The increasing energy prices and pollutants from fossil fuels that threaten the climate, there
is a growing preference for renewable energy. The implementation of hybrid renewable …

As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

The simplicity, transparency, reliability, high efficiency and robust nature of PID controllers
are some of the reasons for their high popularity and acceptance for control in process …

Meta-heuristic algorithms are becoming more prevalent and have been widely applied in
various fields. There are numerous reasons for the success of such techniques in both …

Metaheuristics are an impressive area of research with extremely important improvements in
the solution of intractable optimization problems. Major advances have been made since the …

The purpose of community detection in complex networks is to identify the structural location
of nodes. Complex network methods are usually graphical, with graph nodes representing …

This paper proposes a novel global optimization algorithm called Political Optimizer (PO),
inspired by the multi-phased process of politics. PO is the mathematical map** of all the …

Resilient modulus (MR) plays the most critical role in the evaluation and design of flexible
pavement foundations. MR is utilised as the principal parameter for representing stiffness …

A reliable and accurate prediction of the tunnel boring machine (TBM) performance can
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …