P. K. Tiwari et al. A Secure and Robust Machine Learning Model for Intrusion Detection in Internet of Vehicles, IEEE Access, 2025. [Link]

A. F. Tehrani and Manish Aggarwal, On extension of 2-copulas for information fusion,  Information Systems and Operational Research, 2024. [Link]

Manish Aggarwal, Raghunathan Krishankumar, Kattur Soundarapandian Ravichandran, Madasu Hanmandlu, Cloud vendor selection using choice models based on interactive criteria and varying attitudes of experts, Expert Systems with Applications, Volume 239, 2024. [Link]

Xinxing Wu, Zhiyi Zhu, Guanrong Chen, Witold Pedrycz, Lantian Liu, Manish Aggarwal, Gener- alized TODIM method based on symmetric intuitionistic fuzzy Jensen-Shannon divergence, Expert Systems with Applications, Volume 237, Part B, 2024. [Link]

Manish Aggarwal, On fuzzy entropy functions based on human attitude, Journal of the Operational Research Society, 2024. [Link]

Manish Aggarwal, An entropy framework for randomness and fuzziness, Expert Systems with Applications, Volume 243, 2024. [Link]

Manish Aggarwal, On Agent-specific Fuzzy Entropy Systems, IEEE Transactions on Systems, Man and Cybernetics: Systems, 2023. [Link]

Manish Aggarwal and M. Hanmandlu, On Modelling Ambiguity through Entropy, International Transactions in Operational Research, 2023. [Link]

Manish Aggarwal, R. Krishankumar, K. S. Ravichandran, T. Senapati, R. R. Yager, Assessing Potential of Organizations with Fuzzy Entropy, Operations Research Forum, 2023. [Link]

Manish Aggarwal, A. F. Tehrani, Heuristics-based Modelling of Human Decision Process, Iranian Journal of Fuzzy Systems, 2023. [Link]

R. Krishankumar, K. S. Ravichandran, Manish Aggarwal, D. Pamucar, An improved entropy function for the intuitionistic fuzzy sets with application to cloud vendor selection, Decision Analytics Journal, 2023. [Link]

Manish Aggarwal, Representing Uncertainty in Group Decision-making through the Hesitant Information Set Approach, Soft Computing, 2022. [Link]

Manish Aggarwal, Fuzzy Entropy Functions Based on Perceived Uncertainty, Knowledge and Information Systems, 64, pp. 2389-2409, 2022. [Link]

R. Krishankumar, D. M. Deveci, Manish Aggarwal, K. S. Ravichandran, Assessment of renewable energy sources for smart cities’ demand satisfaction using multi-hesitant fuzzy linguistic based choquet integral approach, Renewable Energy, Volume 189, 2022. [Link]

Manish Aggarwal, Attitude-based Entropy Function and Applications in Decision-Making, Engineering Applications of Artificial Intelligence. [Link]

Manish Aggarwal, Human Decision Making through an Entropic Framework, Expert Systems with Applications. [Link]

Manish Aggarwal, Entropy-based Logit Models of Discrete Choice, IEEE Transactions on Knowledge and Data Engineering. [Link]

Manish Aggarwal, Redefining Fuzzy Entropy with a General Framework, Expert Systems with Applications. [Link]

Manish Aggarwal, Representing uncertainty about fuzzy membership grade, Soft Computing. [Link]

R. Krishankumar, P. Rani, K. S. Ravichandran, Manish Aggarwal, X. Peng, An integrated and discriminative approach for group decision-making with probabilistic linguistic information, Soft Computing. [Link]

Manish Aggarwal, Modelling A Decision-maker’s Choice Behaviour through Perceived Values, IEEE Transactions on Systems, Man and Cybernetics: Systems. [Link]

Manish Aggarwal, Bridging the Gap Between Probabilistic and Fuzzy Entropy, IEEE Transactions on Fuzzy Systems. [Link]

Manish Aggarwal, Logit Choice Models for Interactive Attributes, Information Sciences, 2020.

Manish Aggarwal, Probit and Nested Logit Models based on Fuzzy Measure, Iranian Journal of Fuzzy Systems, 2020

Manish Aggarwal, Soft Information Set for Multi-Criteria Decision Making, International Journal of Intelligent Systems, 2020

Manish Aggarwal, Ali-Fallah Tehrani, Modelling Human Decision Behaviour with Preference-learning, INFORMS Journal on Computing, Vol. 31, Issue 2, pp. 193-410, 2019.

Manish Aggarwal, Learning of a Decision-Maker’s Preference Zone with an Evolutionary Approach, IEEE Transactions on Neural Networks and Learning Systems, vol.30, no. 3, pp. 670 – 682, March 2019.

