artificial neural network for time series forecasting

(2022) Information Sciences, 607, pp. 572-584.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131828912&doi=10.1016%2fj.ins.2022.06.012&partnerID=40&md5=24df5849b8c83755898e0386c1efcc0b

DOI: 10.1016/j.ins.2022.06.012

Bas, E., Egrioglu, E.

A fuzzy regression functions approach based on Gustafson-Kessel clustering algorithm

(2022) Information Sciences, 592, pp. 206-214.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124234111&doi=10.1016%2fj.ins.2022.01.057&partnerID=40&md5=529dbb6a641d621782629d0e1225ec80

DOI: 10.1016/j.ins.2022.01.057

Yılmaz, O., Bas, E., Egrioglu, E.

The Training of Pi-Sigma Artificial Neural Networks with Differential Evolution Algorithm for Forecasting

(2022) Computational Economics, 59 (4), pp. 1699-1711.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129375947&doi=10.1007%2fs10614-020-10086-2&partnerID=40&md5=aedb78ae83cac67eedeeaf84185ff749

DOI: 10.1007/s10614-020-10086-2

Chen, M.-Y., Sangaiah, A.K., Chen, T.-H., Lughofer, E.D., Egrioglu, E.

Deep Learning for Financial Engineering

(2022) Computational Economics, 59 (4), pp. 1277-1281.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128404923&doi=10.1007%2fs10614-022-10260-8&partnerID=40&md5=e7f6826a0c77cc19745d73cba62f91d3

DOI: 10.1007/s10614-022-10260-8

Bas, E., Egrioglu, E., Kolemen, E.

Training simple recurrent deep artificial neural network for forecasting using particle swarm optimization

(2022) Granular Computing, 7 (2), pp. 411-420.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108727170&doi=10.1007%2fs41066-021-00274-2&partnerID=40&md5=be2363ea97eeb8e06d351dd6e31a2ca5

DOI: 10.1007/s41066-021-00274-2

Eğrioğlu, E., Fildes, R.

A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting

(2022) Computational Economics, 59 (4), pp. 1355-1383.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096390441&doi=10.1007%2fs10614-020-10073-7&partnerID=40&md5=7066e5fd0a71538276a66bea9e0ee9c0

DOI: 10.1007/s10614-020-10073-7

Chen, M.-Y., Liao, C.-H., Lughofer, E.D., Egrioglu, E.

Editorial

(2022) Library Hi Tech, 40 (1), pp. 1-2.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127043051&doi=10.1108%2fLHT-02-2022-443&partnerID=40&md5=5bfd9fdaed7ea7df8002af7cd721014f

DOI: 10.1108/LHT-02-2022-443

Yolcu, O.C., Egrioglu, E., Bas, E., Yolcu, U.

Multivariate intuitionistic fuzzy inference system for stock market prediction: The cases of Istanbul and Taiwan

(2022) Applied Soft Computing, 116, art. no. 108363, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122332024&doi=10.1016%2fj.asoc.2021.108363&partnerID=40&md5=75c463775788e8fd473bd9f653f25f1d

DOI: 10.1016/j.asoc.2021.108363

Egrioglu, E., Bas, E.

A new automatic forecasting method based on a new input significancy test of a single multiplicative neuron model artificial neural network

(2022) Network: Computation in Neural Systems, 33 (1-2), pp. 1-16.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125891371&doi=10.1080%2f0954898X.2022.2042609&partnerID=40&md5=07b81f55d3ba5cfb777437828ff30587

DOI: 10.1080/0954898X.2022.2042609

Chen, M.-Y., Lughofer, E.D., Egrioglu, E.

Deep learning and intelligent system towards smart manufacturing

(2022) Enterprise Information Systems, 16 (2), pp. 189-192.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124231706&doi=10.1080%2f17517575.2021.1898050&partnerID=40&md5=76a6cd065ff01774aabc4c885cc3d21d

DOI: 10.1080/17517575.2021.1898050

Egrioglu, E., Fildes, R., Baş, E.

Recurrent fuzzy time series functions approaches for forecasting

(2022) Granular Computing, 7 (1), pp. 163-170.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106859799&doi=10.1007%2fs41066-021-00257-3&partnerID=40&md5=c6a7ea9ffc3025c0415edbd83f3a9c09

DOI: 10.1007/s41066-021-00257-3

Bas, E., Egrioglu, E., Yolcu, U.

