FA-Based Optimal Strategy of Train’s Energy Saving with Energy Materials

2012 ◽  
Vol 485 ◽  
pp. 93-96 ◽  
Author(s):  
Hui Hu
Keyword(s):  
Mathematical Model ◽  
Energy Saving ◽  
Optimization Algorithm ◽  
Optimal Strategy ◽  
Energy Efficient ◽  
Energy Materials ◽  
Ga Algorithm ◽  
Firefly Optimization ◽  
Simulation Results ◽  
Firefly Optimization Algorithm

According to one energy-efficient mathematical model which usually uses GA algorithm to solve, a new algorithm based on firefly optimization algorithm is applied to solve it. Through calculation for a cited example, simulation results such as speed-position curve are got. Compared with other methods, it demonstrates this new FA-based algorithm has a better performance and can be considered to be put into practical use.

FA-Based Optimal Strategy Study of Train's Energy Saving Operation under Disturbed Condition

2013 ◽  
Vol 339 ◽  
pp. 50-54
Author(s):  
Hui Hu
Keyword(s):  
Energy Saving ◽  
Energy Efficient ◽  
Chromosome Length ◽  
Railway Network ◽  
Disturbed Condition ◽  
Strategy Study ◽  
Computation Efficiency ◽  
Train Operation ◽  
Firefly Optimization ◽  
Firefly Optimization Algorithm

Different from changeable chromosome length genetic algorithm, a new method based on firefly optimization algorithm is put forward to search a trains energy saving operation strategy under running disturbance condition in railway network. The algorithm is designed and validated using a referenced simulation case. Compared with other methods, it demonstrates this new FA-based algorithm has a better result in computation efficiency and may be considered to use in other energy efficient train operation models.

Evaluation of the trust values among human resources in the enterprise cloud using an optimization algorithm and fuzzy logic

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lantian Li ◽  
Bahareh Pahlevanzadeh
Keyword(s):  
Optimization Algorithm ◽  
Heuristic Algorithms ◽  
Human Life ◽  
Cloud Services ◽  
Cloud Provider ◽  
Suggested Approach ◽  
Content Type ◽  
Firefly Optimization ◽  
Security Costs ◽  
Firefly Optimization Algorithm

PurposeCloud eases information processing, but it holds numerous risks, including hacking and confidentiality problems. It puts businesses at risk in terms of data security and compliance. This paper aims to maximize the covered human resource (HR) vulnerabilities and minimize the security costs in the enterprise cloud using a fuzzy-based method and firefly optimization algorithm.Design/methodology/approachCloud computing provides a platform to improve the quality and availability of IT resources. It changes the way people communicate and conduct their businesses. However, some security concerns continue to derail the expansion of cloud-based systems into all parts of human life. Enterprise cloud security is a vital component in ensuring the long-term stability of cloud technology by instilling trust. In this paper, a fuzzy-based method and firefly optimization algorithm are suggested for optimizing HR vulnerabilities while mitigating security expenses in organizational cloud environments. MATLAB is employed as a simulation tool to assess the efficiency of the suggested recommendation algorithm. The suggested approach is based on the firefly algorithm (FA) since it is swift and reduces randomization throughout the lookup for an optimal solution, resulting in improved performance.FindingsThe fuzzy-based method and FA unveil better performance than existing met heuristic algorithms. Using a simulation, all the results are verified. The study findings showed that this method could simulate complex and dynamic security problems in cloud services.Practical implicationsThe findings may be utilized to assist the cloud provider or tenant of the cloud infrastructure system in taking appropriate risk mitigation steps.Originality/valueUsing a fuzzy-based method and FA to maximize the covered HR vulnerabilities and minimize the security costs in the enterprise cloud is the main novelty of this paper.

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