Circulatory System Based Optimization (CSBO): an expert multilevel biologically inspired meta-heuristic algorithm
The optimization problems are becoming more complicated, requiring new and efficient
optimization techniques to solve them. Many bio-inspired meta-heuristic algorithms have …
optimization techniques to solve them. Many bio-inspired meta-heuristic algorithms have …
A stochastic configuration network based on chaotic sparrow search algorithm
Stochastic configuration network (SCN), as a novel incremental generation model with
supervisory mechanism, has an excellent superiority in solving large-scale data regression …
supervisory mechanism, has an excellent superiority in solving large-scale data regression …
[HTML][HTML] A survey of recently developed metaheuristics and their comparative analysis
A Alorf - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
The aim of this study was to gather, discuss, and compare recently developed
metaheuristics to understand the pace of development in the field of metaheuristics and …
metaheuristics to understand the pace of development in the field of metaheuristics and …
[HTML][HTML] Modeling of drilling process of GFRP composite using a hybrid random vector functional link network/parasitism-predation algorithm
Non-laminated glass fiber-reinforced epoxy composites (GFREC) have shown promising
applications in various engineering fields. In this study, an experimental investigation …
applications in various engineering fields. In this study, an experimental investigation …
A Comprehensive Review on Heart Disease Risk Prediction using Machine Learning and Deep Learning Algorithms
Cardiovascular diseases claim approximately 17.9 million lives annually, with heart attacks
and strokes accounting for over 80% of these deaths. Key risk factors, including …
and strokes accounting for over 80% of these deaths. Key risk factors, including …
[HTML][HTML] An efficient adaptive-mutated coati optimization algorithm for feature selection and global optimization
The feature selection (FS) problem has occupied a great interest of scientists lately since the
highly dimensional datasets might have many redundant and irrelevant features. FS aims to …
highly dimensional datasets might have many redundant and irrelevant features. FS aims to …
Predicting solar distiller productivity using an AI Approach: Modified genetic algorithm with Multi-Layer Perceptron
Abstract Solar Stills (SSs) are an eco-friendly and efficient approach to generating drinking
water from brackish or saline sources. In this paper, a novel model for predicting the …
water from brackish or saline sources. In this paper, a novel model for predicting the …
Reliable applied objective for identifying simple and detailed photovoltaic models using modern metaheuristics: Comparative study
The first issue in the optimal photovoltaic system design is providing an accurate PV model
that emulates the system behaviour under several environmental conditions. The accuracy …
that emulates the system behaviour under several environmental conditions. The accuracy …
Large scale salp-based grey wolf optimization for feature selection and global optimization
Salp swarm algorithm (SSA) is a recently developed meta-heuristic swarm intelligence
optimization algorithm based on simulating the chain movement behavior of salps sailing …
optimization algorithm based on simulating the chain movement behavior of salps sailing …
Improved salp swarm algorithm based on levy flight and sine cosine operator
J Zhang, JS Wang - Ieee Access, 2020 - ieeexplore.ieee.org
The salp swarm algorithm (SSA) is a swarm intelligence optimization algorithm that
simulates the chain movement behavior of salp populations in the sea. Aiming at the …
simulates the chain movement behavior of salp populations in the sea. Aiming at the …