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  1. 921

    Optimization method of building energy efficiency design based on decomposition multi objective and agent assisted model by Bai Chaoqin, Yang Zhuoyue

    Published 2024-01-01
    “…For the same building type, the average volume measurements of the multi-objective particle swarm optimization algorithm assisted by the decomposed surrogate model are 21153 and 40230, respectively. …”
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    Article
  2. 922

    Identifying Capsule Defect Based on an Improved Convolutional Neural Network by Junlin Zhou, Jiao He, Guoli Li, Yongbin Liu

    Published 2020-01-01
    “…The Adam optimizer is introduced to accelerate model training and improve model convergence. …”
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    Article
  3. 923

    Low-carbon economic optimization for flexible DC distribution networks based on the hiking optimization algorithm by Ke Wu, Yuefa Guo, Ke Wang, Zhenliang Chen

    Published 2025-03-01
    “…The proposed model is solved using a novel Hiking Optimization Algorithm (HOA), and comparative analysis across different scenarios is conducted to investigate the impact of the carbon trading strategy on low-carbon operation, alongside an evaluation of the system’s economic and environmental performance under reasonable scheduling of both the carbon trading strategy and flexible loads. …”
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  4. 924

    Influence of soil parameters on dynamic compaction: numerical analysis and predictive modeling using GA-optimized BP neural networks by Yu Zhang, Xueshui Chen, Huakang Ge, Zhigang Guo, Xu Li

    Published 2025-07-01
    “…Orthogonal experimental design and single factor analysis were used to quantify the influence of each parameter on the compaction volume. In order to improve the prediction accuracy, this paper introduces genetic algorithm (GA) to optimize the BP neural network model, constructs a multi-factor dynamic compaction prediction model, and compares it with the traditional BP model. …”
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    Article
  5. 925

    Residual Life Prediction of Proton Exchange Membrane Fuel Cell Based on Improved ESN by Tiejiang YUAN, Rongsheng LI, Jiandong KANG, Huaguang YAN

    Published 2025-05-01
    “…Aiming at the problem that the current residual effective life prediction (RUL) technique for proton exchange membrane fuel cells (PEMFCs) has poor prediction effect in the medium and long term, a residual life prediction method based on the Improved Gray Wolf Optimization algorithm (IGWO) and Echo State Network (ESN) is proposed, in which the voltage of the electric stack is firstly selected as a health indicator, and the PEMFC dataset is processed by using convolutional smoothing filtering method to carry out data Smoothing and normalization are used to effectively reduce the interference of outliers on the subsequent model training. …”
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    Article
  6. 926

    Hybrid Darknet53-SVM model with random grid search optimization for enhanced colorectal cancer histological image classification by Pragati Patharia, Prabira Kumar Sethy, K. Lakshmipathi Raju, Anita Khanna, Ashoka Kumar Ratha, Santi Kumari Behera, Aziz Nanthaamornphong

    Published 2025-07-01
    “…To enhance the classification performance, Darknet53 was hybridized with a SVM by replacing the dense layer, and hyperparameters were optimized using a Random Grid Search algorithm. The optimized hybrid model exhibited a remarkable improvement, with an Acc. of 99.7%, Sen. of 99.7%, Spec. of 99.91%, Prec. of 99.98%, and F1-score of 99.98%, alongside significant improvements in other metrics. …”
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    Article
  7. 927

    Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features by Qu FZ, Ding J, An XF, Peng R, He N, Liu S, Jiang X

    Published 2024-12-01
    “…Finally, a correlation analysis was conducted to examine the relationships between these features and other significant clinical features.Results: The logistic regression (LR) model was determined to be the optimal machine learning algorithm in this study, achieving an accuracy of 0.64, a precision of 0.45, a recall of 0.72, an F1 score of 0.51, and an AUC of 0.81 in the training set and 0.91 in the testing set. …”
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    Article
  8. 928

    Recurrent academic path recommendation model for engineering students using MBTI indicators and optimization enabled recurrent neural network by Anupama V, Sudheep Elayidom M

