As one of the three pillars in computational intelligence, fuzzy systems are a powerful
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …

Adaptive Neuro‐Fuzzy Inference System (ANFIS) blends advantages of both Artificial Neural
Networks (ANNs) and Fuzzy Logic (FL) in a single framework. It provides accelerated …

In the present study, for the first time, a new framework is used by combining metaheuristic
algorithms, decomposition and machine learning for flood frequency analysis under climate …

This paper proposes a new computational model to predict the earth pressure balance
(EPB) shield performance during tunnelling. The proposed model integrates an improved …

In this study, the application of four evolutionary algorithms, continuous genetic algorithm
(CGA), particle swarm optimization (PSO), ant colony optimization for continuous domains …

Machine Learning (ML) techniques for time series prediction are becoming increasingly
accurate and helpful, particularly in considering climate change. As more methods are …

Accurate wind speed (WS) modelling is crucial for optimal utilization of wind energy.
Numerical Weather Prediction (NWP) techniques, generally used for WS modelling are not …

Global warming may lead to changes in nutritional composition and fish biodiversity in
estuaries due to the effect of increasing temperatures on Sillago fish occurrence …

Precise Air temperature modeling is crucial for a sustainable environment. In this study, a
novel binary optimized machine learning model, the random vector functional link (RVFL) …

Air temperature is a vital meteorological variable required in many applications, such as
agricultural and soil sciences, meteorological and climatological studies, etc. Given the …