A systematic review of the whale optimization algorithm: theoretical foundation, improvements, and hybridizations
Despite the simplicity of the whale optimization algorithm (WOA) and its success in solving
some optimization problems, it faces many issues. Thus, WOA has attracted scholars' …
some optimization problems, it faces many issues. Thus, WOA has attracted scholars' …
Hybrid approaches to optimization and machine learning methods: a systematic literature review
Notably, real problems are increasingly complex and require sophisticated models and
algorithms capable of quickly dealing with large data sets and finding optimal solutions …
algorithms capable of quickly dealing with large data sets and finding optimal solutions …
Recent advances in Grey Wolf Optimizer, its versions and applications
The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
[HTML][HTML] The orb-weaving spider algorithm for training of recurrent neural networks
AS Mikhalev, VS Tynchenko, VA Nelyub, NM Lugovaya… - Symmetry, 2022 - mdpi.com
The quality of operation of neural networks in solving application problems is determined by
the success of the stage of their training. The task of learning neural networks is a complex …
the success of the stage of their training. The task of learning neural networks is a complex …
A novel particle swarm optimization-based grey model for the prediction of warehouse performance
Warehouses constitute a key component of supply chain networks. An improvement to the
operational efficiency and the productivity of warehouses is crucial for supply chain …
operational efficiency and the productivity of warehouses is crucial for supply chain …
Addressing feature selection and extreme learning machine tuning by diversity-oriented social network search: an application for phishing websites detection
Feature selection and hyper-parameters optimization (tuning) are two of the most important
and challenging tasks in machine learning. To achieve satisfying performance, every …
and challenging tasks in machine learning. To achieve satisfying performance, every …
AI-based metamaterial design
The use of metamaterials in various devices has revolutionized applications in optics,
healthcare, acoustics, and power systems. Advancements in these fields demand novel or …
healthcare, acoustics, and power systems. Advancements in these fields demand novel or …
Multi-objective optimization techniques: a survey of the state-of-the-art and applications: Multi-objective optimization techniques
In recent years, multi-objective optimization (MOO) techniques have become popular due to
their potentiality in solving a wide variety of real-world problems, including bioinformatics …
their potentiality in solving a wide variety of real-world problems, including bioinformatics …
[HTML][HTML] Layout and design optimization of ocean wave energy converters: A sco** review of state-of-the-art canonical, hybrid, cooperative, and combinatorial …
Ocean Wave energy is becoming a prominent technology, which is considered a vital
renewable energy resource to achieve the Net-zero Emissions Plan by 2050. It is also …
renewable energy resource to achieve the Net-zero Emissions Plan by 2050. It is also …
A novel hybrid model for predicting blast-induced ground vibration based on k-nearest neighbors and particle swarm optimization
XN Bui, P Jaroonpattanapong, H Nguyen, QH Tran… - Scientific reports, 2019 - nature.com
In this scientific report, a new technique of artificial intelligence which is based on k-nearest
neighbors (KNN) and particle swarm optimization (PSO), named as PSO-KNN, was …
neighbors (KNN) and particle swarm optimization (PSO), named as PSO-KNN, was …