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Showing 321 - 340 results of 7,292 for search '(( improve post optimization algorithm ) OR ( improve model optimization algorithm ))*', query time: 0.34s Refine Results
  1. 321

    Landslide Forecasting Model Based on PCA and Improved CS-RBF by WANG Lianxia, LI Limin, FANG Zihao, REN Ruibin, FU Zhentao, CUI Chengtao

    Published 2024-08-01
    “…Various models including back propagation (BP), RBF, genetic algorithm-RBF (GA-RBF), CS-RBF, and others are compared with the improved CS-RBF model through experimental analysis. …”
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    Article
  2. 322

    Air Quality Prediction Using Neural Networks with Improved Particle Swarm Optimization by Juxiang Zhu, Zhaoliang Zhang, Wei Gu, Chen Zhang, Jinghua Xu, Peng Li

    Published 2025-07-01
    “…To address this challenge, we propose a novel prediction model that integrates an adaptive-weight particle swarm optimization (AWPSO) algorithm with a back propagation neural network (BPNN). …”
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    Article
  3. 323

    Research on APF-Dijkstra Path Planning Fusion Algorithm Based on Steering Model and Volume Constraints by Xizheng Wang, Gang Li, Zijian Bian

    Published 2025-07-01
    “…Therefore, an APF-Dijkstra path planning fusion algorithm based on steering model and volume constraints is proposed to improve it. …”
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    Article
  4. 324

    Distributed data trading algorithm based on multi-objective utility optimization by Xiaohong HUANG, Yong ZHANG, Desheng SHAN, Yekui QIAN, Lu HAN, Dandan LI, Qun CONG

    Published 2021-02-01
    “…The traditional centralized data trading models are not well applicable to the current intelligent era where everything is interconnected and real-time data is generated, and in order to maximize the use of collected data, it is essential to design an effective data trading framework.Therefore, a distributed data trading framework based on consortium blockchain was proposed, which realized P2P data trading without relying on a third party.Aiming at the problem that existing data trading models only consider the factors of the data itself and ignore the factors related to user tasks, a bi-level multi-objective optimization model was constructed based on multi-dimensional factors, such as data quality, data attributes, attribute relevance and consumer competition, to optimize the utilities of data provider (DP) and data consumer (DC).To solve the above model, an improved multi-objective genetic algorithm-collaborative NSGAII was proposed, calculated by the cooperation of DP, DC and data aggregator (AG).The simulation results show that the collaborative NSGAII achieves better performance in terms of the utilities of DP and DC, thus realizing more effective data trading.…”
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  9. 329

    PID Control of Multisources Complex Excitations Active Vibration Isolation System: An Improved Particle Swarm Optimization Algorithm by Song Chunsheng, Jiang Youliang, Zhang Jinguang

    Published 2016-01-01
    “…Furthermore, this paper also sets up the acceleration feedback-based PID control model for multisources complex excitations active vibration isolation system, proposes an improved particle swarm optimization (PSO) algorithm of dynamic inertia weight factors used to optimize parameters of the built PID control model, and conducts simulation analysis. …”
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  10. 330

    Energy Management of Electric–Hydrogen Coupled Integrated Energy System Based on Improved Proximal Policy Optimization Algorithm by Jingbo Zhao, Zhengping Gao, Zhe Chen

    Published 2025-07-01
    “…However, the inherent uncertainties of renewable energy sources present significant challenges to optimal energy management in the EHCS. To address these challenges, this paper proposes an energy management method for the EHCS based on an improved proximal policy optimization (IPPO) algorithm. …”
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    Article
  11. 331

    Improved Monthly Runoff Prediction of OSELM Based on Secondary Decomposition Technique and Optimization of Ten "Bird" Swarm Algorithms by DENG Zhiyu, CUI Dongwen

