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

“…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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A Multipopulation Firefly Algorithm for Correlated Data Routing in Underwater Wireless Sensor Networks by Ming Xu, Guangzhong Liu

“…Different groups of fireflies conduct their optimization in the evolution in order to improve the convergence speed and solution precision of the algorithm. …”
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A Constrained Multi-Objective Optimization Algorithm with a Population State Discrimination Model by Shaoyu Zhao, Heming Jia, Yongchao Li, Qian Shi

“…By dynamizing the CHTs, the proposed algorithm can adapt to a broader and more complex range of CMOPs. …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…The YOLOv5 (you only look once) method is designed to rapidly and accurately detect specific target objects and their locations in images after training on a sampled dataset. The YOLOv5 algorithm adopted in this study excels at detecting small targets and provides multi-scale detection, strong versatility, fast training, inference speeds, and adaptable fine-tuning capabilities. …”
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A Convex Adaptive Total Variation Model Based on the Gray Level Indicator for Multiplicative Noise Removal by Gang Dong, Zhichang Guo, Boying Wu

“…Different from the other methods, the parameters in the proposed algorithms are found dynamically.…”
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Multi-objective particle swarm optimization algorithm for task allocation and archived guided mutation strategies by Jianjie Chen, Yanmin Liu, Yi Luo, Aijia Ouyang, Jie Yang, Wuer Bai

“…Abstract In this paper, we propose a novel multi-objective particle swarm optimization algorithm with a task allocation and archive-guided mutation strategy (TAMOPSO), which effectively solves the problem of inefficient search in traditional algorithms by assigning different evolutionary tasks to particles with different characteristics. …”
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A novel extraction model optimization with effective separation coefficient for rare earth extraction process using improve differential evolution by Fangping Xu, Hui Yang, Jianyong Zhu, Wenjia Chang

“…Taking into account the multi-modal and multi-variable characteristics of the optimized objective function, we put forth an enhanced version of the improved differential evolution algorithm, the Linear-Chaos and Two Mutation Strategies of Adaptive Differential Evolution (LCTADE)with Covariance Matrix and Cauchy Perturbation(CC-LCTADE). …”
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A bi-subpopulation coevolutionary immune algorithm for multi-objective combinatorial optimization in multi-UAV task allocation by Xi Chen, Yu Wan, Jingtao Qi, Zipeng Zhao, Yirun Ruan, Jun Tang

“…Therefore, this paper constructs a Multi-objective Combinatorial Optimization in Multi-UAV Task Allocation Problem (MCOTAP) model, and proposes a Bi-subpopulation Coevolutionary Immune Algorithm (BCIA). The two coevolutionary mechanisms improve the lower limit of population diversity, and the evolutionary strategy pool integrating multiple strategies and the adaptive strategy selection mechanism enhance the local search ability in the late evolution. …”
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Evolutionary Artificial Intelligence Algorithm for Optimizing Step Phase Detection Based on Foot-Mounted Triaxial Accelerometer Data by P. A. Khmarskiy

“…Experiments involving walking along a closed square path confirmed the high accuracy and robustness of the proposed method: the match between the optimized and reference trajectories demonstrates the practical applicability of the approach for precise gait reconstruction under different conditions. The proposed methodology is easily adaptable to individual movement characteristics and can be integrated into modern wearable sensor systems for a wide range of scientific and applied tasks…”
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A Power Control Algorithm for V2V Communication Networks Based on Dynamic Multi-Objective Optimization by Mengyu Ma, Zihao Gu, Chao Wang, Zuxing Li, Jianyao Hu, Fuqiang Liu

“…We propose a prediction-based dynamic multi-objective optimization evolutionary algorithm (DMOEA) that facilitates the evolution of the solution population by predicting the centroid of the power allocation decision set in a new environment, so that transmission decisions can be made to adapt to the highly dynamic environment. …”
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FedDyH: A Multi-Policy with GA Optimization Framework for Dynamic Heterogeneous Federated Learning by Xuhua Zhao, Yongming Zheng, Jiaxiang Wan, Yehong Li, Donglin Zhu, Zhenyu Xu, Huijuan Lu

