Adaptive niche quantum-inspired immune clonal algorithm

Liu, Jianyong; Wang, Huaixiao; Sun, Yangyang; Li, Ling

doi:10.1007/s11047-015-9495-4

Cited by 8 publications

(3 citation statements)

References 14 publications

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“…Niche immunity is exploited in this paper to restrict over duplication of similar individuals, so as to ensure the diversity of population. The detailed steps of NI algorithm are displayed in [23]. LA optimized by NI can be performed as follow:…”

Section: La Improved By Niche Immunementioning

confidence: 99%

Short-Term Load Forecasting for Electric Vehicle Charging Station Based on Niche Immunity Lion Algorithm and Convolutional Neural Network

Huang

Zhang

2018

Energies

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Accurate and stable prediction of short-term load for electric vehicle charging stations is of great significance in ensuring economical and safe operation of electric vehicle charging stations and power grids. In order to improve the accuracy and stability of short-term load forecasting for electric vehicle charging stations, an innovative prediction model based on a convolutional neural network and lion algorithm, improved by niche immunity, is proposed. Firstly, niche immunity is utilized to restrict over duplication of similar individuals, so as to ensure population diversity of lion algorithm, which improves the optimization performance of the lion algorithm significantly. The lion algorithm is then employed to search the optimal weights and thresholds of the convolutional neural network. Finally, a proposed short-term load forecasting method is established. After analyzing the load characteristics of the electric vehicle charging station, two cases in different locations and different months are selected to validate the proposed model. The results indicate that the new hybrid proposed model offers better accuracy, robustness, and generality in short-term load forecasting for electric vehicle charging stations.

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Section: La Improved By Niche Immunementioning

confidence: 99%

Short-Term Load Forecasting for Electric Vehicle Charging Station Based on Niche Immunity Lion Algorithm and Convolutional Neural Network

Huang

Zhang

2018

Energies

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“…Parameter optimization is widely studied in many applications associated with SVM. For example, Liu proposed an adaptive niche quantum-inspired immune clonal algorithm for making the multi-modal function more effectively and converge to extreme value points based on the quantum coding, immune clone, and niche mechanism [2]. Demidova presented an improved particle swarm optimization algorithm for searching the kernel function type, kernel function parameter, and regularization parameter simultaneously [3].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Support Vector Machine Parameters based on Quantum and Immune Algorithm

Tian¹

2019

IJPE

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In view of premature convergence and blind searching of the quantum and immune algorithm in the evolution process, this paper proposes two improvements. Firstly, the fitness function is improved by utilizing the mean square error as the fitness function, and the concentration of immune antibodies is introduced to the fitness function to improve the diversity of populations and avoid premature convergence of the algorithm. Secondly, the probability of rotation is adopted to optimize the quantum rotate gate to avoid blind searching and accelerate the convergence of the algorithm. The improved algorithm is adopted to optimize parameters of support vector machines and is applied to network intrusion detection. The experimental results show that the improved algorithm has better optimization effects.

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“…al. combine quantum coding, immune clone and niche mechanism together to solve multi-modal function optimization more effectively [7]; Tzyy-Chyang Lu proposed a region-based QEA, the algorithm adopted quantum bit representation for the selection of regions; Its search process uses a region-by-region exploration in the beginning and, as the candidate regions are identified, a randomized search in good regions is employed for exploitation [8]; Qian Jie et al proposed a statistical learning QEA. Experiments had shown that this new design could avoid premature convergence [9].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Collaborative Quantum-Inspired Evolutionary Algorithm for Global Numerical Functions

Zhou

Shao

2018

ITM Web Conf.

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Abstract. -A novel adaptive collaborative quantum-inspired evolutionary algorithm (ACQEA) is proposed by combining the collaborative evolution and adaptive mutation mechanism together in this paper. In ACQEA, the whole population will be divided into multi sub-populations which can complete the evolution independently, and then the collaborative evolution mechanism is used to make these multi sub-populations full exchange their evolution information in operation process. In addition, the adaptive mutation and update strategies are implemented in order to give ACQEA the power to explore its search space on the basis of characteristic information of the elite individual and corresponding population diversity. Finally, the proposed ACQEA is compared with existing quantum evolution algorithm (QEA) in solving global numerical functions and the experiments results verify that the advantages of ACQEA on convergence rate and searching accuracy.

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Adaptive niche quantum-inspired immune clonal algorithm

Cited by 8 publications

References 14 publications

Short-Term Load Forecasting for Electric Vehicle Charging Station Based on Niche Immunity Lion Algorithm and Convolutional Neural Network

Short-Term Load Forecasting for Electric Vehicle Charging Station Based on Niche Immunity Lion Algorithm and Convolutional Neural Network

Optimizing Support Vector Machine Parameters based on Quantum and Immune Algorithm

Adaptive Collaborative Quantum-Inspired Evolutionary Algorithm for Global Numerical Functions

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