Showing 801 - 820 results of 5,845 for search '(((improved OR improve) most) OR ((improved OR improve) model)) optimization algorithm', query time: 0.42s Refine Results
  1. 801

    A Framework for Low-Carbon Container Multimodal Transport Route Optimization Under Hybrid Uncertainty: Model and Case Study by Fenling Feng, Fanjian Zheng, Ze Zhang, Lei Wang

    Published 2025-06-01
    “…Subsequently, a multi-strategy improved whale optimization algorithm (WOA) is developed to solve the formulated model. …”
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    Article
  2. 802

    An Experimental Study of Strategies to Control Diversity in Grouping Mutation Operators: An Improvement to the Adaptive Mutation Operator for the GGA-CGT for the Bin Packing Proble... by Stephanie Amador-Larrea, Marcela Quiroz-Castellanos, Octavio Ramos-Figueroa

    Published 2025-03-01
    “…Grouping Genetic Algorithms (GGAs) are among the most outstanding methods for solving NP-hard combinatorial optimization problems by efficiently grouping sets of items. …”
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  3. 803

    Predictive Performance of Anti-Lock Braking System with PID Controller Optimized by Gravitational Search Algorithm for a Quarter Car Model: Simulation Modeling and Control by Mohd Sabirin Rahmat, Fauzi Ahmad, Vimal Rau Aparow, Rizauddin Ramli, Sallehuddin Mohamed Haris, Mohd Anas Mohd Sabri, Mohd Anas Mohd Sabri, Meor Iqram Meor Ahmad, Mohd Muhyidin Mustafa

    Published 2025-03-01
    “…This research addresses these issues by developing an ABS model using a quarter-car framework incorporated with a PID controller optimized by using Gravitational Search Algorithm (GSA). …”
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  4. 804

    A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI. by Balraj Preet Kaur, Harpreet Singh, Rahul Hans, Sanjeev Kumar Sharma, Chetna Sharma, Md Mehedi Hassan

    Published 2024-01-01
    “…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. …”
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    Article
  5. 805

    Predictive Modeling of Yoga's Impact on Venous Clinical Severity Scoring Using Gaussian Process Classification and Advanced Optimization Algorithms by Yazdan Ashgevari, Faranak Kazemi

    Published 2025-06-01
    “…The study employs the Adaptive Opposition Slime Mould Algorithm (AOSM) and Mountain Gazelle Optimizer (MGO) to enhance the predictive capabilities of a Gaussian Process Classification (GPC) model. …”
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  6. 806

    Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization by Haiying Yang, Feiyang Ren, Jingbo Yin, Siqi Wang, Rafi Ullah Khan

    Published 2025-04-01
    “…This study addresses the tramp ship routing and scheduling problem by incorporating the carbon intensity indicator (CII) into the optimization framework. A bi-objective optimization model is developed, with two objective functions aimed at maximizing fleet profit and improving CII ratings. …”
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  7. 807
  8. 808

    The Application Based on Support Vector Machine Optimized by Particle Swarm Optimization and Genetic Algorithm by MAN Chun-tao, LIU Bo, CAO Yong-cheng

    Published 2019-06-01
    “…In order to improve the precision of the parameter optimization, the research integrates the Particle Swarm Optimization Algorithm with Support Vector Machine, and matches the experimental data, and then establishes a steadystate model of complex process system, which is based on Particle Swarm Optimization Algorithm and Support Vector Machine On the basis of this model, an improved Particle Swarm Optimization Algorithm introduced to Genetic Algorithm is proposed, in order to overcome the defects of Particle Swarm. …”
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  9. 809

    Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

    Published 2021-01-01
    “…To improve the accuracy of dissolved oxygen prediction,this paper researches and proposes a prediction method that combines seagull optimization algorithm (SOA) with support vector machine (SVM) and BP neural network,prepares four prediction schemes based on the monthly dissolved oxygen monitoring data of the Jinghong Power Station in Xishuangbanna,a national important water supply source in Yunnan Province,from January 2009 to September 2020,optimizes the key parameters of SVM and weight threshold of BP neural network by SOA to construct SOA-SVM and SOA-BP models,predicts the dissolved oxygen of Jinghong Power Station based on the models,and compares the prediction results with those of SVM and BP models.The results show that:The absolute values of the average relative errors of the SOA-SVM and SOA-BP models for the 4 schemes of dissolved oxygen prediction are between 4.07%~4.98% and 3.85%~4.83%,and that of the average absolute errors are 0.309~0.374 mg/L and 0.294~0.371 mg/L,respectively.With better prediction accuracy than SVM and BP models,they have good prediction accuracy and generalization ability.SOA can effectively optimize the key parameters of SVM and weight threshold of BP neural network.SOA-SVM and SOA-BP models are feasible for dissolved oxygen prediction,which can provide references for related prediction research.…”
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  10. 810

