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Forecasting

A taxonomy for detecting and preventing temporal data leakage in machine learning-based build prediction: A dual-platform empirical validation

Lalit Narayan Mishra, Amit Rangari, Sandesh Nagrare, Saroj Kumar Nayak

MixNet: A scale-adaptive method for multivariate time series forecasting

Xinhan Wang, Bowen Zhao

A hybrid BiLSTM and rule-based system for integrated diabetes prediction and personalized guidance

Muhammad Saleem, Muhammad Hamid, Saadia Malik

Eigen-guided transformer: A data-driven approach for chronic kidney disease forecasting

Fahman Saeed, Sultan Aldera

KGR-SKATER: Spatially clustered kernel graph regression for counting processes

Jeffrey Wu, Gareth W. Peters, Alex Franks

DG-LLM: Decomposition-based dynamic graph adaptation of large language models for spatiotemporal traffic forecasting

Sadia Tabassum, Naushin Nower

Pharmacogenomics knowledge and implementation readiness among community pharmacists in Jordan: A national cross-sectional study

Khalid Awad Al-Kubaisi, Derar H. Abdel-Qader, [ ... ], Ahmed Alhusban

Optimizing bike-sharing station locations: A machine learning and artificial neural networks approach using geospatial and demographic data

Marek Weis, Wojciech Dawid

RF-SVR-based prediction methodology for metal tube-bending rebound: Handling non-uniformity and limited sample challenges

Ziluo Fang, Pengfei Zhang, Liangyou Li, Qingzhu Zhang

Marketing analytics in banking 4.0: A two-stage explainable AI framework for high-accuracy and well-calibrated predictions

Fahim Nasir, Abdulghani Ali Ahmed, Iryna Yevseyeva, Mehmet Sabir Kiraz

Equity premium forecasting with reliability-screened forward-looking signals

Jeonggyu Huh, Jaegi Jeon, Seungwon Jeong

Predicting the uniaxial compressive strength and elasticity modulus of sandstones from physical and mechanical properties using statistical analyses and artificial intelligence-based techniques

Davood Fereidooni, Matloob Hejazifar

Interpretable prediction of dynamic compressive strength of red sandstone under wetting-drying cycles using ensemble learning

Bin Du, Wei Qi, Haibo Bai

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