The greatest and fastest advances in the computing world today require researchers to
develop new problem-solving techniques capable of providing an optimal global solution …

The increased interest in renewable-based microgrids imposes several challenges, such as
source integration, power quality, and operating cost. Dealing with these problems requires …

Metaheuristic algorithms are increasingly utilized to solve complex optimization problems
because they can efficiently explore large solution spaces. The moss growth optimization …

Accurate parameter estimation of the equivalent circuit model (ECM) for Li-Ion batteries
(LiBs) allows for better behavior modeling and understanding. This is crucial for various …

For many electrical systems, such as renewable energy sources, their internal parameters
are exposed to degradation due to the operating conditions. Since the model's accuracy is …

Defining proper parameters for lithium-ion battery models is a challenge for several
applications, including automobiles powered by electricity. Conventional parameter …

The reservoir flood control operation problem has the characteristics of multiconstraint, high-
dimension, nonlinearity, and being difficult to solve. In order to better solve this problem, this …

Bald Eagle Search (BES) is a recent and highly successful swarm-based metaheuristic
algorithm inspired by the hunting strategy of bald eagles in capturing prey. With its …

Discrete grey forecasting models based on an accumulative operator have been widely
used in many practical fields. With the development of grey forecasting models, it is a …

The optimal parameter identification of lithium-ion (Li-ion) battery models is essential for
accurately capturing battery behavior and performance in electric vehicle (EV) applications …