An innovative hybrid heap-based and jellyfish search algorithm for combined heat and power economic dispatch in electrical grids
This paper proposes a hybrid algorithm that combines two prominent nature-inspired meta-
heuristic strategies to solve the combined heat and power (CHP) economic dispatch. In this …
heuristic strategies to solve the combined heat and power (CHP) economic dispatch. In this …
Advanced Data-Driven Fault Diagnosis in Lithium-Ion Battery Management Systems for Electric Vehicles: Progress, Challenges, and Future Perspectives
Hazards in electric vehicles (EVs) often stem from lithium-ion battery (LIB) packs during
operation, aging, or charging. Robust early fault diagnosis algorithms are essential for …
operation, aging, or charging. Robust early fault diagnosis algorithms are essential for …
Gradient-based elephant herding optimization for cluster analysis
Y Duan, C Liu, S Li, X Guo, C Yang - Applied Intelligence, 2022 - Springer
Clustering analysis is essential for obtaining valuable information from a predetermined
dataset. However, traditional clustering methods suffer from falling into local optima and an …
dataset. However, traditional clustering methods suffer from falling into local optima and an …
A hybrid chaotic-based multiobjective differential evolution technique for economic emission dispatch problem
The economic emission dispatch problem (EEDP) is a nonconvex and nonsmooth
multiobjective optimization problem in the power system field. Generally, fuel cost and total …
multiobjective optimization problem in the power system field. Generally, fuel cost and total …
Economic sustainability enhancement by the integration of renewable energy in a deregulated system: A study
The global energy system is continuously changing, driven by increasing power demands
and the urgent need to address environmental challenges. This highlights the necessity of …
and the urgent need to address environmental challenges. This highlights the necessity of …
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms.
Abstract Radial Basis Function Neural Network (RBFNN) ensembles have long suffered
from non-efficient training, where incorrect parameter settings can be computationally …
from non-efficient training, where incorrect parameter settings can be computationally …
A Novel Modified Gorilla Troops Optimizer Algorithm for Interline Power Flow Controller-Based Damping Controller Design
RK Khadanga, D Das, S Panda… - Energy Exploration …, 2024 - journals.sagepub.com
To stabilize frequency in a power system, this research study suggests a novel modified
Gorilla Troops Optimizer (mGTO) technique, which builds on the original technique, and …
Gorilla Troops Optimizer (mGTO) technique, which builds on the original technique, and …
Optimal control by pattern search optimization method
K Kandhway - 2022 14th International Conference on …, 2022 - ieeexplore.ieee.org
In this work, we demonstrate the use of pattern search optimization method in numerically
solving optimal control problems. Pattern search is a derivative free optimization method and …
solving optimal control problems. Pattern search is a derivative free optimization method and …
An Improved Bio-Inspired Material Generation Algorithm for Engineering Optimization Problems Including PV Source Penetration in Distribution Systems
The Material Generation Optimization (MGO) algorithm is an innovative approach inspired
by material chemistry which emulates the processes of chemical compound formation and …
by material chemistry which emulates the processes of chemical compound formation and …