River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …

In the last few years, methods falling within the family of randomization-based machine
learning models have grasped a great interest in the Artificial Intelligence community, mainly …

The use of wind energy plays a vital role in society owing to its economic and environmental
importance. Knowing the wind power generation within a specific time window is useful for …

This research attempts to study the Supplier Selection and Order Allocation Problem
(SSOAP) considering three crucial concepts, namely responsiveness, sustainability, and …

Accurate streamflow estimation is crucial for proper water management for irrigation,
hydropower, drinking and industrial purposes. The main aim of this study to adopt new data …

This study proposes an ensemble deep learning approach that integrates Bagging Ridge
(BR) regression with Bi-directional Long Short-Term Memory (Bi-LSTM) neural networks …

Recurrent Neural Networks (RNNs) have demonstrated their outstanding ability in sequence
tasks and have achieved state-of-the-art in wide range of applications, such as industrial …

Alzheimer's disease (AD) is a neurodegenerative disease of the human brain that affects
neurotransmitters, tissue, and neurons that impair the senses, memories, and behaviors …

Solar irradiance forecasting has been an essential topic in renewable energy generation.
Forecasting is an important task because it can improve the planning and operation of …

Abstract Feed Forward Neural Network (FFNN), Adaptive Neuro-fuzzy Inference System
(ANFIS), and Support Vector Regression (SVR) were applied for rainfall-runoff modeling of …