Stability analysis of the particle dynamics in bat algorithm: standard and modified versions

Shirjini, Mahsa Fozuni; Nikanjam, Amin; Shoorehdeli, Mahdi Aliyari

doi:10.1007/s00366-020-00979-z

Cited by 8 publications

(5 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lyapunov stability analysis is based on the idea that if the total energy in the system continuously decreases, the system will asymptotically reach the zero energy state associated with the equilibrium point. The results reveal that the Lyapunov energy function decreases with time in the stability range of the algorithm's parameters, and the particles' trajectory shows the asymptotic stability of the particle dynamics [49].…”

Section: • Stability Analysismentioning

confidence: 95%

“…The success rate exceeded 70% in the trials [48]. Fozuni et al, analyzed the stability and convergence of particle dynamics in the standard BA version, addressed the limitations, and proposed new update relations [49]. In addition, the dynamics of the algorithm were investigated, and sufficient stability conditions were obtained using Lyapunov stability analysis.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Implementation of Machine Learning Algorithms on Multi-Robot Coordination

Yi̇ği̇t

Cankaya

2022

Electronics

View full text Add to dashboard Cite

Occasionally, professional rescue teams encounter issues while rescuing people during earthquake collapses. One such issue is the localization of wounded people from the earthquake. Machines used by rescue teams may cause crucial issues due to misleading localization. Usually, robot technology is utilized to address this problem. Many research papers addressing rescue operations have been published in the last two decades. In the literature, there are few studies on multi-robot coordination. The systems designed with a single robot should also overcome time constraints. A sophisticated algorithm should be developed for multi-robot coordination to solve that problem. Then, a fast rescuing operation could be performed. The distinctive property of this study is that it proposes a multi-robot system using a novel heuristic bat-inspired algorithm for use in search and rescue operations. Bat-inspired techniques gained importance in soft-computing experiments. However, there are only single-robot systems for robot navigation. Another original aspect of this paper is that this heuristic algorithm is employed to coordinate the robots. The study is devised to encourage extended work related to earthquake collapse rescue operations.

show abstract

Section: • Stability Analysismentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Implementation of Machine Learning Algorithms on Multi-Robot Coordination

Yi̇ği̇t

Cankaya

2022

Electronics

View full text Add to dashboard Cite

show abstract

“…Standard BAT algorithm 31 has certain inherent issues like failure to converge to global optima, multimodal optimization, poor exploration, slow rate of convergence, and no population diversity. To address these issues, various BAT variants have been introduced by researchers across the globe like Adaptive multi-swarm bat algorithm (AMBA) 32 , Bat with Mutation 33 , BATDNN 34 , Binary Bat algorithm, Differential Operator & Levy flights Bat 32 , Directed Artificial Bat Algorithm (DABA), Double- subpopulation Lévy flight bat algorithm (DLBA) 35 , Dynamic Virtual Bats Algorithm (DVBA) 36 , Improved Bat algorithm (cost estimation) 37 , Improved dynamic virtual bats algorithm with probabilistic selection 38 , Island multi populational parallel bat algorithm (IBA) 34 , Levy flight-based bat algorithm (LBA) 32 , LogisticBatDNN 33 , MeanBatDNN 33 , Modified Bat Algorithm (ANN) 33 , Modified Bat Algorithm (Stability Analysis) 39 , Multi-Objective bat algorithm (MOBA) 36 , Novel bat algorithm with multiple strategies coupling (mixBA) 40 , Piecewise-BatDNN 33 , shrink factor bat algorithm (SBA) 34 , Simplified Adaptive Bat based on frequency 41 , SinBatDNN 34 . Authors in Ref.…”

Section: Related Workmentioning

confidence: 99%

An efficient ANFIS-EEBAT approach to estimate effort of Scrum projects

Arora

Verma

Kavita

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Software effort estimation is a significant part of software development and project management. The accuracy of effort estimation and scheduling results determines whether a project succeeds or fails. Many studies have focused on improving the accuracy of predicted results, yet accurate estimation of effort has proven to be a challenging task for researchers and practitioners, particularly when it comes to projects that use agile approaches. This work investigates the application of the adaptive neuro-fuzzy inference system (ANFIS) along with the novel Energy-Efficient BAT (EEBAT) technique for effort prediction in the Scrum environment. The proposed ANFIS-EEBAT approach is evaluated using real agile datasets. It provides the best results in all the evaluation criteria used. The proposed approach is also statistically validated using nonparametric tests, and it is found that ANFIS-EEBAT worked best as compared to various state-of-the-art meta-heuristic and machine learning (ML) algorithms such as fireworks, ant lion optimizer (ALO), bat, particle swarm optimization (PSO), and genetic algorithm (GA).

show abstract

“…The main advantage of the bat algorithm is that it absorbs the advantages of other successful algorithms, parameter adjustment and frequency regulating, on the basis of bat individual echolocation. Literature (Shirjini et al, 2020) analyzes the convergence and stability of this algorithm in the respect of particle dynamics and investigates the dynamics of this algorithm. Literature (Osaba et al, 2016) uses this algorithm to solve the discrete combinatorial optimization problem, which is the traveling salesman problem.…”

Section: Sl-gaba Algorithmmentioning

confidence: 99%

A Diffraction Service Composition Approach Based on S-ABCPC

Min

Wang

et al. 2022

International Journal of Information System Modeling and Design

View full text Add to dashboard Cite

In recent years, the research on the QoS-aware service composition problem often assume that each component service in the process to be solved is equally essential, they do not consider the impact of core component services and other component services on problem-solving, or even though their impact is considered, they are not fully considered. So this paper first proposes a diffractive method based on them. Considering the advantages of Artificial Bee Colony (ABC) such as simplicity, this paper chooses it as the basic algorithm. In addition, with the continuous development of service ecosystem, it gradually formed a variety of domain features. They have an important influence on problem-solving, but the existing research has not explored this influence in-depth. Therefore, this paper digs deep into this influence. Given the characteristics of the problem to be solved in this paper, the S-ABCPC algorithm is designed. At last, experiments have proved the effectiveness of the method proposed in this paper. The impact factors of this method have been studied.

show abstract

Stability analysis of the particle dynamics in bat algorithm: standard and modified versions

Cited by 8 publications

References 45 publications

Implementation of Machine Learning Algorithms on Multi-Robot Coordination

Implementation of Machine Learning Algorithms on Multi-Robot Coordination

An efficient ANFIS-EEBAT approach to estimate effort of Scrum projects

A Diffraction Service Composition Approach Based on S-ABCPC

Contact Info

Product

Resources

About