“…Finally, the framework introduces a genetic algorithm (GA) to simulate biological evolution, leveraging mechanisms such as gene selection, crossover, and mutation to optimize hyperparameter configurations. …”
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Numerical Scheme for the Pseudoparabolic Singularly Perturbed Initial-boundary Problem with Interior Transitional Layer by A. A. Bykov

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Revisiting the Control Systems of Autonomous Vehicles in the Agricultural Sector: A Systematic Literature Review by Vinayambika S. Bhat, Yong Wang

“…This approach enhances clarity in understanding algorithm suitability, adaptability, and scalability across different agricultural settings. …”
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IWOA-LSTM based intrinsic structural identification of steel fiber concrete by Ping Li, Jie Feng, Shiwei Duan

“…In order to accurately identify the high-temperature constitutive model taking into account the damage evolution, a high-temperature constitutive identification model using the Improved Whale Algorithm (IWOA) optimised Long Short-Term Memory (LSTM) neural network is presented. …”
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A systematic improvement of the high-quality temperature field reconstruction for acoustic pyrometry by Jingkao Tan, Na Li, Qulan Zhou, Yanyuan Hu, Lehang Chen, Zhongquan Gao, Jie Zhou

“…We used multiple means of improvement to improve the reconstruction performance of AP in a gradual and systematic manner. The fast finite-difference shooting method, the adaptive grid evolution strategy (AGES) and the radial basis function approximation with polynomial reproduction (RBFPR) were proposed and integrated into the sequential process optimization approach we concluded to systematically improve the reconstruction performance over the initial algorithm. …”
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A synergic quantum particle swarm optimisation for constrained combinatorial test generation by Xu Guo, Xiaoyu Song, Jian‐tao Zhou

“…Three auxiliary strategies, including contraction‐expansion coefficient adaptive change strategy, differential evolution strategy, and discretisation strategy, are proposed to improve the performance of QPSO. …”
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Characteristics of Eddy Dissipation Rates in Atmosphere Boundary Layer Using Doppler Lidar by Yufei Chu, Guo Lin, Min Deng, Zhien Wang

“…Building upon prior research utilizing Doppler lidar wind-field data, we optimized the EDR retrieval algorithm using a genetic adaptive approach. The newly developed algorithm demonstrates enhanced accuracy in EDR estimation. …”
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Robust Framework for PMU Placement and Voltage Estimation of Power Distribution Network by Nida Khanam, Mohd. Rihan, Salman Hameed

“…The suggested method uses a hybrid Multi-Objective Particle Swarm Optimization and Differential Evolution (MOPSO-DE) algorithm to find the best PMU positions and the Weighted Least Squares (WLS) method to estimate voltage magnitude. …”
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RLDEAO optimized of air quality data clustering analysis(RLDEAO优化的空气质量数据聚类分析) by 田闯(TIAN Chuang), 黄鹤(HUANG He), 杨澜(YANG Lan), 王会峰(WANG Huifeng), 茹锋(RU Feng)

“…In view of this deficiency, we propose the adaptive dimension-by-dimension keyhole imaging reverse learning strategy, Levy flight combined with stagnation perturbation strategy and mutation evolution of the survival of the fittest to improve the search performance of the algorithm, thus avoiding local optimization; Secondly, a weighted maximum minimum distance product (WMMP) is designed to calculate the cluster center point, which can reflect the importance of each feature in the data and play a good role to improve the clustering results; Finally, RLDEAO and WMMP are combined to optimize K-means complementary iteration. …”
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Prediction of Current and Future Distributions of Chalcophora detrita (Coleoptera: Buprestidae) Under Climate Change Scenarios by Arif Duyar, Muhammed Arif Demir, Mahmut Kabalak

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