[HTML][HTML] Differential evolution: A recent review based on state-of-the-art works
Differential evolution (DE) is a popular evolutionary algorithm inspired by Darwin's theory of
evolution and has been studied extensively to solve different areas of optimisation and …
evolution and has been studied extensively to solve different areas of optimisation and …
On hyperparameter optimization of machine learning algorithms: Theory and practice
Abstract Machine learning algorithms have been used widely in various applications and
areas. To fit a machine learning model into different problems, its hyper-parameters must be …
areas. To fit a machine learning model into different problems, its hyper-parameters must be …
Differential Evolution: A review of more than two decades of research
Since its inception in 1995, Differential Evolution (DE) has emerged as one of the most
frequently used algorithms for solving complex optimization problems. Its flexibility and …
frequently used algorithms for solving complex optimization problems. Its flexibility and …
Chaotic multi-swarm whale optimizer boosted support vector machine for medical diagnosis
Support vector machine (SVM) is a widely used pattern classification method that its
classification accuracy is greatly influenced by both kernel parameter setting and feature …
classification accuracy is greatly influenced by both kernel parameter setting and feature …
Heuristic approaches to address vehicle routing problem in the Iot-based waste management system
Nowadays, population growth and urban development lead to having an efficient waste
management system (WMS) based on recent advances and trends. Alongside all functions …
management system (WMS) based on recent advances and trends. Alongside all functions …
Toward an optimal kernel extreme learning machine using a chaotic moth-flame optimization strategy with applications in medical diagnoses
This study proposes a novel learning scheme for the kernel extreme learning machine
(KELM) based on the chaotic moth-flame optimization (CMFO) strategy. In the proposed …
(KELM) based on the chaotic moth-flame optimization (CMFO) strategy. In the proposed …
A literature survey of benchmark functions for global optimisation problems
Test functions are important to validate and compare the performance of optimisation
algorithms. There have been many test or benchmark functions reported in the literature; …
algorithms. There have been many test or benchmark functions reported in the literature; …
Metaheuristics in large-scale global continues optimization: A survey
Metaheuristic algorithms are extensively recognized as effective approaches for solving high-
dimensional optimization problems. These algorithms provide effective tools with important …
dimensional optimization problems. These algorithms provide effective tools with important …
An enhanced grey wolf optimization based feature selection wrapped kernel extreme learning machine for medical diagnosis
In this study, a new predictive framework is proposed by integrating an improved grey wolf
optimization (IGWO) and kernel extreme learning machine (KELM), termed as IGWO‐KELM …
optimization (IGWO) and kernel extreme learning machine (KELM), termed as IGWO‐KELM …
Interior search algorithm (ISA): a novel approach for global optimization
AH Gandomi - ISA transactions, 2014 - Elsevier
This paper presents the interior search algorithm (ISA) as a novel method for solving
optimization tasks. The proposed ISA is inspired by interior design and decoration. The …
optimization tasks. The proposed ISA is inspired by interior design and decoration. The …