Manish Aggarwal, A New Family of Fuzzy Discrete Choice Models, IEEE Transactions on Fuzzy Systems, 2019.

Manish Aggarwal, Decision-Aiding Model with Entropy-based Subjective Utility, Information Sciences, 2019.

R. Krishankumar, K. S. Ravichandran, Manish Aggarwal, S. K. Tyagi, Extended hesitant fuzzy linguistic term set with fuzzy confidence for solving group decision-making problems, Neural Computing and Applications, 2019

Manish Aggarwal, M. Hanmandlu, M. Keane, K. K. Biswas, Intuitionistic Fuzzy Multinomial Logit Model, IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 3, no. 1, pp. 85-89, Feb. 2019.

Manish Aggarwal, Attitudinal Choice Models with Applications in Human Decision Making, International Journal of Intelligent Systems, Vol. 34, Issue 7, pp. 1524-1554, July 2019.

Manish Aggarwal, Preferences-based learning of multinomial logit model, Knowledge and Information Systems, Vol. 59, Issue 3, pp 523–538, June 2019.

Manish Aggarwal, Generalized attitudinal Choquet integral, International Journal of Intelligent Systems, Vol.34, pp. 733-753, May 2019.

Manish Aggarwal, Confidence soft sets and applications in supplier selection, Computers and Industrial Engineering, vol. 127, pp. 614 – 624, January 2019.

Manish Aggarwal, Hesitant information sets and application in group decision making, Applied Soft Computing, vol. 75, pp. 120 -129, February 2019.

Manish Aggarwal, Modelling Subjective Utility through Entropy, Journal of the Operational Research Society, Vol. 70, Issue 4, pp. 634-654, 2019.

Manish Aggarwal, Learning Attitudinal Decision Model through Pair-wise Preferences, Kybernetes, vol. 47, no. 8, pp. 1569-1584, April 2018.

37. Manish Aggarwal, Attitudinal Choquet integrals and applications in decision making, International Journal of Intelligent Systems, vol. 33, no. 4, pp. 879-898, April 2018.

Manish Aggarwal, Adaptive linguistic weighted aggregation operators in multi-criteria decision making, Applied Soft Computing, vol. 58, pp. 690-699, Sep. 2017.

Manish Aggarwal, Rough Information Set and Its Applications in Decision Making, IEEE Transactions on Fuzzy Systems, no. 2, pp. 265 − 276, April 2017.

Manish Aggarwal, Learning of aggregation models in multi criteria decision making, Knowledge Based Systems, Vol. 119, pp. 1 − 9, March 2017

Manish Aggarwal, Discriminative aggregation operators for multi criteria decision making, Applied Soft Computing, Vol. 52, pp. 1058 − 1069, Mar. 2017.

Manish Aggarwal, Representation of Uncertainty with Information and Probabilistic Information Granules, International Journal of Fuzzy Systems, Vol. 19, Issue 5, pp 1617–1634, October 2017.

Manish Aggarwal, Linguistic Discriminative Aggregation in Multi-Criteria Decision Making, International Journal of Intelligent Systems, Vol. 31, no. 6, pp. 529 − 555, 2016.

Manish Aggarwal, On Learning of Choice Models with Interactive Attributes, IEEE Transactions on Knowledge & Data Engineering, Vol. 28 , Issue 10, pp. 2697 - 2708, Oct. 2016.

Manish Aggarwal, Probabilistic Variable Precision Fuzzy Rough Sets, IEEE Transactions on Fuzzy Systems, Vol. 24, no. 1, pp. 1 − 15, 2016.

Manish Aggarwal, M. Hanmandlu, Representing Uncertainty with Information Sets, IEEE Transactions on Fuzzy Systems, Vol. 24, no. 1, pp. 29 − 39, 2016.

Manish Aggarwal, On the Learning of Weights through Preferences, Information Sciences, Vol. 321, pp. 90 − 102, 2015.

Manish Aggarwal, Generalized Compensative Weighted Averaging Operators, Computers and Industrial Engineering, Vol. 87, pp. 81 − 90, 2015.

Manish Aggarwal, Compensative Weighted Averaging Operators, Applied Soft Computing, Vol. 28, pp. 368 − 378, 2015.

Manish Aggarwal, New Family of Induced OWA Aggregation Operators, International Journal of Intelligent Systems, Vol. 30, pp. 170 − 205, 2015.

Manish Aggarwal, Probabilistic Fuzzy Rough Sets, Journal of Intelligent and Fuzzy Systems, vol. 29, no. 5, pp. 1901 − 1912, 2015.

Manish Aggarwal, A. F. Tehrani, E. Hullermeier, Preference-based Learning of Ideal Solutions in TOPSIS-like Decision Models, Journal of Multi-Criteria Decision Analysis (Wiley), Vol. 22, no. 3 − 4, pp. 175 − 183, 2015.

