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  1. 1081

    A Dynamic Neural Network Optimization Model for Heavy Metal Content Prediction in Farmland Soil by Kun Cao, Cong Zhang, Liangliang Li, Shuaifeng Li

    Published 2022-01-01
    “…To improve the accuracy of soil heavy metal content prediction, this study proposes a dynamic neural network optimization model (DNNOM). …”
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    Article
  2. 1082

    An Experimental Comparison of Self-Adaptive Differential Evolution Algorithms to Induce Oblique Decision Trees by Rafael Rivera-López, Efrén Mezura-Montes, Juana Canul-Reich, Marco-Antonio Cruz-Chávez

    Published 2024-11-01
    “…This study addresses the challenge of generating accurate and compact oblique decision trees using self-adaptive differential evolution algorithms. Although traditional decision tree induction methods create explainable models, they often fail to achieve optimal classification accuracy. …”
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    Article
  3. 1083

    An Improved Shuffled Frog Leaping Algorithm for Electrical Resistivity Tomography Inversion by Fuyu Jiang, Likun Gao, Run Han, Minghui Dai, Haijun Chen, Jiong Ni, Yao Lei, Xiaoyu Xu, Sheng Zhang

    Published 2025-07-01
    “…Second, an adaptive movement operator is constructed to dynamically regulate the step size of the search, enhancing the guiding effect of the optimal solution. In synthetic data tests of three typical electrical models, including a high-resistivity anomaly with 5% random noise, a normal fault, and a reverse fault, the improved algorithm shows an approximately 2.3 times higher accuracy in boundary identification of the anomaly body compared to the least squares (LS) method and standard SFLA. …”
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    Article
  4. 1084

    Adaptive neighbourhood for locally and globally tuned biogeography based optimization algorithm by Parimal Kumar Giri, Sagar S. De, Satchidananda Dehuri

    Published 2021-05-01
    “…We name it as “Adaptive Neighbourhood for Locally and Globally Tuned Biogeography Based Optimization algorithm (ANLGBBO)”. This maintains the balance between intensification and diversification i.e., improve solution by exploiting the accumulated search space and exploring the large space by identifying regions with high quality solutions. …”
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    Article
  5. 1085

    EG-DPoS: Optimized DPoS Consensus Algorithm Based on Evolutionary Game by LIU Yong, DENG Xiaohong, LIU Lihui, SHI Yiran, ZHANG Li

    Published 2025-05-01
    “…Compared with other typical DPoS improved algorithms, EG-DPoS also has obvious performance advantages.…”
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  6. 1086

    Establishment and Solution Test of Wear Prediction Model Based on Particle Swarm Optimization Least Squares Support Vector Machine by Xiao Huang, Yongguo Wang, Yuhui Mao

    Published 2025-03-01
    “…The model parameters are optimized by the two-dimensional coordinates (c and g) of the particle swarm algorithm to adapt to the given training sample set. …”
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    Article
  7. 1087

    FATIGUE CRACK GROWTH PREDICTION BASED ON IPSO-PF ALGORITHM by JIN Ting, WANG Xiaolei, LIU Yu, YUAN Jianming

    Published 2025-04-01
    “…The traditional Paris formula ignores the influence of various uncertain factors in the crack growth process, which leads to a big difference between the predicted crack growth process and the real crack growth process. In order to improve the prediction accuracy of fatigue crack growth, a fatigue crack growth prediction method based on the improved particle swarm optimization particle filtering (IPSO-PF) algorithm was proposed. …”
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    Article
  8. 1088
  9. 1089

    Automatic Optimization of Guidance Guardrail Layout Based on Multi-Objective Evolutionary Algorithm by Wei-Li Liu, Yixin Chen, Xiang Li, Jinghui Zhong, Rongjun Chen, Hu Jin

    Published 2024-12-01
    “…To address this limitation, this paper introduces a novel automated optimization framework for guidance guardrails based on a multi-objective evolutionary algorithm. …”
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    Article
  10. 1090

    Optimizing Renewable Energy Integration Using IoT and Machine Learning Algorithms by Orken Mamyrbayev, Ainur Akhmediyarova, Dina Oralbekova, Janna Alimkulova, Zhibek Alibiyeva

    Published 2025-03-01
    “…The study also implemented a reinforcement learning-based grid optimization system. Results showed significant improvements in forecasting accuracy, with the LSTM model achieving a 59.1% reduction in Mean Absolute Percentage Error compared to the persistence model. …”
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  11. 1091