Bootstrapped Holt Method with Autoregressive Coefficients Based on Harmony Search Algorithm

(2021) Forecasting, 3 (4), pp. 839-849.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138493032&doi=10.3390%2fforecast3040050&partnerID=40&md5=3aee3a32921886df2f3da1d5d3978a98

DOI: 10.3390/forecast3040050

Bas, E., Yolcu, U., Egrioglu, E.

Intuitionistic fuzzy time series functions approach for time series forecasting

(2021) Granular Computing, 6 (3), pp. 619-629.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107890741&doi=10.1007%2fs41066-020-00220-8&partnerID=40&md5=de90453a0bbd04635a9df1bc2e253dd5

DOI: 10.1007/s41066-020-00220-8

Kocak, C., Egrioglu, E., Bas, E.

A new deep intuitionistic fuzzy time series forecasting method based on long short-term memory

(2021) Journal of Supercomputing, 77 (6), pp. 6178-6196.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096451512&doi=10.1007%2fs11227-020-03503-8&partnerID=40&md5=16404535a602f4628e7fee22f9aca092

DOI: 10.1007/s11227-020-03503-8

Bas, E., Egrioglu, E., Karahasan, O.

A Pi-Sigma artificial neural network based on sine cosine optimization algorithm

(2021) Granular Computing, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117964140&doi=10.1007%2fs41066-021-00297-9&partnerID=40&md5=5ffa034d4e8e6d8ee900490aebc99763

DOI: 10.1007/s41066-021-00297-9

Chen, M.-Y., Lughofer, E.D., Egrioglu, E.

Cloud & fog computing: intelligent applications

(2021) Enterprise Information Systems, 15 (9), pp. 1197-1199.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116453047&doi=10.1080%2f17517575.2021.1909751&partnerID=40&md5=c575f5c7bd185ba8cc0d63ea218546ef

DOI: 10.1080/17517575.2021.1909751

Tak, N., Egrioglu, E., Bas, E., Yolcu, U.

An adaptive forecast combination approach based on meta intuitionistic fuzzy functions

(2021) Journal of Intelligent and Fuzzy Systems, 40 (5), pp. 9567-9581.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104945195&doi=10.3233%2fJIFS-202021&partnerID=40&md5=98f26ba51e5ee156e31f1222338b6793

DOI: 10.3233/JIFS-202021

Yildirim, A.N., Bas, E., Egrioglu, E.

Threshold single multiplicative neuron artificial neural networks for non-linear time series forecasting

(2021) Journal of Applied Statistics, 48 (13-15), pp. 2809-2825.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099244906&doi=10.1080%2f02664763.2020.1869702&partnerID=40&md5=4c4ce242283d6ec72cd71a9dfb00700e

DOI: 10.1080/02664763.2020.1869702

Yolcu, U., Egrioglu, E., Bas, E., Yolcu, O.C., Dalar, A.Z.

Probabilistic forecasting, linearity and nonlinearity hypothesis tests with bootstrapped linear and nonlinear artificial neural network

(2021) Journal of Experimental and Theoretical Artificial Intelligence, 33 (3), pp. 383-404.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064013295&doi=10.1080%2f0952813X.2019.1595167&partnerID=40&md5=120b8b38e3d83359b105ad2e7da4e1b1

DOI: 10.1080/0952813X.2019.1595167

Chen, M.-Y., Liao, C.-H., Lughofer, E.D., Egrioglu, E.

Informetrics on social network mining: research, policy and practice challenges

(2020) Library Hi Tech, 38 (2), pp. 273-275.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086266804&doi=10.1108%2fLHT-06-2020-279&partnerID=40&md5=e2887c1534a4032bf16885aa7f2621c5

DOI: 10.1108/LHT-06-2020-279

Chen, M.-Y., Chiang, H.-S., Lughofer, E., Egrioglu, E.

Deep learning: emerging trends, applications and research challenges

(2020) Soft Computing, 24 (11), pp. 7835-7838.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083090822&doi=10.1007%2fs00500-020-04939-z&partnerID=40&md5=942839a1a5c6036d60d239a67ba2b371

DOI: 10.1007/s00500-020-04939-z

Kocak, C., Dalar, A.Z., Cagcag Yolcu, O., Bas, E., Egrioglu, E.

A new fuzzy time series method based on an ARMA-type recurrent Pi-Sigma artificial neural network

(2020) Soft Computing, 24 (11), pp. 8243-8252.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075189636&doi=10.1007%2fs00500-019-04506-1&partnerID=40&md5=70c85b1da1c8e1776fa0e73f2b3e4276

DOI: 10.1007/s00500-019-04506-1

Cagcag Yolcu, O., Bas, E., Egrioglu, E., Yolcu, U.

