Elitism based Shuffled Frog Leaping algorithm

Sharma, Pragya; Sharma, Nirmala; Sharma, Harish

doi:10.1109/icacci.2016.7732142

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…Here results depict that ISFLA is better at accuracy and efficiency level in comparison of GSA, SMO and DE. Boxplot analysis of average number of function evaluations (AFE) can also be designed for the comparison of considered algorithms ISFLA, GSA, SMO and DE [12]. The boxplot is a graphical representation of data, in which rectangle is drawn to represent the interquartile with a vertical line indicating the median value.…”

Section: B Analysis Of Resultsmentioning

confidence: 99%

Improved Shuffled Frog Leaping Algorithm

Jing

2017

IJASRE

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Section: B Analysis Of Resultsmentioning

confidence: 99%

Improved Shuffled Frog Leaping Algorithm

Jing

2017

IJASRE

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“…SFLA combines the global breadth search of the entire frog populations and the local depth search of frogs individual information, leading the algorithm towards the global optimum direction [25,31]. The frog representing the solution is divided into several subgroups, and each population has its own culture.…”

Section: Shuffled Frog Leapingmentioning

confidence: 99%

“…MED is also a valid approach to the period estimation problem [23]. However, given strong noise, the failure impact component will be lost by MED, and this is because of the following reasons [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

A New Method for Weak Fault Feature Extraction Based on Improved MED

Jiang

Fan

et al. 2018

Shock and Vibration

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Because of the characteristics of weak signal and strong noise, the low-speed vibration signal fault feature extraction has been a hot spot and difficult problem in the field of equipment fault diagnosis. Moreover, the traditional minimum entropy deconvolution (MED) method has been proved to be used to detect such fault signals. The MED uses objective function method to design the filter coefficient, and the appropriate threshold value should be set in the calculation process to achieve the optimal iteration effect. It should be pointed out that the improper setting of the threshold will cause the target function to be recalculated, and the resulting error will eventually affect the distortion of the target function in the background of strong noise. This paper presents an improved MED based method of fault feature extraction from rolling bearing vibration signals that originate in high noise environments. The method uses the shuffled frog leaping algorithm (SFLA), finds the set of optimal filter coefficients, and eventually avoids the artificial error influence of selecting threshold parameter. Therefore, the fault bearing under the two rotating speeds of 60 rpm and 70 rpm is selected for verification with typical low-speed fault bearing as the research object; the results show that SFLA-MED extracts more obvious bearings and has a higher signal-to-noise ratio than the prior MED method.

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Enhanced shuffled frog leaping algorithm with improved local exploration and energy-biased load reduction phase for load balancing of gateways in WSNs

Adamuthe¹,

Pathan²

2021

Open Computer Science

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Wireless sensor networks (WSNs) have grown widely due to their application in various domains, such as surveillance, healthcare, telecommunication, etc. In WSNs, there is a necessity to design energy-efficient algorithms for different purposes. Load balancing of gateways in cluster-based WSNs is necessary to maximize the lifetime of a network. Shuffled frog leaping algorithm (SFLA) is a popular heuristic algorithm that incorporates a deterministic approach. Performance of any heuristic algorithm depends on its exploration and exploitation capability. The main contribution of this article is an enhanced SFLA with improved local search capability. Three strategies are tested to enhance the local search capability of SFLA to improve the load balancing of gateways in WSNs. The first proposed approach is deterministic in which the participation of the global best solution in information exchange is increased. The next two variations reduces the deterministic approach in the local search component of SFLA by introducing probability-based selection of frogs for information exchange. All three strategies improved the success of local search. Second contribution of article is increased lifetime of gateways in WSNs with a novel energy-biased load reduction phase introduced after the information exchange step. The proposed algorithm is tested with 15 datasets of varying areas of deployment, number of sensors and number of gateways. Proposed ESFLA-RW variation shows significant improvement over other variations in terms of successful local explorations, best fitness values, average fitness values and convergence rate for all datasets. Obtained results of proposed ESFLA-RW are significantly better in terms of network energy consumption, load balancing, first gateway die and network life. The proposed variations are tested to check the effect of various algorithm-specific parameters namely frog population size, probability of information exchange and probability of energy-biased load reduction phase. Higher population size and probabilities give better solutions and convergence rate.

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Elitism based Shuffled Frog Leaping algorithm

Cited by 3 publications

References 14 publications

Improved Shuffled Frog Leaping Algorithm

Improved Shuffled Frog Leaping Algorithm

A New Method for Weak Fault Feature Extraction Based on Improved MED

Enhanced shuffled frog leaping algorithm with improved local exploration and energy-biased load reduction phase for load balancing of gateways in WSNs

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