    Published 2025-01-01
    “…To improve the accuracy of monthly runoff time series prediction and enhance the performance of online sequential extreme learning machine (OSELM) prediction, ten "bird" swarm algorithms were compared and validated for optimization, including satin bowerbird optimizer (SBO)/Harris hawks optimization (HHO)/seagull optimization algorithm (SOA)/African vultures optimization algorithm (AVOA)/coot optimization algorithm (COOT)/pelican optimization algorithm (POA)/eagle perching optimization (EPO)/osprey optimization algorithm (OOA). …”
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  12. 332

    Knowledge reasoning and strategy optimization for ship operation and maintenance based on digital twin and improved KD tree algorithm by Liyao ZHANG, Ziqian GUO, Ruifang LI, Xun YE, Tao MA

    Published 2025-04-01
    “…Based on the database, a method for ship O&M knowledge reasoning and strategy generation using an improved KD tree algorithm is proposed. Neighboring cases are weighted using Gaussian distance weighting, and the whale optimization algorithm (WOA) is used to optimize the characteristic attributes of ship equipment to achieve accurate knowledge reasoning. …”
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    Article
  13. 333

    An Operation Optimization Strategy of the Combined Power Generation System with Wind Power & Pumped Storage Based on Improved Whale Algorithm by LI Kecheng, YANG Ning

    Published 2022-12-01
    “…In order to solve the model, based on the basic whale optimization algorithm, a multi-objective whale optimization algorithm is developed by adding external population and leader selection mechanism, and the control parameter in the algorithm is improved to obtain an improved multi-objective whale optimization algorithm. …”
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    Research on Collaborative Optimization Method of CCHP Regional Integrated Energy System Based on Improved Multivariate Universe Algorithm by Dahai Xu, Changle Yu, Wenwen Li, Su Zhang, Zhengda Li, Zhihui Qu, Pengtao Li, Xingfan Han

    Published 2025-01-01
    “…A case study conducted in a representative northern region yielded the following experimental results: When compared with both the traditional particle swarm algorithm and an improved version of it, the CCHP-type integrated energy system optimized using the enhanced multi-objective multiverse algorithm reduced operating costs by 7.98% and carbon dioxide emissions by 12%, relative to the original system. …”
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  17. 337

    A Novel Exploration Stage Approach to Improve Crayfish Optimization Algorithm: Solution to Real-World Engineering Design Problems by Harun Gezici

    Published 2025-06-01
    “…In order to compensate these shortcomings, this study proposes an Improved Crayfish Optimization Algorithm (ICOA) that designs the competition stage with three modifications: (1) adaptive step length mechanism inversely proportional to the number of iterations, which enables exploration in early iterations and exploitation in later stages, (2) vector mapping that increases stochastic behavior and improves efficiency in high-dimensional spaces, (3) removing the X<sub>shade</sub> parameter in order to abstain from early convergence. …”
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  18. 338

    An improvement in the design process of sustainable peak power rating transformer for solar utility by Emir Yükselen, Ebrahim Rahimpour

    Published 2025-09-01
    “…Such upgrades are essential for transitioning to a zero-emission electricity system and developing green energy projects.In this paper, a transformer has been studied using a combination of electrical design and 3D finite element method simulation to evaluate various design parameters. An optimization study has been conducted using an innovative multi-objective genetic algorithm utilizing a cost function that factors in size and material costs to identify the most efficient and cost-effective design solutions.The proposed design method was then validated through thermal model simulations and experimental tests based on the photovoltaic load cycle. …”
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    Control Strategy of a Rotating Power Flow Controller Based on an Improved Hybrid Particle Swarm Optimization Algorithm by Ziyang Zhang, Jiaoxin Jia, Waseem Aslam, Abubakar Siddique, Fahad R. Albogamy

    Published 2025-02-01
    “…Notably, this paper introduces intelligent optimization algorithms to this field for the first time, employing an improved hybrid particle swarm optimization (HPSO) algorithm to control the active power while keeping the reactive power constant and subsequently adjusting the reactive power while maintaining the active power steady, thereby achieving power regulation. …”
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