Manish Aggarwal, T. Palpanas, Linguistic Rough Sets, International Journal of Machine Learning and Cybernetics (Springer), 2014.

Manish Aggarwal, K. K. Biswas, M. Hanmandlu, Generalized intuitionistic fuzzy soft sets with applications in decision-making, Applied Soft Computing, Vol. 13, Issue 8, 2013, pp. 3552 − 3566.

Manish Aggarwal, M. Hanmandlu, K. K. Biswas, A Probabilistic and Decision Attitude Aggregation Operator for Intuitionistic Fuzzy Environment, International Journal of Intelligent Systems, Vol. 28, Issue 8, 2013, pp. 806 − 839.

M. Aggarwal, M. Hanmandlu, Confidence Information Sets, 12th IADIS International Conference on Information Systems 2019, Utrecht, The Netherlands, 11-13 April, 2019

M. Aggarwal, M. Hanmandlu, Moderated Information Sets, 16th International Symposium on Neural Networks, July 10-12 2019, Moscow, Russia

M. Aggarwal, M. Hanmandlu, Information Measures for Hesitant Information Sets, 2018 2nd International Conference on Computational Biology and Bioinformatics, 11-13 Oct., 2018, Bari, Italy.

M. Aggarwal, M. Hanmandlu, Intelligent Controllers for Uncertain Systems, The 2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2018), 28-30 Jul. 2018, China.

M. Aggarwal J. Heinermann, S. Oehmcke, 0. Kramer, Preferences-Based Choice Prediction in Evolutionary Multi-objective Optimization, Evostar, European Conference on the Applications of Evolutionary Computation, 19-21 April 2017, Amsterdam, The Netherlands

M. Aggarwal, M. Hanmandlu, K. K. Biswas, The Properties and Information Measures for Information Sets, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE, 2014), 6 -11 July 2014, Beijing, China.

M. Aggarwal, M. Hanmandlu, K. K. Biswas, New Linguistic Aggregation Operators for Decision Making, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE, 2014), 6 - 11 July 2014, Beijing, China.

M. Aggarwal, K. K. Biswas, M. Hanmandlu, Intuitionistic fuzzy soft preference relations and application in decision making, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE, 2013) , pp. 1 - 8, 7 - 10 July 2013, Hyderabad, India.

M. Aggarwal, K. K. Biswas, M. Hanmandlu, Choquet integral vs. TOPSIS: An intuitionistic fuzzy approach, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE, 2013), pp. 1 - 8, 7 - 10 July 2013, Hyderabad, India.

M. Aggarwal, K. K. Biswas, M. Hanmandlu, Probabilistic Intuitionistic Fuzzy Models, 5th International Conference on Automation, Robotics and Applications (ICARA, 2011), pp. 214 - 219, Dec. 6 - 8, Wellington, New Zealand, 2011.

M. Aggarwal, K. K. Biswas, M. Hanmandlu, Fuzzy Model Building using Probabilistic Rules, International Conference on Fuzzy Computation Theory and Applications, IJCCI (FCTA, 2011), Scitepress, pp. 361 - 369, Paris, France, 24 - 26 Oct. 2011 Nominated for best student paper.

M. Aggarwal, K. K. Biswas, M. Hanmandlu, Relations in Generalized Intuitionistic Fuzzy Soft Sets, IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA, 2011), Sep 19 - 22, Ottawa, Canada, 2011.

M. Aggarwal, M. Hanmandlu, K. K. Biswas, Generalized intuitionistic fuzzy soft set and its application in practical medical diagnosis problem, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE, 2011), pp. 2972 - 2978, Taipei, Taiwan, 27 - 30 June 2011.

M. Aggarwal, M. Hanmandlu, Moderated Information Sets, in: Lecture Notes in Computer Science book series (LNCS, volume 11554), Advances in Neural Networks - ISNN 2019, Lu et al. (Eds.), Springer, Cham, LNCS 11554, pp. 418 - 425, 2019.

M. Aggarwal J. Heinermann, S. Oehmcke, 0. Kramer, Preferences-Based Choice Prediction in Evolutionary Multi-Objective Optimization, in: EvoApplications 2017, G. Squillero and K. Sim (Eds.), Springer, Cham, Part 1, LNCS 10199, pp. 1 - 10, 2017.

M. Aggarwal, K. K. Biswas, M. Hanmandlu, Handling Fuzzy Models in the Probabilistic domain, in: Computational Intelligence, Studies in Computational Intelligence (SCI), Madani et al. (Eds.), Springer, Berlin, pp. 137 -151, 2013.