    Optimization the stochastic optimal reactive power dispatch with renewable energy resources using a modified dandelion algorithm. by Naima Agouzoul, Aziz Oukennou, Faissal Elmariami, Mohamed Ebeed, Jamal Boukherouaa, Rabiaa Gadal, Mokhtar Aly, Emad A Mohamed

    Published 2025-01-01
    “…Improvement performance of transmission systems is crucial task that can be boosted via optimal reactive power dispatch (ORPD). …”
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    Article
  12. 1092

    GENETIC ALGORITHM IN OPTIMIZATION DESIGN OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR by Phuong Le Ngo

    Published 2017-05-01
    “…For designing PMSM, evolution algorithms are more attractive approach. Genetic algorithm is one of the most common. …”
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    Article
  13. 1093

    Resource optimization algorithm of combination of NFV and SDN for application of multiple services by Xiaorong ZHU, Qian ZHANG

    Published 2018-11-01
    “…Various services of internet of things (IoT) require flexible network deployment to guarantee different quality of service (QoS).Aiming at the problem of IoT service function chain deployment,network function virtualization (NFV) and software defined networking (SDN) were combined to optimize resources.Considering forwarding cost and traffic load balance,a joint optimization model of virtual network function placement and service function chain routing was given and was proved to be NP-Hard.In order to solve this model,two heuristic algorithms were proposed.One was the service chain deployment algorithm of first routing then placing (FRTP) and the other was the placing followed by routing (PFBR) based on node priority.Simulation results demonstrate that FRTP and PFBR algorithm can significantly balance network traffic load while alleviating congestion and improving the acceptance ratio of the chain requests compared with other algorithms.…”
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  14. 1094

    MULTI-OBJECTIVE OPTIMIZATION OF HYDRODYNAMIC BEARING BASED ON ADAPTIVE GOLDEN JACKAL ALGORITHM (MT) by XU Kai, ZHANG HuiFang

    Published 2023-01-01
    “…In order to improve the load-carrying capacity of the hydrodynamic bearing, and reduce the calorific value and friction coefficient at the same time, a multi-objective optimization model of the hydrodynamic bearing was established. …”
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  15. 1095

    Earthworm optimization algorithm for extracting parameters for solar cells and photovoltaic modules by Fatima Wardi, Mohamed Louzazni, Mohamed Hanine

    Published 2025-08-01
    “…In this paper, we deal with the use of the earthworm optimization algorithm (EOA) in foraging to estimate and extract the intrinsic electrical parameters of single-, double-, and triple-diode solar cells and photovoltaic modules across different technologies. …”
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  16. 1096

    Optimization of the Offshore Wind Turbines Layout Using Cuckoo Search Algorithm by Ibrahim Abdulwahab, Solomon Andrew Onazi, Gideon Rimamfate, Akande Abdulwasiu, Abubakar Umar, N.A Iliyasu

    Published 2024-06-01
    “…After-which a cuckoo search algorithm technique is employed in the wind farm model to optimize the optimization problem (minimizing the wake effect while improving power output and cost). …”
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  17. 1097

    A Cooperative Trajectory Optimization Algorithm for Connected Vehicles in Merging Zones by Hao Li, Yun Pu, Lingjuan Chen, Yu Wang

    Published 2022-01-01
    “…Traffic flow optimization and trajectory guidance in merging zones have significant implications for improving capacity and reducing time consumption. …”
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    Article
  18. 1098
  19. 1099

    A Hybrid Optimization Algorithm for the Synthesis of Sparse Array Pattern Diagrams by Youzhi Liu, Linshu Huang, Xu Xie, Huijuan Ye

    Published 2025-06-01
    “…The algorithm enhances global search capability through the introduction of a quantum potential well model, while incorporating adaptive mutation operations to prevent premature convergence, thereby improving optimization accuracy during later iterations. …”
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  20. 1100

    Hybrid strategy enhanced crayfish optimization algorithm for breast cancer prediction by Yu-Jiong Li

    Published 2025-08-01
    “…When combined with Extreme Learning Machine (ELM) and applied to the Wisconsin breast cancer dataset, the MSCOA-ELM model achieved 100% accuracy and F1 score, a 28.9% improvement over the baseline ELM, demonstrating the algorithm’s efficiency and generalization ability in solving practical optimization problems.…”
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