A new intuitionistic fuzzy functions approach based on hesitation margin for time-series prediction

(2020) Soft Computing, 24 (11), pp. 8211-8222.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074694938&doi=10.1007%2fs00500-019-04432-2&partnerID=40&md5=c175f9567fd8261b8d8e7fa6d8d9802d

DOI: 10.1007/s00500-019-04432-2

Bas, E., Yolcu, U., Egrioglu, E.

Picture fuzzy regression functions approach for financial time series based on ridge regression and genetic algorithm

(2020) Journal of Computational and Applied Mathematics, 370, art. no. 112656, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076478565&doi=10.1016%2fj.cam.2019.112656&partnerID=40&md5=8cadb8bd10b9348786bbcaa6d0faf85f

DOI: 10.1016/j.cam.2019.112656

Sengul, D., Sengul, I., Egrioglu, E., Ozturk, T., Aydin, I., Kesicioglu, T., Vural, S., Tosum, A., Bekci, T.

Can cut-off points of 10 and 15 mm of thyroid nodule predict malignancy on the basis of three diagnostic tools: I) strain elastography, ii) the Bethesda System for Reporting Thyroid Cytology with 27-gauge fine-needle, and iii) histopathology?

(2020) Journal of B.U.ON., 25 (2), pp. 1122-1129.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085113491&partnerID=40&md5=93b32d768a481d765323d98da2c7802d

Sengul, I., Sengul, D., Egrioglu, E., Ozturk, T.

Laterality of the thyroid nodules, anatomic and sonographic, as an estimator of thyroid malignancy and its neoplastic nature by comparing the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) and histopathology

(2020) Journal of B.U.ON., 25 (2), pp. 1116-1121.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085068189&partnerID=40&md5=b4fb6793898224061315a6b47c9102c6

Kizilaslan, B., Egrioglu, E., Evren, A.A.

Intuitionistic fuzzy ridge regression functions

(2020) Communications in Statistics: Simulation and Computation, 49 (3), pp. 699-708.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067491928&doi=10.1080%2f03610918.2019.1626887&partnerID=40&md5=c2e3b3694ec5a922a792b3a07db33e35

DOI: 10.1080/03610918.2019.1626887

Egrioglu, E., Bas, E., Yolcu, U., Chen, M.Y.

Picture fuzzy time series: Defining, modeling and creating a new forecasting method

(2020) Engineering Applications of Artificial Intelligence, 88, art. no. 103367, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075122917&doi=10.1016%2fj.engappai.2019.103367&partnerID=40&md5=2738a2e005f4d2e69846367270187b9a

DOI: 10.1016/j.engappai.2019.103367

Corba, B.S., Egrioglu, E., Dalar, A.Z.

AR–ARCH Type Artificial Neural Network for Forecasting

(2020) Neural Processing Letters, 51 (1), pp. 819-836.

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DOI: 10.1007/s11063-019-10117-6

Bas, E., Egrioglu, E., Yolcu, U.

A hybrid algorithm based on artificial bat and backpropagation algorithms for multiplicative neuron model artificial neural networks

(2020) Journal of Ambient Intelligence and Humanized Computing, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083768590&doi=10.1007%2fs12652-020-01950-y&partnerID=40&md5=855ff5161f34bd34b98934581ac82de1

DOI: 10.1007/s12652-020-01950-y

Bas, E., Egrioglu, E., Yolcu, U., Grosan, C.

Type 1 fuzzy function approach based on ridge regression for forecasting

(2019) Granular Computing, 4 (4), pp. 629-637.

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Egrioglu, E., Yolcu, U., Bas, E.

Intuitionistic high-order fuzzy time series forecasting method based on pi-sigma artificial neural networks trained by artificial bee colony

(2019) Granular Computing, 4 (4), pp. 639-654.

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DOI: 10.1007/s41066-018-00143-5

Göktaş, A., Eğrioğlu, E., Dağalp, R.

Special Issue: 11th International Statistics Days Conference

(2019) Communications in Statistics Case Studies Data Analysis and Applications, 5 (3), p. 167.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080108993&doi=10.1080%2f23737484.2019.1649391&partnerID=40&md5=7f5816c9082118580cab92c5ca27670a

DOI: 10.1080/23737484.2019.1649391

Egrioglu, E., Bas, E., Yolcu, O.C., Yolcu, U.

Intuitionistic time series fuzzy inference system

(2019) Engineering Applications of Artificial Intelligence, 82, pp. 175-183.

