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Applying Adaptive and Self Assessment Fish Migration Optimization on Localization of Wireless Sensor Network on 3-D Te rrain.

Qing-Wei Chai, +3 more
- Vol. 11, pp 90-102
TLDR
An improved fish migration optimization (FMO), which adopts novel update equations of individuals and energy and a chieftain concept is introduced and it can attract individuals to exploitation around it.
Abstract
This paper presents an improved fish migration optimization (FMO), which adopts novel update equations of individuals and energy. A chieftain concept is introduced and it can attract individuals to exploitation around it. Therefore, the novel algorithm reduced the randomness and improved the convergence ability of the original algorithm. A more flexible update equation of energy is introduced which adjusts the amplitude of energy increase of individuals according to its fitness quality. The performance of the new algorithm is verified by CEC 2013 benchmark function. Besides, the novel algorithm is applied in solving the localization problem of Wireless Sensor Network (WSN) on 3-D terrain.

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Citations
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Simplified Phasmatodea population evolution algorithm for optimization

TL;DR: This work proposes a population evolution algorithm to deal with optimization problems based on the evolution characteristics of the Phasmatodea (stick insect) population, called the PPE, which has better performance than similar algorithms.
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Distribution network reconfiguration with distributed generation based on parallel slime mould algorithm

TL;DR: In this article , a parallel slime mold algorithm (PSMA) is proposed to solve the distribution network reconfiguration problem with distributed generation (DG) based on the parallel slime mould algorithm, and the results show that the PSMA can solve the DNR problem more accurately and quickly than the other three algorithms.
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Optimal Design and Simulation for PID Controller Using Fractional-Order Fish Migration Optimization Algorithm

TL;DR: In this paper, a fractional-order fish migration optimization (FOFMO) is proposed to improve the optimization performance of FMO, which is based on fractional calculus (FC) theory.
Journal ArticleDOI

Parallel fish migration optimization with compact technology based on memory principle for wireless sensor networks

TL;DR: In this paper , a parallel fish migration optimization algorithm with compact technology (PCFMO) was proposed to save memory space in WSNs. But, the performance of PCFMO was not compared with other well-known algorithms, such as Particle Swarm Optimization (PSO), Gray Wolf Optimization, Harris Hawks Optimisation (HHO), Salp Swarm Algorithm (SSA), FMO), Archimedes Optimization Algorithm, and Aquila Optimizer (AO).
Journal ArticleDOI

Modified Parallel Tunicate Swarm Algorithm and Application in 3D WSNs Coverage Optimization

TL;DR: A Modified Parallel Tunicate Swarm Algorithm (MPTSA) is proposed based on modified parallelism, which can improve the convergence of the algorithm and optimal global solution and improve the coverage of the whole network.
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