Z. Ali, J. Moon, S. Gillani, S. Afzal, M. Bukhari, and S. Rho, "A Region-Aware Deep Learning Model for Dual-Subject Gait Recognition in Occluded Surveillance Scenarios," Computer Modeling in Engineering & Sciences, vol. 144, no. 2, pp. 2263–2286, 2025. [LINK]
M. Kim, H. Kim*, and J. Moon*, "Beginner-Friendly Review of Research on R-Based Energy Forecasting: Insights from Text Mining," Electronics, vol. 14, no. 17, p. 3513, 2025. (* Co-corresponding Authors) [LINK]
J. Moon and J. Woo, "CARE: Comprehensive Artificial Intelligence Techniques for Reliable Autism Evaluation in Pediatric Care," Computers, Materials & Continua, vol. 85, no. 1, pp. 1383–1425, 2025. [LINK]
S. Kim, B. Lee, M. Maqsood, J. Moon*, and S. Rho*, "Deep Learning-Based Natural Language Processing Model and Optical Character Recognition for Detection of Online Grooming on Social Networking Services," Computer Modeling in Engineering & Sciences, vol. 143, no. 2, pp. 2079–2108, 2025. (* Co-corresponding Authors) [LINK]
Z. Ali*, J. Moon*, S. Gillani, S. Afzal, M. Maqsood, and S. Rho, "Vision-based approach to knee osteoarthritis and Parkinson’s disease detection utilizing human gait patterns," PeerJ Computer Science, vol. 11, p. e2857, 2025. (* Co-first Authors) [LINK]
J. Lee, D. Jung, J. Moon*, and S. Rho*, "Advanced R-GAN: Generating anomaly data for improved detection in imbalanced datasets using regularized generative adversarial networks," Alexandria Engineering Journal, vol. 111, pp. 491–510, 2025. (* Co-corresponding Authors) [LINK]
M. Yasir, Y. Ansari, K. Latif, H. Maqsood, A. Habib, J. Moon, and S. Rho, "Machine learning-assisted efficient demand forecasting using endogenous and exogenous indicators for the textile industry," International Journal of Logistics Research and Applications, vol. 27, no. 12, pp. 2867–2886, 2024. [LINK]
M. Kim, J. Kang, I. Jeon, J. Lee, J. Park, S. Yeom, J. Jeong, J. Woo, and J. Moon*, "Differential Impacts of Environmental, Social, and Governance News Sentiment on Corporate Financial Performance in the Global Market: An Analysis of Dynamic Industries Using Advanced Natural Language Processing Models," Electronics, vol. 13, no. 22, p. 4507, 2024. (* Corresponding Author) [LINK]
J. Moon*, M. Maqsood*, D. So, S. W. Baik, S. Rho, and Y. Nam, "Advancing ensemble learning techniques for residential building electricity consumption forecasting: Insight from explainable artificial intelligence," PLoS ONE, vol. 19, no. 11, p. e0307654, 2024. (* Co-first Authors) [LINK]
I. Jeon, M. Kim, D. So, E. Y. Kim, Y. Nam, S. Kim, S. Shim, J. Kim*, and J. Moon*, "Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI," Diagnostics, vol. 14, no. 22, p. 2504, 2024. (* Co-corresponding Authors) [LINK]
B. Lee, S. Kim, M. Maqsood, J. Moon*, and S. Rho*, "Advancing Autoencoder Architectures for Enhanced Anomaly Detection in Multivariate Industrial Time Series," Computers, Materials & Continua, vol. 81, no. 1, pp. 1275–1300, 2024. (* Co-corresponding Authors) [LINK]
J. Moon*, M. Bukhari*, C. Kim, Y. Nam, M. Maqsood, and S. Rho, "Object detection under the lens of privacy: A critical survey of methods, challenges, and future directions," ICT Express, vol. 10, no. 5, pp. 1124–1144, 2024. (* Co-first Authors) [LINK]
J. Yoo and J. Moon*, "Bayesian Model Selection for Addressing Cold-Start Problems in Partitioned Time Series Prediction," Mathematics, vol. 12, no. 17, p. 2682, 2024. (* Corresponding Author) [LINK]
Y.-J. Han, J. Moon*, and J. Woo*, "Prediction of Churning Game Users Based on Social Activity and Churn Graph Neural Networks," IEEE Access, vol. 12, pp. 101971–101984, 2024. (* Co-corresponding Authors) [LINK]