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DOI: 10.1016/j.engappai.2019.03.024

Egrioglu, E., Yolcu, U., Bas, E., Dalar, A.Z.

Median-Pi artificial neural network for forecasting

(2019) Neural Computing and Applications, 31 (1), pp. 307-316.

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Bas, E., Grosan, C., Egrioglu, E., Yolcu, U.

High order fuzzy time series method based on pi-sigma neural network

(2018) Engineering Applications of Artificial Intelligence, 72, pp. 350-356.

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DOI: 10.1016/j.engappai.2018.04.017

Cagcag Yolcu, O., Bas, E., Egrioglu, E., Yolcu, U.

Single Multiplicative Neuron Model Artificial Neural Network with Autoregressive Coefficient for Time Series Modelling

(2018) Neural Processing Letters, 47 (3), pp. 1133-1147.

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Akdeniz, E., Egrioglu, E., Bas, E., Yolcu, U.

An ARMA Type Pi-Sigma Artificial Neural Network for Nonlinear Time Series Forecasting

(2018) Journal of Artificial Intelligence and Soft Computing Research, 8 (2), pp. 121-132.

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Sarıca, B., Eğrioğlu, E., Aşıkgil, B.

A new hybrid method for time series forecasting: AR–ANFIS

(2018) Neural Computing and Applications, 29 (3), pp. 749-760.

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DOI: 10.1007/s00521-016-2475-5

Yolcu, U., Bas, E., Egrioglu, E.

A new fuzzy inference system for time series forecasting and obtaining the probabilistic forecasts via subsampling block bootstrap

(2018) Journal of Intelligent and Fuzzy Systems, 35 (2), pp. 2349-2358.

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Tak, N., Evren, A.A., Tez, M., Egrioglu, E.

Recurrent type-1 fuzzy functions approach for time series forecasting

(2018) Applied Intelligence, 48 (1), pp. 68-77.

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Inan, D., Egrioglu, E., Sarica, B., Askin, O.E., Tez, M.

Particle swarm optimization based Liu-type estimator

(2017) Communications in Statistics - Theory and Methods, 46 (22), pp. 11358-11369.

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Yolcu, U., Jin, Y., Egrioglu, E.

An ensemble of single multiplicative neuron models for probabilistic prediction

(2017) 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016, art. no. 7849975, .

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Cagcag Yolcu, O., Yolcu, U., Egrioglu, E., Aladag, C.H.

High order fuzzy time series forecasting method based on an intersection operation

(2016) Applied Mathematical Modelling, 40 (19-20), pp. 8750-8765.

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Bas, E., Uslu, V.R., Egrioglu, E.

Robust learning algorithm for multiplicative neuron model artificial neural networks

(2016) Expert Systems with Applications, 56, pp. 80-88.

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Gundogdu, O., Egrioglu, E., Aladag, C.H., Yolcu, U.

Multiplicative neuron model artificial neural network based on Gaussian activation function

(2016) Neural Computing and Applications, 27 (4), pp. 927-935.

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Aladag, C.H., Yolcu, U., Egrioglu, E., Turksen, I.B.

Type-1 fuzzy time series function method based on binary particle swarm optimisation

(2016) International Journal of Data Analysis Techniques and Strategies, 8 (1), pp. 2-13.

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Bas, E., Egrioglu, E., Aladag, C.H., Yolcu, U.

Fuzzy-time-series network used to forecast linear and nonlinear time series

(2015) Applied Intelligence, 43 (2), pp. 343-355.

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Uzun, I., Gunduz, K., Celenk, P., Avsever, H., Orhan, K., Canitezer, G., Ozmen, B., Cicek, E., Egrioglu, E.

Comparing the effect of different voxel resolutions for assessment of vertical root fracture of permanent teeth

(2015) Iranian Journal of Radiology, 12 (3), art. no. e18290, pp. 1-7.

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Egrioglu, E., Yolcu, U., Aladag, C.H., Bas, E.

Recurrent Multiplicative Neuron Model Artificial Neural Network for Non-linear Time Series Forecasting

(2015) Neural Processing Letters, 41 (2), pp. 249-258.

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Cagcag, O., Yolcu, U., Egrioglu, E.

A new robust regression method based on particle swarm optimization

(2015) Communications in Statistics - Theory and Methods, 44 (6), pp. 1270-1280.

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Yolcu, U., Bas, E., Egrioglu, E., Aladag, C.H.

