Improved metaheuristics-based clustering with multihop routing protocol for underwater wireless sensor networks
Underwater wireless sensor networks (UWSNs) comprise numerous underwater wireless
sensor nodes dispersed in the marine environment, which find applicability in several areas …
sensor nodes dispersed in the marine environment, which find applicability in several areas …
Migration-based moth-flame optimization algorithm
Moth–flame optimization (MFO) is a prominent swarm intelligence algorithm that
demonstrates sufficient efficiency in tackling various optimization tasks. However, MFO …
demonstrates sufficient efficiency in tackling various optimization tasks. However, MFO …
An improved moth-flame optimization algorithm with adaptation mechanism to solve numerical and mechanical engineering problems
Moth-flame optimization (MFO) algorithm inspired by the transverse orientation of moths
toward the light source is an effective approach to solve global optimization problems …
toward the light source is an effective approach to solve global optimization problems …
An innovative quadratic interpolation salp swarm-based local escape operator for large-scale global optimization problems and feature selection
M Qaraad, S Amjad, NK Hussein… - Neural Computing and …, 2022 - Springer
Salp swarm algorithm (SSA) is a unique swarm intelligent algorithm widely used for various
practical applications due to its simple framework and good optimization performance …
practical applications due to its simple framework and good optimization performance …
An improved nonlinear tuna swarm optimization algorithm based on circle chaos map and levy flight operator
W Wang, J Tian - Electronics, 2022 - mdpi.com
The tuna swarm optimization algorithm (TSO) is a new heuristic algorithm proposed by
observing the foraging behavior of tuna populations. The advantages of TSO are a simple …
observing the foraging behavior of tuna populations. The advantages of TSO are a simple …
Flexible job shop scheduling with stochastic machine breakdowns by an improved tuna swarm optimization algorithm
C Fan, W Wang, J Tian - Journal of Manufacturing Systems, 2024 - Elsevier
In job-shop production environments, machine breakdowns are a significant factor in
reducing productivity. Existing approaches seldom consider algorithm improvement and …
reducing productivity. Existing approaches seldom consider algorithm improvement and …
Towards higher-order zeroing neural network dynamics for solving time-varying algebraic Riccati equations
One of the most often used approaches for approximating various matrix equation problems
is the hyperpower family of iterative methods with arbitrary convergence order, whereas the …
is the hyperpower family of iterative methods with arbitrary convergence order, whereas the …
[PDF][PDF] Deep Learning Based Autonomous Transport System for Secure Vehicle and Cargo Matching.
T Shanthi, M Ramprasath, A Kavitha… - … Automation & Soft …, 2023 - cdn.techscience.cn
The latest 6G improvements secured autonomous driving's realism in Intelligent
Autonomous Transport Systems (IATS). Despite the IATS's benefits, security remains a …
Autonomous Transport Systems (IATS). Despite the IATS's benefits, security remains a …
Metaheuristic solution for stability analysis of nonlinear systems using an intelligent algorithm with potential applications
In this article, we provide a metaheuristic-based solution for stability analysis of nonlinear
systems. We identify the optimal level set in the state space of these systems by combining …
systems. We identify the optimal level set in the state space of these systems by combining …
SGGTSO: A Spherical Vector-Based Optimization Algorithm for 3D UAV Path Planning
W Wang, C Ye, J Tian - Drones, 2023 - mdpi.com
The application of 3D UAV path planning algorithms in smart cities and smart buildings can
improve logistics efficiency, enhance emergency response capabilities as well as provide …
improve logistics efficiency, enhance emergency response capabilities as well as provide …