A new dynamic firefly algorithm for demand estimation of water resources

Wang, Hui; Wang, Wenjun; Cui, Zhihua; Zhou, Xinyu; Zhao, Jia; Li, Ya

doi:10.1016/j.ins.2018.01.041

Cited by 139 publications

(49 citation statements)

References 32 publications

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“…Based on the above analysis, dimension learning is embedded into Equations (12) and (13). Then, the new search models are rewritten as below:…”

Section: Dimensional Learningmentioning

confidence: 99%

“…To effectively solve optimization problems, intelligent optimization methods have been presented. Some representative algorithms are particle swarm optimization [1][2][3][4][5], artificial bee colony (ABC) [6,7], differential evolution [8,9], firefly algorithm [10][11][12][13], earthworm optimization algorithm [14], cuckoo search [15,16], moth search [17], pigeon inspired optimization [18], bat algorithm [19][20][21][22][23], krill herd algorithm [24][25][26][27], and social network optimization [28]. Among these algorithms, ABC has few control parameters and strong exploration abilities [29,30].…”

Section: Introductionmentioning

confidence: 99%

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An Improved Artificial Bee Colony Algorithm Based on Elite Strategy and Dimension Learning

Xiao

Wang

et al. 2019

Mathematics

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Artificial bee colony is a powerful optimization method, which has strong search abilities to solve many optimization problems. However, some studies proved that ABC has poor exploitation abilities in complex optimization problems. To overcome this issue, an improved ABC variant based on elite strategy and dimension learning (called ABC-ESDL) is proposed in this paper. The elite strategy selects better solutions to accelerate the search of ABC. The dimension learning uses the differences between two random dimensions to generate a large jump. In the experiments, a classical benchmark set and the 2013 IEEE Congress on Evolutionary (CEC 2013) benchmark set are tested. Computational results show the proposed ABC-ESDL achieves more accurate solutions than ABC and five other improved ABC variants.

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“…Based on the above analysis, dimension learning is embedded into Equations (12) and (13). Then, the new search models are rewritten as below:…”

Section: Dimensional Learningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Improved Artificial Bee Colony Algorithm Based on Elite Strategy and Dimension Learning

Xiao

Wang

et al. 2019

Mathematics

Self Cite

View full text Add to dashboard Cite

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“…Intelligent optimization algorithms (IOAs) have attracted much attention in the past several years. Recently, different 2 Mathematical Problems in Engineering IOAs were proposed to solve various optimization problems [5][6][7][8][9][10][11][12][13]. ABC is a popular optimization algorithm based on swarm intelligence [1].…”

Section: Standard Abcmentioning

confidence: 99%

Improving Artificial Bee Colony Algorithm Using a Dynamic Reduction Strategy for Dimension Perturbation

Zhou

Wang

2019

Mathematical Problems in Engineering

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To accelerate the convergence speed of Artificial Bee Colony (ABC) algorithm, this paper proposes a Dynamic Reduction (DR) strategy for dimension perturbation. In the standard ABC, a new solution (food source) is obtained by modifying one dimension of its parent solution. Based on one-dimensional perturbation, both new solutions and their parent solutions have high similarities. This will easily cause slow convergence speed. In our DR strategy, the number of dimension perturbations is assigned a large value at the initial search stage. More dimension perturbations can result in larger differences between offspring and their parent solutions. With the growth of iterations, the number of dimension perturbations dynamically decreases. Less dimension perturbations can reduce the dissimilarities between offspring and their parent solutions. Based on the DR, it can achieve a balance between exploration and exploitation by dynamically changing the number of dimension perturbations. To validate the proposed DR strategy, we embed it into the standard ABC and three well-known ABC variants. Experimental study shows that the proposed DR strategy can efficiently accelerate the convergence and improve the accuracy of solutions.

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“…The inside KGAs are that the test server launched keyword-guessing attacks. Actually, such kind of attack also has been considered in deduplication system [30] and other security protocols [3,[31][32][33]. Specifically, the malicious server can create their ciphertext since the production of a PEKS ciphertext of keyword involves only public parameters.…”

Section: Introductionmentioning

confidence: 99%

A Secure Ciphertext Retrieval Scheme against Insider KGAs for Mobile Devices in Cloud Storage

Xie

et al. 2018

Security and Communication Networks

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With the advent of cloud computing, data privacy has become one of critical security issues and attracted much attention as more and more mobile devices are relying on the services in cloud. To protect data privacy, users usually encrypt their sensitive data before uploading to cloud servers, which renders the data utilization to be difficult. The ciphertext retrieval is able to realize utilization over encrypted data and searchable public key encryption is an effective way in the construction of encrypted data retrieval. However, the previous related works have not paid much attention to the design of ciphertext retrieval schemes that are secure against inside keyword-guessing attacks (KGAs). In this paper, we first construct a new architecture to resist inside KGAs. Moreover we present an efficient ciphertext retrieval instance with a designated tester (dCRKS) based on the architecture. This instance is secure under the inside KGAs. Finally, security analysis and efficiency comparison show that the proposal is effective for the retrieval of encrypted data in cloud computing.

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A new dynamic firefly algorithm for demand estimation of water resources

Cited by 139 publications

References 32 publications

An Improved Artificial Bee Colony Algorithm Based on Elite Strategy and Dimension Learning

An Improved Artificial Bee Colony Algorithm Based on Elite Strategy and Dimension Learning

Improving Artificial Bee Colony Algorithm Using a Dynamic Reduction Strategy for Dimension Perturbation

A Secure Ciphertext Retrieval Scheme against Insider KGAs for Mobile Devices in Cloud Storage

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