Extracting knowledge from hybrid data, comprising both categorical and numerical data,
poses significant challenges due to the inherent difficulty in preserving information and …

The increasing complexity of modern power systems due to the integration of prosumers,
renewable energy sources, and energy storage, has significantly complicated system …

The study employs a predictive modelling approach using a fuzzy inference system to
assess the beekee** potential of a geographic area. Specifically, an adaptive neuro-fuzzy …

Neuro-fuzzy techniques have been widely used in many applications due to their ability to
generate interpretable fuzzy rules. Ensemble learning, on the other hand, is an emerging …

Ensemble models perform classification on data using multiple models combined and
unified to a single output. An important part of the ensemble is the combination or …

Экономика субъектов Российской Федерации, представляющих собой социо-эколого-
экономические системы, характеризуется быстро меняющимися условиями …

Realistic evaluation of uncertainty is crucial for informed decision-making in machine
learning (ML) models. Our study introduces a pioneering approach to quantify uncertainty in …

The study employs a predictive modelling approach using a fuzzy inference system to
assess the beekee** potential of a geographic area. Specifically, an adaptive neuro-fuzzy …

Machine Learning (ML) solutions have demonstrated significant improvements across
various domains. However, the complete integration of ML solutions into critical fields such …

Экономика субъектов Российской Федерации, представляющих собой социо-эколого-
экономические системы, характеризуется быстро меняющимися условиями …