B. Ali, M. Bukhari, M. Maqsood, J. Moon, E. Hwang, and S. Rho, "An end-to-end gait recognition system for covariate conditions using custom kernel CNN," Heliyon, vol. 10, no. 12, p. 32934, 2024. [LINK]
H. Min, S. Hong, J. Song, B. Son, B. Noh*, and J. Moon*, "SolarFlux Predictor: A Novel Deep Learning Approach for Photovoltaic Power Forecasting in South Korea," Electronics, vol. 13, no. 11, p. 2071, 2024. (* Co-corresponding Authors) [LINK]
J. Moon, "A Multi-Step-Ahead Photovoltaic Power Forecasting Approach Using One-Dimensional Convolutional Neural Networks and Transformer," Electronics, vol. 13, no. 11, p. 2007, 2024. [LINK]
J. Oh, D. So, J. Jo, N. Kang, E. Hwang*, and J. Moon*, "Two-Stage Neural Network Optimization for Robust Solar Photovoltaic Forecasting," Electronics, vol. 13, no. 9, p. 1659, 2024. (* Co-corresponding Authors) [LINK]
S. Leem, J. Oh, J. Moon*, M. Kim, and S. Rho*, "Enhancing multistep-ahead bike-sharing demand prediction with a two-stage online learning-based time-series model: insight from Seoul," The Journal of Supercomputing, vol. 80, pp. 4049–4082, 2024. (* Co-corresponding Authors) [LINK]
M. Bukhari, S. Yasmin, S. Naz, M. Y. Durrani, M. Javaid, J. Moon, and S. Rho, "A Smart Heart Disease Diagnostic System Using Deep Vanilla LSTM," Computers, Materials & Continua, vol. 77, no.1, pp. 1251–1279, 2023. [LINK]
D. So, J. Oh, I. Jeon, J. Moon*, M. Lee, and S. Rho*, "BiGTA-Net: A Hybrid Deep Learning-Based Electrical Energy Forecasting Model for Building Energy Management Systems," Systems, vol. 11, no. 9, p. 456, 2023. (* Co-corresponding Authors) [LINK]
D. So, J. Oh, S. Leem, H. Ha, and J. Moon*, "A Hybrid Ensemble Model for Solar Irradiance Forecasting: Advancing Digital Models for Smart Island Realization," Electronics, vol. 12, no. 12, p. 2607, 2023. (* Corresponding Author) [LINK]
J. Jang, W. Jeong, S. Kim, B. Lee, M. Lee, and J. Moon*, "RAID: Robust and Interpretable Daily Peak Load Forecasting via Multiple Deep Neural Networks and Shapley Values," Sustainability, vol. 15, no. 8, p. 6951, 2023. (* Corresponding Author) [LINK]
S. Leem, J. Oh, D. So, and J. Moon*, "Towards Data-Driven Decision-Making in the Korean Film Industry: An XAI Model for Box Office Analysis Using Dimension Reduction, Clustering, and Classification," Entropy, vol. 25, no. 4, p. 571, 2023. (* Corresponding Author) [LINK]
S. Cho*, J. Moon*, J. Bae, J. Kang, and S. Lee, "A Framework for Understanding Unstructured Financial Documents Using RPA and Multimodal Approach," Electronics, vol. 12, p. 939, 2023. (* Co-first Authors) [LINK]
Y. Ansari, S. Yasmin, S. Naz, H. Zaffar, Z. Ali, J. Moon, and S. Rho, "A Deep Reinforcement Learning-Based Decision Support System for Automated Stock Market Trading," IEEE Access, vol. 10, pp. 127469–127501, 2022. [LINK]
J. Moon, S. Rho, and S. W. Baik, "Toward explainable electrical load forecasting of buildings: A comparative study of tree-based ensemble methods with Shapley values," Sustainable Energy Technologies and Assessments, vol. 54, p. 102888, 2022. [LINK]
F. Ullah, J. Moon, H. Naeem, and S. Jabbar, "Explainable artificial intelligence approach in combating real-time surveillance of COVID19 pandemic from CT scan and X-ray images using ensemble model," The Journal of Supercomputing, vol. 78, pp. 19246–19271, 2022. [LINK]
A. Jabeen, M. Yasir, Y. Ansari, S. Yasmin, J. Moon, and S. Rho, "An Empirical Study of Macroeconomic Factors and Stock Returns in the Context of Economic Uncertainty News Sentiment Using Machine Learning," Complexity, vol. 2022, p. 4646733, 2022. [LINK]
