Swarm intelligence

G Beni - Complex Social and Behavioral Systems: Game …, 2020 - Springer
SI can be seen also as part of the broader field of computational intelligence (CI)(Keller et al.
2016), which comprises computational methods for problems not solvable by the first …

An optimization model for electric vehicle battery charging at a battery swap** station

H Wu, GKH Pang, KL Choy… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
A new model for a viable battery swap** station is proposed to minimize its cost by
determining the optimized charging schedule for swapped electric vehicle (EV) batteries …

Machine Learning-driven optimization for SVM-based intrusion detection system in vehicular ad hoc networks

A Alsarhan, M Alauthman, E Alshdaifat… - Journal of Ambient …, 2023 - Springer
Abstract Machine learning (ML) driven solutions have been widely used to secure wireless
communications Vehicular ad hoc networks (VANETs) in recent studies. Unlike existing …

Generative artificial intelligence for designing multi-scale hydrogen fuel cell catalyst layer nanostructures

Z Niu, W Zhao, H Deng, L Tian, VJ Pinfield, P Ming… - ACS …, 2024 - ACS Publications
Multiscale design of catalyst layers (CLs) is important to advancing hydrogen
electrochemical conversion devices toward commercialized deployment, which has …

Day ahead carbon emission forecasting of the regional National Electricity Market using machine learning methods

V Aryai, M Goldsworthy - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Accurate forecasting of regional electrical grid carbon emissions is an essential part of
demand response programs for emissions reduction. Most existing research for short-term …

[書籍][B] Swarm intelligence and evolutionary computation: theory, advances and applications in machine learning and deep learning

G Kouziokas - 2023 - taylorfrancis.com
The aim of this book is to present and analyse theoretical advances and also emerging
practical applications of swarm and evolutionary intelligence. It comprises nine chapters …

Understanding the limitations of particle swarm algorithm for dynamic optimization tasks: A survey towards the singularity of PSO for swarm robotic applications

DE Gbenga, EI Ramlan - ACM Computing Surveys (CSUR), 2016 - dl.acm.org
One of the most widely used biomimicry algorithms is the Particle Swarm Optimization
(PSO). Since its introduction in 1995, it has caught the attention of both researchers and …

Speech emotion recognition using hybrid spectral-prosodic features of speech signal/glottal waveform, metaheuristic-based dimensionality reduction, and Gaussian …

F Daneshfar, SJ Kabudian, A Neekabadi - Applied Acoustics, 2020 - Elsevier
In this paper, a hybrid system consisting of three stages of feature extraction, dimensionality
reduction, and feature classification is proposed for speech emotion recognition (SER). At …

Speech emotion recognition using discriminative dimension reduction by employing a modified quantum-behaved particle swarm optimization algorithm

F Daneshfar, SJ Kabudian - Multimedia Tools and Applications, 2020 - Springer
Abstract In recent years, Speech Emotion Recognition (SER) has received considerable
attention in affective computing field. In this paper, an improved system for SER is proposed …

Particle swarm optimization of a hybrid wind/tidal/PV/battery energy system. Application to a remote area in Bretagne, France

OH Mohammed, Y Amirat, M Benbouzid - Energy Procedia, 2019 - Elsevier
A new method proposed in this work to optimize the power generated by a hybrid renewable
energy system which consists of Wind turbine/Tidal turbine/PV module/Batteries. This …