Ant lion optimization: variants, hybrids, and applications
Ant Lion Optimizer (ALO) is a recent novel algorithm developed in the literature that
simulates the foraging behavior of a Ant lions. Recently, it has been applied to a huge …
simulates the foraging behavior of a Ant lions. Recently, it has been applied to a huge …
Opposition-based Laplacian equilibrium optimizer with application in image segmentation using multilevel thresholding
This paper proposes a modified version of freshly developed Equilibrium Optimizer (EO) for
segmentation of gray-scale images using multi-level thresholding. Laplace distribution …
segmentation of gray-scale images using multi-level thresholding. Laplace distribution …
Photovoltaic power prediction method for zero energy consumption buildings based on multi-feature fuzzy clustering and MAOA-ESN
N Li, L Li, F Huang, X Liu, S Wang - Journal of Building Engineering, 2023 - Elsevier
Due to their high efficiency and compatibility with building integration, photovoltaic (PV)
power generation systems are frequently utilized in zero energy buildings (ZEBs). However …
power generation systems are frequently utilized in zero energy buildings (ZEBs). However …
A new metaheuristic algorithm based on water wave optimization for data clustering
A Kaur, Y Kumar - Evolutionary Intelligence, 2022 - Springer
Data clustering is an important activity in the field of data analytics. It can be described as
unsupervised learning for grouping the similar objects into clusters. The similarity between …
unsupervised learning for grouping the similar objects into clusters. The similarity between …
Nonlinear programming for BESS operation for the improvement of economic, technical and environmental indices by considering grid-connected and stand-alone …
LF Grisales-Noreña, B Cortés-Caicedo… - Journal of Energy …, 2024 - Elsevier
This study addresses the problem of optimal Battery Energy Storage System (BESS)
operation in power distribution networks in a realistic scenario that reflects the variability in …
operation in power distribution networks in a realistic scenario that reflects the variability in …
A linearly adaptive Sine–cosine algorithm with application in deep neural network for feature optimization in arrhythmia classification using ECG signals
This work proposes a novel variant namely Linear Adaptive Sine–Cosine Algorithm (LA-
SCA) of newly developed metaheuristic called Sine–Cosine Algorithm (SCA). The …
SCA) of newly developed metaheuristic called Sine–Cosine Algorithm (SCA). The …
An improved antlion optimizer with dynamic random walk and dynamic opposite learning
Antlion optimization algorithm (ALO) has been one of the most popular meta-heuristic
algorithms to solve engineering optimization problems with a fast convergence speed and …
algorithms to solve engineering optimization problems with a fast convergence speed and …
An improved teaching–learning-based optimization algorithm with a modified learner phase and a new mutation-restarting phase
Teaching–learning-based optimization (TLBO) is a powerful metaheuristic algorithm for
solving complex optimization problems pertaining to the global optimum. Many TLBO …
solving complex optimization problems pertaining to the global optimum. Many TLBO …
An intelligent deep neural network with Opposition based Laplacian Equilibrium Optimizer to improve feature extraction using ECG signals
Problem The leading cause of death in the world is cardiovascular disease (CVD). It is
required to detect, prevent and manage cardiovascular diseases to reduce their effect and …
required to detect, prevent and manage cardiovascular diseases to reduce their effect and …
A novel generalized normal distribution arithmetic optimization algorithm for global optimization and data clustering problems
L Abualigah, M Altalhi - Journal of Ambient Intelligence and Humanized …, 2024 - Springer
In the recent years of the progress of data volumes and the emergence of complexity in
solving large and complex problems, the need for advanced and intelligent methods to deal …
solving large and complex problems, the need for advanced and intelligent methods to deal …