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Non-linear and probabilistic state discretization functions for enhanced discrete reinforcement learning: Application on wind turbine pitch control

Alberto Gil-Maciá, J. Enrique Sierra-García, Matilde Santos • Machine Learning with Applications (2026)

Discrete reinforcement learning (RL) offers interpretability advantages compared to continuous reinforcement learning. Neural networks used in continuous RL behave like black boxes that do not show an obvious relationship between the system...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.mlwa.2026.100919

From Causes to Forecasts: Granger Causality and Machine Learning Predictions of Housing Sales in Türkiye

Musa Gün, Ahmet Akusta, Haydar Karadağ • İstanbul İktisat Dergisi (2025)

This study aims to examine the impact of macro-financial indicators on the housing sales volume in Türkiye and evaluate the forecasting performance of traditional time-series models versus modern machine-learning algorithms. Using monthly d...

DOAJ Open Access (DOAJ) DOI: 10.26650/ISTJECON2025-1707729

Global patterns of gully occurrence and their sensitivity to environmental changes

Yixian Chen, Sofie De Geeter, Jean Poesen, Francis Matthews et al. • International Soil and Water Conservation Research (2026)

Gully formation is a significant driver of soil erosion and land degradation worldwide and often leads to important downstream impacts. Nonetheless, our understanding of the global patterns and the factors controlling this process remains l...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.iswcr.2025.09.004

REVIEW OF THEORETICAL APPROACHES TO USING OF ARTIFICIAL INTELLIGENCE FOR PLANNING PROBLEMS IN ECONOMICS

Gocha Ugulava • ეკონომიკური პროფილი (2022)

Artificial intelligence methods and technologies are increasingly included in human's everyday life. Managing actors in the context of their activities, from the planning stage to the decision-making stage, are faced with the need to operat...

DOAJ Open Access (DOAJ) DOI: 10.52244/ep.2021.22.11