A new multilayer feedforward network based on trimmed mean neuron model

(2015) Neural Network World, 25 (6), pp. 587-602.

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Egrioglu, E., Khashei, M., Aladag, C.H., Turksen, I.B., Yolcu, U.

Advanced Time Series Forecasting Methods

(2015) Mathematical Problems in Engineering, 2015, art. no. 918045, .

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Gunduz, K., Buyuk, C., Egrioglu, E.

Evaluation of the prevalence of bifid mandibular condyle detected on cone beam computed tomography images in a Turkish population [Evaluación de la prevalencia de cóndilo mandibular bífido detectado en tomografía computadorizada cone-beam en una población Turca]

(2015) International Journal of Morphology, 33 (1), pp. 43-47.

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Aladag, C.H., Egrioglu, E., Yolcu, U.

Robust multilayer neural network based on median neuron model

(2014) Neural Computing and Applications, 24 (3-4), pp. 945-956.

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Bas, E., Uslu, V.R., Yolcu, U., Egrioglu, E.

A modified genetic algorithm for forecasting fuzzy time series

(2014) Applied Intelligence, 41 (2), pp. 453-463.

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Aladag, C.H., Yolcu, U., Egrioglu, E., Bas, E.

Fuzzy lagged variable selection in fuzzy time series with genetic algorithms

(2014) Applied Soft Computing Journal, 22, pp. 465-473.

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Yolcu, U., Cagcag, O., Aladag, C.H., Egrioglu, E.

An enhanced fuzzy time series forecasting method based on artificial bee colony

(2014) Journal of Intelligent and Fuzzy Systems, 26 (6), pp. 2627-2637.

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Egrioglu, E.

PSO-based high order time invariant fuzzy time series method: Application to stock exchange data

(2014) Economic Modelling, 38, pp. 633-639.

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Rezan Uslu, V., Bas, E., Yolcu, U., Egrioglu, E.

A fuzzy time series approach based on weights determined by the number of recurrences of fuzzy relations

(2014) Swarm and Evolutionary Computation, 15, pp. 19-26.

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Avsever, H., Gunduz, K., Orhan, K., Uzun, I., Ozmen, B., Egrioglu, E., Midilli, M.

Comparison of intraoral radiography and cone-beam computed tomography for the detection of horizontal root fractures: An in vitro study

(2014) Clinical Oral Investigations, 18 (1), pp. 285-292.

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Aladag, C.H., Egrioglu, E., Yolcu, U., Uslu, V.R.

A high order seasonal fuzzy time series model and application to international tourism demand of Turkey

(2014) Journal of Intelligent and Fuzzy Systems, 26 (1), pp. 295-302.

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Egrioglu, E., Yolcu, U., Aladag, C.H., Kocak, C.

An ARMA type fuzzy time series forecasting method based on particle swarm optimization

(2013) Mathematical Problems in Engineering, 2013, art. no. 935815, .

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Aladag, C.H., Yolcu, U., Egrioglu, E.

A new multiplicative seasonal neural network model based on particle swarm optimization

(2013) Neural Processing Letters, 37 (3), pp. 251-262.

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Egrioglu, E., Aladag, C.H., Yolcu, U.

Fuzzy time series forecasting with a novel hybrid approach combining fuzzy c-means and neural networks

(2013) Expert Systems with Applications, 40 (3), pp. 854-857.

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Yolcu, U., Egrioglu, E., Aladag, C.H.

A new linear & nonlinear artificial neural network model for time series forecasting

(2013) Decision Support Systems, 54 (3), pp. 1340-1347.

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Gunduz, K., Avsever, H., Orhan, K., Çelenk, P., Ozmen, B., Cicek, E., Egrioglu, E., Karaçaylı, Ü.

Comparison of intraoral radiography and cone-beam computed tomography for the detection of vertical root fractures: An in vitro study

(2013) Oral Radiology, 29 (1), pp. 6-12.

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Yolcu, U., Aladag, C.H., Egrioglu, E., Uslu, V.R.

Time-series forecasting with a novel fuzzy time-series approach: An example for Istanbul stock market

(2013) Journal of Statistical Computation and Simulation, 83 (4), pp. 599-612.

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Aladag, C.H., Eǧrioǧlu, E., Kadilar, C.

Forecasting gold prices series in turkey by the forecast combination

(2012) Advances in Time Series Forecasting, pp. 108-117.

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Eǧrioǧlu, E., Aladag, C.H., Yolcu, U.

A hybrid forecasting approach combines SARIMA and Fuzzy time series

(2012) Advances in Time Series Forecasting, pp. 96-107.

