Showing 1 - 20 results of 657 for search '(( Adaptive different evolution algorithm ) OR ( Adaptive different evaluation algorithm ))', query time: 0.25s Refine Results
  1. 1

    An Improved Human Evolution Optimization Algorithm for Unmanned Aerial Vehicle 3D Trajectory Planning by Xue Wang, Shiyuan Zhou, Zijia Wang, Xiaoyun Xia, Yaolong Duan

    Published 2025-01-01
    “…Furthermore, in the loser update strategy, an adaptive <i>t</i>-distribution perturbation strategy is utilized for its small mutation amplitude, which enhances the local search capability and robustness of the algorithm. …”
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    Harmony Search Based Parameter Ensemble Adaptation for Differential Evolution by Rammohan Mallipeddi

    Published 2013-01-01
    “…In differential evolution (DE) algorithm, depending on the characteristics of the problem at hand and the available computational resources, different strategies combined with a different set of parameters may be effective. …”
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    Article
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    An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration by Junwei Zhang, Liangqing Lyu

    Published 2025-04-01
    “…Based on this requirement, this paper proposes an actor–critic-based hyper-heuristic autonomous mission planning algorithm, which is used for mission planning and execution at different levels to support spacecraft Adaptive Space Scientific Exploration in deep space environments. …”
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    Matching heterogeneous ontologies with adaptive evolutionary algorithm by Xingsi Xue, Haolin Wang, Xin Zhou, Guojun Mao, Hai Zhu

    Published 2022-12-01
    “…Then, an Adaptive Evolutionary Algorithm (AEA) is proposed to effectively solve this problem. …”
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    Bayesian network structure learning algorithm based on hybrid binary salp swarm-differential evolution algorithm by Bin LIU, Ruixing FAN, Haoran LIU, Liyue ZHANG, Haiyu WANG, Chunlan ZHANG

    Published 2019-07-01
    “…Aiming at the disadvantages of Bayesian network structure learned by heuristic algorithms,which were trapping in local minimums and having low search efficiency,a method of learning Bayesian network structure based on hybrid binary slap swarm-differential evolution algorithm was proposed.An adaptive scale factor was used to balance local and global search in the swarm grouping stage.The improved mutation operator and crossover operator were taken into salp search strategy and differential search strategy respectively to renew different subswarms in the update stage.Two-point mutation operator was adopted to improve the swarm’s diversity in the stage of merging of subswarms.The convergence analysis of the proposed algorithm demonstrates that best structure can be found through the iterative search of population.Experimental results show that the convergence accuracy and efficiency of the proposed algorithm are improved compared with other algorithms.…”
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  7. 7

    An adaptive differential evolution algorithm using fitness distance correlation and neighbourhood-based mutation strategy by Wei Li, Yafeng Sun, Ying Huang, Jianbing Yi

    Published 2022-12-01
    “…However, the DE algorithm mainly focuses on strengthening the adaptability of exploitation, which allows the sensitivity of the DE algorithm to be solved in cases where the effects of solving various types of problems are quite different. …”
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  8. 8

    Differential Evolution with Novel Mutation and Adaptive Crossover Strategies for Solving Large Scale Global Optimization Problems by Ali Wagdy Mohamed, Abdulaziz S. Almazyad

    Published 2017-01-01
    “…This paper presents Differential Evolution algorithm for solving high-dimensional optimization problems over continuous space. …”
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    Improved Parallel Differential Evolution Algorithm with Small Population for Multi-Period Optimal Dispatch Problem of Microgrids by Tianle Li, Yifei Li, Fang Wang, Cheng Gong, Jingrui Zhang, Hao Ma

    Published 2025-07-01
    “…In the new approach, the main population of the parallel algorithm is divided into several small populations, and each performs the original operators of a differential evolution algorithm, i.e., mutation, crossover, and selection, in different processes concurrently. …”
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    Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

    Published 2024-11-01
    “…Seven different experimental data sets are used to improve the performance of the proposed differential evolution with an integrated mutation per iteration algorithm (DEIMA). …”
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    Comprehensive influence evaluation algorithm of complex network nodes based on global-local attributes by Weijin JIANG, Ying YANG, Tiantian LUO, Wenying ZHOU, En LI, Xiaowei ZHANG

    Published 2022-09-01
    “…Mining key nodes in the network plays a great role in the evolution of information dissemination, virus marketing, and public opinion control, etc.The identification of key nodes can effectively help to control network attacks, detect financial risks, suppress the spread of viruses diseases and rumors, and prevent terrorist attacks.In order to break through the limitations of existing node influence assessment methods with high algorithmic complexity and low accuracy, as well as one-sided perspective of assessing the intrinsic action mechanism of evaluation metrics, a comprehensive influence (CI) assessment algorithm for identifying critical nodes was proposed, which simultaneously processes the local and global topology of the network to perform node importance.The global attributes in the algorithm consider the information entropy of neighboring nodes and the shortest distance nodes between nodes to represent the local attributes of nodes, and the weight ratio of global and local attributes was adjusted by a parameter.By using the SIR (susceptible infected recovered) model and Kendall correlation coefficient as evaluation criteria, experimental analysis on real-world networks of different scales shows that the proposed method is superior to some well-known heuristic algorithms such as betweenness centrality (BC), closeness centrality (CC), gravity index centrality(GIC), and global structure model (GSM), and has better ranking monotonicity, more stable metric results, more adaptable to network topologies, and is applicable to most of the real networks with different structure of real networks.…”
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    Analysis of Block Adaptive Type-II Progressive Hybrid Censoring with Weibull Distribution by Kundan Singh, Yogesh Mani Tripathi, Liang Wang, Shuo-Jye Wu

    Published 2024-12-01
    “…Consequently, reliability performance and differences across different testing facilities are analyzed. …”
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    Personalized learning effect evaluation model for vocational education with cloud computing technology by Xiangyu Wang, Kang Cao

    Published 2025-12-01
    “…To achieve more efficient and accurate evaluation of learning effect, an adjustable variation genetic algorithm-backpropagation neural network (AGA-BP) is proposed. …”
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    QPSO-Based Adaptive DNA Computing Algorithm by Mehmet Karakose, Ugur Cigdem

    Published 2013-01-01
    “…However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. …”
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    Spatiotemporal Fusion Algorithm Based on Multikernal Adaptive Network by Qiuhui Wang, Qiong Ran, Ke Zheng, Jiaxin Li

    Published 2025-01-01
    “…The experimental results demonstrate that MKAN excels in multiple evaluation metrics. Compared to optimal comparison algorithms, MKAN increases structural similarity by an average of 1.4&#x0025; and reduces global dimensionless error by an average of 4.4&#x0025;, fully demonstrating the rationality and superiority of its design. …”
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