    Ultrahigh-Dimensional Model and Optimization Algorithm for Resource Allocation in Large-Scale Intelligent D2D Communication System by Minxin Liang, Jiandong Liu, Jinrui Tang, Ruoli Tang

    Published 2021-01-01
    “…Simulation results show that the developed VGCC-PSO algorithm performs the best in optimizing the UHDO model with up to 6000 dimensionalities. …”
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  11. 811

    Low Capillary Elastic Flow Model Optimization Using the Lattice Boltzmann Method and Non-Dominated Sorting Genetic Algorithm by Yaqi Hou, Wei Zhang, Jiahua Hu, Feiyu Gao, Xuexue Zong

    Published 2025-02-01
    “…This paper establishes an LBM multiphase flow model enhanced by machine learning. The hyperparameters of the machine learning model are optimized using the particle swarm algorithm. …”
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  12. 812

    A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks by B Nagarajan, Santhosh Kumar SVN, M Selvi, K Thangaramya

    Published 2024-11-01
    “…In the course of this effort, an effective strategy for sensor node failure detection algorithm using the Poisson Hidden Markov Model (PHMM) and the Fuzzy-based Chicken Swarm Optimization (F-CSO) is proposed for efficient detection of sensor node faults in the WSN. …”
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  13. 813

    Enhanced securities investment strategy using ISSA–SVM: a hybrid model combining adaptive moving average, support vector machine, and multi-strategy sparrow search algorithm for im... by Wei Ni, Qingqing Chen, Xiaochen Guo, Yanan Liu

    Published 2025-05-01
    “…This study proposes a novel hybrid strategy, ISSA–SVM, that combines Adaptive Moving Average (AMA), Support Vector Machine (SVM), and an Improved Sparrow Search Algorithm (ISSA) to enhance CTA model performance in securities investment. …”
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  14. 814

    An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang, Junjie Lei

    Published 2025-04-01
    “…Next, the collected received signal strength indication (RSSI) data are processed using Kalman filtering and Min-Max normalization, suppressing signal fluctuations and accelerating the gradient descent convergence of the distance measurement model. Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. …”
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  15. 815

    Improvement in positional accuracy of neural-network predicted hydration sites of proteins by incorporating atomic details of water-protein interactions and site-searching algorith... by Kochi Sato, Masayoshi Nakasako

    Published 2025-03-01
    “…Here, we report the improvements in prediction accuracy by the reorganized CNN together with the details in the architecture, training data, and peak search algorithm.…”
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  16. 816

    Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

    Published 2025-01-01
    “…This work introduces the Deep Learning Model with Evolutionary Computing Approach (DLECA), a novel method for compressing and optimizing hierarchical deep learning models (HDLM). …”
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  17. 817

    Multiphase Transport Network Optimization: Mathematical Framework Integrating Resilience Quantification and Dynamic Algorithm Coupling by Linghao Ren, Xinyue Li, Renjie Song, Yuning Wang, Meiyun Gui, Bo Tang

    Published 2025-06-01
    “…Next, we create a dynamic adaptive public transit optimization model using an entropy weight-TOPSIS decision framework coupled with an improved simulated annealing algorithm (ISA-TS), achieving coordinated suburban–urban network optimization while maintaining 92.3% solution stability under simulated node failure conditions. …”
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  18. 818

    The PSO-IFAH optimization algorithm for transient electromagnetic inversion. by Zhengyu Xu, Guofeng Zhao, Xian Liao, Nengyi Fu

    Published 2025-01-01
    “…And finally, an improved PSO-IFA hybrid optimization algorithm (PSO-IFAH) was proposed in the paper. …”
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  19. 819

    The application of ICPA optimization algorithm in multi-objective optimization structural design of prefabricated buildings by Chao Li

    Published 2024-12-01
    “…Finally, a novel structural design optimization model was proposed. These experiments confirmed that the improved algorithm had the least 160 iterations and 17 optimal solutions, which was an increase of 15 compared to traditional aphid algorithms. …”
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  20. 820

    Research of the Parameter Comprehensive Optimization of Excavator Working Device based on the Hybrid Optimization Algorithm by Zhang Xian, Liu Baixi, Qu Tao

    Published 2016-01-01
    “…The efficiency and accuracy of the solution is improved for the advantages of two algorithms are effectively combined and local optimal solution is avoided. …”
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