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Eǧrioǧlu, E., Aladag, C.H., Yolcu, U.

Comparison of architecture selection sriteria in analyzing long memory time series

(2012) Advances in Time Series Forecasting, pp. 18-25.

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Aladag, C.H., Eǧrioǧlu, E.

A hybrid forecasting model based on multivariate fuzzy time series and artificial neural networks

(2012) Advances in Time Series Forecasting, pp. 118-129.

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Aladag, C.H., Eǧrioǧlu, E.

Adaptive weighted information criterion to determine the best architecture

(2012) Advances in Time Series Forecasting, pp. 34-39.

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Eǧrioǧlu, E., Aladag, C.H., Yolcu, U.

A new method for forecasting fuzzy time series with triangular fuzzy number observations

(2012) Advances in Time Series Forecasting, pp. 48-55.

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Eǧrioǧlu, E., Uslu, V.R., Koc, S.

New criteria to compare interval estimates in fuzzy time series methods

(2012) Advances in Time Series Forecasting, pp. 56- 63.

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Eǧrioǧlu, E., Aladag, C.H.

The effect of the length of interval in fuzzy time series models on forecasting

(2012) Advances in Time Series Forecasting, pp. 64-77.

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Aladag, C.H., Eǧrioǧlu, E.

Advanced time series forecasting methods

(2012) Advances in Time Series Forecasting, pp. 3-10.

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Eǧrioǧlu, E., Aladag, C.H., Yolcu, U.

Comparison of feed forward and elman neural networks forecasting ability: Case study for IMKB

(2012) Advances in Time Series Forecasting, pp. 11-17.

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Aladag, C.H., Yolcu, U., Egrioglu, E., Dalar, A.Z.

A new time invariant fuzzy time series forecasting method based on particle swarm optimization

(2012) Applied Soft Computing Journal, 12 (10), pp. 3291-3299.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864750553&doi=10.1016%2fj.asoc.2012.05.002&partnerID=40&md5=cf430d444a337582b07714c5eb4b4f53

DOI: 10.1016/j.asoc.2012.05.002

Eǧrioǧlu, E.

A new time-invariant fuzzy time series forecasting method based on genetic algorithm

(2012) Advances in Fuzzy Systems, art. no. 785709, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864952412&doi=10.1155%2f2012%2f785709&partnerID=40&md5=050d729dbed81d7f0a5bf95bec4ca3e1

DOI: 10.1155/2012/785709

Aladag, S., Aladag, C.H., Mentes, T., Egrioglu, E.

A new seasonal fuzzy time series method based on the multiplicative neuron model and SARIMA

(2012) Hacettepe Journal of Mathematics and Statistics, 41 (3), pp. 337-345.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870277987&partnerID=40&md5=6c008f7493b941dec71a15d9a0777574

Alpaslan, F., Cagcag, O., Aladag, C.H., Yolcu, U., Egrioglu, E.

A novel seasonal fuzzy time series method

(2012) Hacettepe Journal of Mathematics and Statistics, 41 (3), pp. 375-385.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870273208&partnerID=40&md5=47cd4774a5b099e87b9933fd9f0ccb3e

Aladag, C.H., Egrioglu, E., Yolcu, U.

A simulation based approach to calculate the fuzzy correlation coefficient of fuzzy observations

(2012) Hacettepe Journal of Mathematics and Statistics, 41 (3), pp. 361-364.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870268938&partnerID=40&md5=c3d0c11f54bf5d078e02b1ec09f625c2

Egrioglu, E., Aladag, C.H., Kadilar, C.

Nonlinear forecasting with a hybrid approach combining SARIMA, ARCH and ANN

(2011) New Developments in Artificial Neural Networks Research, pp. 221-228.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84895338526&partnerID=40&md5=c0964458065f77153d96adb98b4d284c

Gündüz, K., Acikgöz, A., Egrioglu, E.

Radiologic investigation of prevalence, associated pathologies and dental anomalies of non-third molar impacted teeth in Turkish oral patients.

(2011) The Chinese journal of dental research : the official journal of the Scientific Section of the Chinese Stomatological Association (CSA), 14 (2), pp. 141-146.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859413489&partnerID=40&md5=68b2751ce8694431afeca16b01048238

Egrioglu, E., Aladag, C.H., Kadilar, C.

The CSS and the two-staged methods for parameter estimation in SARFIMA models

(2011) Journal of Probability and Statistics, art. no. 691058, .

