Elephant Herding Optimization for Energy-Based Localization

Correia, Sérgio D.; Beko, Marko; Cruz, Luís A. da Silva; Tomic, Slaviša

doi:10.3390/s18092849

Cited by 41 publications

(7 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The state estimation of neural network is added in the ENN for updating the weight and the necessary expressions are given by Eqs. ( 20) and (21).…”

Section: Elman Neural Networkmentioning

confidence: 99%

See 1 more Smart Citation

Method for Fault Diagnosis and Speed Control of PMSM

Ghosh¹

2023

Computer Systems Science and Engineering

View full text Add to dashboard Cite

In the field of fault tolerance estimation, the increasing attention in electrical motors is the fault detection and diagnosis. The tasks performed by these machines are progressively complex and the enhancements are likewise looked for in the field of fault diagnosis. It has now turned out to be essential to diagnose faults at their very inception; as unscheduled machine downtime can upset deadlines and cause heavy financial burden. In this paper, fault diagnosis and speed control of permanent magnet synchronous motor (PMSM) is proposed. Elman Neural Network (ENN) is used to diagnose the fault of permanent magnet synchronous motor. Both the fault location and fault severity are considered. In this, eccentricity fault may occur in the motor. To control the speed of the permanent magnet synchronous motor, Dolphin Swarm Optimization (DSO) algorithm is used. The proposed work is simulated by using MATLAB in terms of amplitude, speed and torque. The comparison graph of speed vs. torque obtained by the proposed method gives better result compared to the other existing techniques. The proposed work is also compared with Particle Swarm Optimization (PSO) and Elephant Herding Optimization (EHO) algorithm. The proposed usage of Elman Neural Network to detect the fault and the usage of Dolphin Swarm Optimization algorithm to control the speed of the permanent magnet synchronous motor gives better outcome.

show abstract

“…The state estimation of neural network is added in the ENN for updating the weight and the necessary expressions are given by Eqs. ( 20) and (21).…”

Section: Elman Neural Networkmentioning

confidence: 99%

“…The proposed work is also being compared with other existing algorithms i.e., PSO [20] and EHO [21].…”

Section: Introductionmentioning

confidence: 99%

Method for Fault Diagnosis and Speed Control of PMSM

Ghosh¹

2023

Computer Systems Science and Engineering

View full text Add to dashboard Cite

show abstract

“…Traveling salesman problem [134][135] Knapsack [136] Acoustic energy-based positioning [137][138][139][140][141][142][143] Scheduling [144] Electrostatic powder coating process [145][146] Image safety model [147][148][149][150] Image processing [151][152][153] Wireless sensor networks [154] Feature selection [155][156][157] Optimal power flow [158][159] Distribution systems [160] Constrained optimization Linea and nonlinear constrained optimization [161] Economic dispatch problems [162] Multi-objective optimization QoS aware web service composition optimization [163] Civil engineering [164] Structural optimization [165] Figure 5. Engineering optimization/applications.…”

Section: Continuous Optimizationmentioning

confidence: 99%

“…Correia et al [155] applied the EHO algorithm to solve the energy-based source localization problem for wireless sensors networks. The energy decay model between two sensor nodes was matched through key optimized parameters of the EHO algorithm.…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

Elephant Herding Optimization: Variants, Hybrids, and Applications

et al. 2020

View full text Add to dashboard Cite

Elephant herding optimization (EHO) is a nature-inspired metaheuristic optimization algorithm based on the herding behavior of elephants. EHO uses a clan operator to update the distance of the elephants in each clan with respect to the position of a matriarch elephant. The superiority of the EHO method to several state-of-the-art metaheuristic algorithms has been demonstrated for many benchmark problems and in various application areas. A comprehensive review for the EHO-based algorithms and their applications are presented in this paper. Various aspects of the EHO variants for continuous optimization, combinatorial optimization, constrained optimization, and multi-objective optimization are reviewed. Future directions for research in the area of EHO are further discussed.

show abstract

“…EHO and ESWSA have proved to be very effective on different continuous problems especially on real-world applications such as computational biology and several other benchmarks (Correia et al, 2018;Li et al, 2020;Mandal, 2020Mandal, , 2022Meena et al, 2018;Sudip, 2018;Tuba et al, 2017;Wang Gai-Ge & Suash, 2015). Both methods yielded better results in comparison with other techniques such as PSO and GA (Sudip, 2018;Wang Gai-Ge & Suash, 2015).…”

mentioning

confidence: 99%

Association rule mining using new discrete elephant swarm approaches

Moulai

Drias

2022

Expert Systems

View full text Add to dashboard Cite

In this paper, we are proposing two novel swarm intelligence approaches for solving discrete problems. Two different continuous evolutionary algorithms inspired by the behaviour of elephants, namely elephant herding optimization and elephant swarm water search algorithm, are studied and analysed in order to propose discrete versions of the latter called discrete elephant herding optimization and discrete elephant swarm water search algorithm. As an illustration of how our proposals can work on discrete problems, a case study on association rule mining is carried out where the proposed discrete algorithms are modelled and applied on the problem in order to extract interesting association rules from large-scale databases. Extensive experiments on eight different real-life and relevant datasets with various sizes showed that both our proposals yield good results that compete and sometimes outperform state of the art algorithms.

show abstract

Elephant Herding Optimization for Energy-Based Localization

Cited by 41 publications

References 38 publications

Method for Fault Diagnosis and Speed Control of PMSM

Method for Fault Diagnosis and Speed Control of PMSM

Elephant Herding Optimization: Variants, Hybrids, and Applications

Association rule mining using new discrete elephant swarm approaches

Contact Info

Product

Resources

About