J. Moon, S. Park, S. Rho, and E. Hwang, "Robust building energy consumption forecasting using an online learning approach with R ranger," Journal of Building Engineering, vol. 47, p. 103851, 2022. [LINK]
H. Maqsood, M. Maqsood, S. Yasmin, I. Mehmood, J. Moon, and S. Rho, "Analyzing the Stock Exchange Markets of EU Nations: A Case Study of Brexit Social Media Sentiment," Systems, vol. 10, no. 2, p. 24, 2022. [LINK]
J. Moon, S. Park, S. Rho, and E. Hwang, "Interpretable Short-Term Electrical Load Forecasting Scheme Using Cubist," Computational Intelligence and Neuroscience, vol. 2022, p. 6892995, 2022. [LINK]
J. Lee, J. Jeong, S. Jung, J. Moon, and S. Rho, "Verification of De-Identification Techniques for Personal Information Using Tree-Based Methods with Shapley Values," Journal of Personalized Medicine, vol. 12, no. 2, p. 190, 2022. [LINK]
M. J. Gul, G. M. Urfa, A. Paul, J. Moon, S. Rho, and E. Hwang, "Mid-term electricity load prediction using CNN and Bi-LSTM," The Journal of Supercomputing, vol. 77, pp. 10942–10958, 2021. [LINK]
T. Hussain, F. U. M. Ullah, K. Muhammad, S. Rho, A. Ullah, E. Hwang, J. Moon, and S. W. Baik, "Smart and intelligent energy monitoring systems: A comprehensive literature survey and future research guidelines," International Journal of Energy Research, vol. 45, no. 3, pp. 3590–3614, 2021. [LINK]
S. Jung, J. Moon, S. Park, and E. Hwang, "An Attention-Based Multilayer GRU Model for Multistep-Ahead Short-Term Load Forecasting," Sensors, vol. 21, no. 5, p. 1639, 2021. [LINK]
J. Park, J. Moon, S. Jung, and E. Hwang, "Multistep-Ahead Solar Radiation Forecasting Scheme Based on the Light Gradient Boosting Machine: A Case Study of Jeju Island," Remote Sensing, vol. 12, no. 14, p. 2271, 2020. [LINK]
J. Moon, S. Jung, J. Rew, S. Rho, and E. Hwang, "Combination of short-term load forecasting models based on a stacking ensemble approach," Energy and Buildings, vol. 216, p. 109921, 2020. [LINK]
J. Rew, Y. Cho, J. Moon, and E. Hwang, "Habitat Suitability Estimation Using a Two-Stage Ensemble Approach," Remote Sensing, vol. 12, no. 9, p. 1475, 2020. [LINK]
S. Jung, J. Moon, S. Park, S. Rho, S. W. Baik, and E. Hwang, "Bagging Ensemble of Multilayer Perceptrons for Missing Electricity Consumption Data Imputation," Sensors, vol. 20, no. 6, p. 1772, 2020. [LINK]
J. Moon, J. Kim, P. Kang, and E. Hwang, "Solving the Cold-Start Problem in Short-Term Load Forecasting Using Tree-Based Methods," Energies, vol. 13, no. 4, p. 886, 2020. [LINK]
S. Park, J. Moon, S. Jung, S. Rho, S. W. Baik, and E. Hwang, "A Two-Stage Industrial Load Forecasting Scheme for Day-Ahead Combined Cooling, Heating and Power Scheduling," Energies, vol. 13, no. 2, p. 443, 2020. [LINK]
J. Moon, S. Park, S. Rho, and E. Hwang, "A comparative analysis of artificial neural network architectures for building energy consumption forecasting," International Journal of Distributed Sensor Networks, vol. 15, no. 9, 2019. [LINK]
J. Kim, J. Moon, E. Hwang, and P. Kang, "Recurrent inception convolution neural network for multi short-term load forecasting," Energy and Buildings, vol. 194, pp. 328–341, 2019. [LINK]
J. Moon, Y. Kim, M. Son, and E. Hwang, "Hybrid Short-Term Load Forecasting Scheme Using Random Forest and Multilayer Perceptron," Energies, vol. 11, no. 12, p. 3283, 2018. [LINK]
J. Moon, J. Park, E. Hwang, and S. Jun, "Forecasting power consumption for higher educational institutions based on machine learning," The Journal of Supercomputing, vol. 74, no. 8, pp. 3778–3800, 2018. [LINK]
Y. Kim, J. Moon, and E. Hwang, "Constructing Differentiated Educational Materials Using Semantic Annotation for Sustainable Education in IoT Environments," Sustainability, vol. 10, no. 4, p. 1296, 2018. [LINK]