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859181536&doi=10.1155%2f2011%2f691058&partnerID=40&md5=4728ce5cb7a0f9e8e905e81bc5f9f1e1

DOI: 10.1155/2011/691058

Egrioglu, E., Aladag, C.H., Yolcu, U., Uslu, V.R., Erilli, N.A.

Fuzzy time series forecasting method based on Gustafson-Kessel fuzzy clustering

(2011) Expert Systems with Applications, 38 (8), pp. 10355-10357.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-79953721648&doi=10.1016%2fj.eswa.2011.02.052&partnerID=40&md5=75ab4e71ada642673e112d9fdcee091d

DOI: 10.1016/j.eswa.2011.02.052

Ferhat Misir, A., Manisali, M., Egrioglu, E., Naini, F.B.

Retrospective analysis of nasal soft tissue profile changes with maxillary surgery

(2011) Journal of Oral and Maxillofacial Surgery, 69 (6), pp. e190-e194.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-79956371802&doi=10.1016%2fj.joms.2010.10.032&partnerID=40&md5=71ddf2001808feaedf198fcaa75637eb

DOI: 10.1016/j.joms.2010.10.032

Alpaslan, F., Cag̈cag̈, O., Eg̈riog̈lu, E.

Reduction of patient waiting time by simulations in Ondokuz Mayis University Medical Faculty, Department of Neurosurgery

(2011) Scientific Research and Essays, 6 (5), pp. 1063-1070.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-79955599105&partnerID=40&md5=28548156f1fb7cfc8d4848e55fd05f43

Alp Erilli, N., Yolcu, U., Eǧrioǧlu, E., Hakan Aladaǧ, Ĉ., Öner, Y.

Determining the most proper number of cluster in fuzzy clustering by using artificial neural networks

(2011) Expert Systems with Applications, 38 (3), pp. 2248-2252.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-78049529962&doi=10.1016%2fj.eswa.2010.08.012&partnerID=40&md5=b772c0c2cd4c574afad0b2ed67a50ea3

DOI: 10.1016/j.eswa.2010.08.012

Egrioglu, E., Aladag, C.H., Basaran, M.A., Yolcu, U., Uslu, V.R.

A new approach based on the optimization of the length of intervals in fuzzy time series

(2011) Journal of Intelligent and Fuzzy Systems, 22 (1), pp. 15-19.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651303153&doi=10.3233%2fIFS-2010-0470&partnerID=40&md5=6b870c7802febb1c180161a5cdb2d2ca

DOI: 10.3233/IFS-2010-0470

Aladag, C.H., Egrioglu, E., Yolcu, U.

Forecast combination by using artificial neural networks

(2010) Neural Processing Letters, 32 (3), pp. 269-276.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650693344&doi=10.1007%2fs11063-010-9156-7&partnerID=40&md5=b3cf6b5c03c5378062f23965d63a635e

DOI: 10.1007/s11063-010-9156-7

Aladag, C.H., Yolcu, U., Egrioglu, E.

A high order fuzzy time series forecasting model based on adaptive expectation and artificial neural networks

(2010) Mathematics and Computers in Simulation, 81 (4), pp. 875-882.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-78649848468&doi=10.1016%2fj.matcom.2010.09.011&partnerID=40&md5=804d8b9fcf329a8c99cfce608e956aa7

DOI: 10.1016/j.matcom.2010.09.011

Egrioglu, E., Aladag, C.H., Yolcu, U., Uslu, V.R., Basaran, M.A.

Finding an optimal interval length in high order fuzzy time series

(2010) Expert Systems with Applications, 37 (7), pp. 5052-5055.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-77950189383&doi=10.1016%2fj.eswa.2009.12.006&partnerID=40&md5=2caf4642434524b76979a77676682bdd

DOI: 10.1016/j.eswa.2009.12.006

Aladag, C.H., Egrioglu, E., Gunay, S., Basaran, M.A.

Improving weighted information criterion by using optimization

(2010) Journal of Computational and Applied Mathematics, 233 (10), pp. 2683-2687.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-73449108019&doi=10.1016%2fj.cam.2009.11.016&partnerID=40&md5=e69bc2c021f1ee907f3a070ad7a29309

DOI: 10.1016/j.cam.2009.11.016

Eǧrïoǧlu, E., Günay, S.

Bayesian model selection in ARFIMA models

(2010) Expert Systems with Applications, 37 (12), pp. 8359-8364.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-77957838947&doi=10.1016%2fj.eswa.2010.05.047&partnerID=40&md5=fcea0af546e3321b461204ebe354378f

DOI: 10.1016/j.eswa.2010.05.047

Aladag, C.H., Egrioglu, E., Kadilar, C.