    Published 2025-07-01
    “…To address this issue, an intelligent recommendation model is proposed that assists students in discovering the most suitable academic path based on their personal background and personality traits. …”
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    Article
  9. 929

    A fuzzy-optimized hybrid ensemble model for yield prediction in maize-soybean intercropping system by Amna Ikram, Sunnia Ikram, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Adil Hussain, Amal H. Alharbi, Marwa M. Eid, Marwa M. Eid

    Published 2025-05-01
    “…This study proposes a Fuzzy-Optimized Hybrid Ensemble Model (FOHEM), integrating stacked ensemble machine learning algorithms with a fuzzy inference system (FIS) to improve yield prediction. …”
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    Article
  10. 930

    Three Strategies Enhance the Bionic Coati Optimization Algorithm for Global Optimization and Feature Selection Problems by Qingzheng Cao, Shuqi Yuan, Yi Fang

    Published 2025-06-01
    “…To tackle this, this study proposes the bionic ABCCOA algorithm, an enhanced version of the bionic Coati Optimization Algorithm (COA), to improve redundant feature elimination in datasets. …”
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    Article
  11. 931

    Improving Genetic Algorithm with Fine-Tuned Crossover and Scaled Architecture by Ajay Shrestha, Ausif Mahmood

    Published 2016-01-01
    “…Our implementation tests show that leveraging these new concepts of mtDNA and Continental Model results in relative improvement of the optimization quality of GA.…”
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  12. 932

    Numerical Assessment of Automotive Mufflers Using FEM, Neural Networks, and a Genetic Algorithm by Ying-Chun CHANG, Min-Chie CHIU, Meng-Ru WU

    Published 2018-07-01
    “…With this, the muffler’s optimization can proceed by linking the objective function to an optimizer, a Genetic Algorithm (GA). …”
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    Article
  13. 933

    An adaptive hierarchical hybrid kernel ELM optimized by aquila optimizer algorithm for bearing fault diagnosis by Hao Yan, Liangliang Shang, Wan Chen, Mengyao Jiang, Tianqi lu, Fei Li

    Published 2025-04-01
    “…The AO algorithm is further enhanced by incorporating chaos mapping, implementing a refined balanced search strategy, and fine-tuning parameter $$G_2$$ , which collectively improve its ability to escape local optima and conduct global searches, thus strengthening the robustness of the model during parameter optimization. …”
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    Article
  14. 934
  15. 935

    Optimizing Ontology Alignment through Improved NSGA-II by Yikun Huang, Xingsi Xue, Chao Jiang

    Published 2020-01-01
    “…Over the past decades, a large number of complex optimization problems have been widely addressed through multiobjective evolutionary algorithms (MOEAs), and the knee solutions of the Pareto front (PF) are most likely to be fitting for the decision maker (DM) without any user preferences. …”
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  16. 936
  17. 937

    Long short‐term memory‐based forecasting of uncertain parameters in an islanded hybrid microgrid and its energy management using improved grey wolf optimization algorithm by Raji Krishna, Hemamalini S

    Published 2024-12-01
    “…In the second phase, the forecasted RES power and LD are used for optimal distributed generator (DG) scheduling using the improved grey wolf optimization (IGWO) algorithm. …”
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  18. 938

    A Mobile Agent Routing Algorithm in Dual-Channel Wireless Sensor Network by Kui Liu, Sanyang Liu, Hailin Feng

    Published 2012-05-01
    “…A mobile agent routing algorithm (MARA) is presented in this paper, and then based on the dual-channel communication model, the two-layer network combination optimization strategy is also proposed. …”
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  19. 939

    Optimization of Wheel Reprofiling Based on the Improved NSGA-II by Xinghu Wang, Jiabin Yuan, Sha Hua, Bojia Duan

    Published 2020-01-01
    “…Our study reveals the relationship between the diameter, flange thickness, and their individual attrition rates and proposes a wear model, multiobjective model, and improved NSGA-II. …”
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  20. 940