Considering the current research focus on the interpretability and efficiency of wind speed
prediction models, this research presents a novel prediction model for dynamic non …

Accurate short-term forecasting of water quality variables (WQVs) such as dissolved oxygen
(DO) and chlorophyll-a (Chl-a) is crucial for the effective management of aquatic resources …

The optimal parameter values in a feed-forward neural network model play an important role
in determining the efficiency and significance of the trained model. In this paper, we propose …

Metaheuristic optimization algorithms manage the search process to explore search
domains efficiently and are used efficiently in large-scale, complex problems. Transient …

Reducing student attrition in tertiary education plays a significant role in the core mission
and financial well-being of an educational institution. The availability of big data source from …

While multi-layer perceptrons (MLPs) remain popular for various classification tasks, their
application of gradient-based schemes for training leads to some drawbacks including …

Biopsy tests used in the identification and confirmation of breast cancer are time-consuming
and complex. Thus, neural networks can be applied to aid specialists with a prone to be in …

In today's world, agricultural production and operation activities generate a lot of data. As a
result, computer-aided agriculture applications have become a hot topic in the study, with …

Investigating the optimal laser processing parameters for industrial purposes can be time-
consuming. Moreover, an exact analytic model for this purpose has not yet been developed …

Arabic handwritten script recognition presents an energetic area of study. These types of
recognitions face several obstacles, such as vast open databases, boundless diversity in …