Modeling brain wave data by using artificial neural networks

(2010) Hacettepe Journal of Mathematics and Statistics, 39 (1), pp. 81-88.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-77951090057&partnerID=40&md5=1822c4fc70c56803fc2507b4abc6a074

Misir, A.F., Sumer, M., Yenisey, M., Ergioglu, E.

Effect of Surgical Drill Guide on Heat Generated From Implant Drilling

(2009) Journal of Oral and Maxillofacial Surgery, 67 (12), pp. 2663-2668.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-71549160805&doi=10.1016%2fj.joms.2009.07.056&partnerID=40&md5=f13b165a46f7f6f503cd1e72841719cd

DOI: 10.1016/j.joms.2009.07.056

Aladag, C.H., Egrioglu, E., Kadilar, C.

Forecasting nonlinear time series with a hybrid methodology

(2009) Applied Mathematics Letters, 22 (9), pp. 1467-1470.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-67349285333&doi=10.1016%2fj.aml.2009.02.006&partnerID=40&md5=c8942fe5e9086f2682e5e3d1ef352708

DOI: 10.1016/j.aml.2009.02.006

Egrioglu, E., Aladag, C.H., Yolcu, U., Uslu, V.R., Basaran, M.A.

A new approach based on artificial neural networks for high order multivariate fuzzy time series

(2009) Expert Systems with Applications, 36 (7), pp. 10589-10594.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-67349187003&doi=10.1016%2fj.eswa.2009.02.057&partnerID=40&md5=f5abff1f597652a24998b184c13720af

DOI: 10.1016/j.eswa.2009.02.057

Egrioglu, E., Aladag, C.H., Yolcu, U., Basaran, M.A., Uslu, V.R.

A new hybrid approach based on SARIMA and partial high order bivariate fuzzy time series forecasting model

(2009) Expert Systems with Applications, 36 (4), pp. 7424-7434.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-60249083330&doi=10.1016%2fj.eswa.2008.09.040&partnerID=40&md5=c9d67d579d4346c524b8e009be3db802

DOI: 10.1016/j.eswa.2008.09.040

Yolcu, U., Egrioglu, E., Uslu, V.R., Basaran, M.A., Aladag, C.H.

A new approach for determining the length of intervals for fuzzy time series

(2009) Applied Soft Computing Journal, 9 (2), pp. 647-651.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-58549116080&doi=10.1016%2fj.asoc.2008.09.002&partnerID=40&md5=9447cd9cdc814e4ce22ba92a4fe38124

DOI: 10.1016/j.asoc.2008.09.002

Egrioglu, E., Uslu, V.R., Yolcu, U., Basaran, M.A., Hakan, A.C.

A new approach based on artificial neural networks for high order bivariate fuzzy time series

(2009) Advances in Intelligent and Soft Computing, 58, pp. 265-273.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-79551652450&doi=10.1007%2f978-3-540-89619-7_26&partnerID=40&md5=6ca0bb5e1537afb20b05dab3808ec3dd

DOI: 10.1007/978-3-540-89619-7_26

Aladag, C.H., Basaran, M.A., Egrioglu, E., Yolcu, U., Uslu, V.R.

Forecasting in high order fuzzy times series by using neural networks to define fuzzy relations

(2009) Expert Systems with Applications, 36 (3 PART 1), pp. 4228-4231.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-58349090456&doi=10.1016%2fj.eswa.2008.04.001&partnerID=40&md5=13029a21aca347fa0d0848af3363fca9

DOI: 10.1016/j.eswa.2008.04.001

Eǧrioǧlu, E., Aladaǧ, C.H., Günay, S.

A new model selection strategy in artificial neural networks

(2008) Applied Mathematics and Computation, 195 (2), pp. 591-597.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-37349082410&doi=10.1016%2fj.amc.2007.05.005&partnerID=40&md5=75f5f5ca7b3821472d76310dbc3de566

DOI: 10.1016/j.amc.2007.05.005

Aladag, C.H., Egrioglu, E., Gunay, S.

A new architecture selection strategy in solving seasonal autoregressive time series by artificial neural networks

(2008) Hacettepe Journal of Mathematics and Statistics, 37 (2), pp. 185-200.

https://www.scopus.com/inward/record.uri?eid=2-s2.0-77956270587&partnerID=40&md5=204f27179b1d16958c9b10cb36f8a9ed

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