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  1. 4701

    Quality Prediction Model Based on Novel Elman Neural Network Ensemble by Lan Xu, Yuting Zhang

    Published 2019-01-01
    “…In this paper, we propose a novel prediction algorithm based on an improved Elman neural network (NN) ensemble for quality prediction, thus achieving the quality control of designed products at the product design stage. …”
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    Article
  2. 4702

    Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes by Kelly Joel Gurubel Tun, Elizabeth León-Becerril, Octavio García-Depraect

    Published 2025-03-01
    “…This strategy has demonstrated to be a viable algorithm for real-time control applications. First, experimental data from continuous dark fermentation are modeled using support vector machine (SVM) algorithm for response prediction and then, optimization algorithms are employed to identify the key parameters that enhance H2 production. …”
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  3. 4703
  4. 4704

    Deep reinforcement learning for multi-objective location optimization of onshore wind power stations: a case study of Guangdong Province, China by Yanna Gao, Hong Dong, Liujun Hu, Fanhong Zeng, Yuqun Gao, Zhuonan Huang, Shaohua Wang, Shaohua Wang

    Published 2025-07-01
    “…To solve this model at large scale, a deep reinforcement learning (DRL) algorithm is designed and implemented. …”
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    Article
  5. 4705

    Towards precision agriculture: metaheuristic model compression for enhanced pest recognition by Sana Parez, Norah Saleh Alghamdi, Tahir Mahmood, Waseem Ullah, Muhammad Attique Khan, Taha Houda, Naqqash Dilshad

    Published 2025-07-01
    “…The core of this approach integrates InceptionV3 as a backbone feature extractor to capture rich and discriminative features, enhanced further using a channel attention (CA) mechanism for feature refinement. To reduce model complexity and improve deployment feasibility, a metaheuristic optimization algorithm was incorporated that significantly reduces computational overhead without compromising performance. …”
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    Article
  6. 4706

    LightGBM hybrid model based DEM correction for forested areas. by Qinghua Li, Dong Wang, Fengying Liu, Jiachen Yu, Zheng Jia

    Published 2024-01-01
    “…To overcome these shortcomings, this paper cites an improved SSA search algorithm that incorporates the ingestion strategy of the FA algorithm to increase the diversity of solutions and global search capability, the Firefly Algorithm-based Sparrow Search Optimization Algorithm (FA-SSA algorithm) is introduced. …”
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  7. 4707

    Human fall direction recognition in the indoor and outdoor environment using multi self-attention RBnet deep architectures and tree seed optimization by Awais Khan, Jung-Yeon Kim, Chomyong Kim, Muhammad Attique Khan, Hyojin Shin, Jiyoung Woo, Yunyoung Nam

    Published 2025-08-01
    “…To optimize feature selection and improve classification performance while reducing computational costs, we employed the tree seed algorithm on the self-attention features of 7-RBNet and 9-RBNet self-attention models. …”
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    Article
  8. 4708

    Forecast-Aided Converter-Based Control for Optimal Microgrid Operation in Industrial Energy Management System (EMS): A Case Study in Vietnam by Yeong-Nam Jeon, Jae-ha Ko

    Published 2025-06-01
    “…The forecasted load data is then used to optimize charge/discharge schedules for energy storage systems (ESS) using a Particle Swarm Optimization (PSO) algorithm. …”
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    Article
  9. 4709

    Evaluation method of e-government audit information based on big data analysis by Jingui He, Hansi Ya

    Published 2025-12-01
    “…Furthermore, a parallel PSO-RF algorithm combining Particle Swarm Optimization (PSO) and Random Forest (RF) is designed to enhance classification performance and computational efficiency. …”
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    Article
  10. 4710

    Management of the business system of the enterprise by O. Grosheleva, M. Ivanova, O. Usatenko

    Published 2021-12-01
    “…An optimization model has been built, which allows to determine the share of expenditures for certain communication activities in the overall budget structure. …”
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    Article
  11. 4711
  12. 4712

    A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

    Published 2025-06-01
    “…Traditional energy management methods, based on static models or heuristic algorithms, often fail to handle real-time grid dynamics, leading to suboptimal energy distribution, high operational costs, and significant energy wastage. …”
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    Article
  13. 4713

    Combining miRNA concentrations and optimized machine-learning techniques: An effort for the tomato storage quality assessment in the agriculture 4.0 framework by Seyed Mohammad Samadi, Keyvan Asefpour Vakilian, Seyed Mohamad Javidan

    Published 2025-03-01
    “…However, the RF, with hyperparameters optimized by the genetic algorithm, was able to improve the R2 values of the prediction of storage temperature and period to 0.96 and 0.89. …”
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  14. 4714

    Enhancing resilience of distribution system under extreme weather: Two-stage energy storage system configuration strategy based on robust optimization by Ye He, Hongyun Fu, Andrew Y. Wu, Hongbin Wu, Ming Ding

    Published 2025-06-01
    “…Finally, a two-stage robust optimization model for the ESS is established to improve DN resilience with the objective of minimizing the comprehensive economic cost of the ESS and the annual comprehensive weighted load loss, which is solved using the column-and-constraint generation algorithm (C&CG). …”
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  15. 4715

    A Deep Learning Model for ERP Enterprise Financial Management System by Hui Zhang

    Published 2022-01-01
    “…The method proposes an improved temporal convolutional network-long and short-term memory network (TCN_LSTM) structure and introduces an optimization algorithm to optimize the parameters of the deep learning model. …”
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  16. 4716

    Study on the Method of Vineyard Information Extraction Based on Spectral and Texture Features of GF-6 Satellite Imagery by Xuemei Han, Huichun Ye, Yue Zhang, Chaojia Nie, Fu Wen

    Published 2024-10-01
    “…Moreover, the RF model, which amalgamates spectral and texture features, exhibits a notable 13.59% increase in accuracy versus the spectral-only model and a 14.92% improvement over the texture-only model. …”
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  17. 4717

    Intelligent End-Edge Computation Offloading Based on Lyapunov-Guided Deep Reinforcement Learning by Xue Feng, Chi Xu, Xi Jin, Changqing Xia, Jing Jiang

    Published 2024-11-01
    “…To address the end-edge computation offloading challenge in the multi-terminal and multi-server environment, this paper proposes an intelligent computation offloading algorithm based on Lyapunov optimization and deep reinforcement learning. …”
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  18. 4718

    YOLOv9-GSSA model for efficient soybean seedlings and weeds detection by Baihe Liang, Liangchen Hu, Guangxing Liu, Peng Hu, Shaosheng Xu, Biao Jie

    Published 2025-12-01
    “…To tackle these issues, we propose a real-time detection algorithm called YOLOv9-GSSA. The improved Mosaic-Dense algorithm increases object density at the model's input layer, enhancing its ability to capture detailed features. …”
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  19. 4719

    RETRACTED ARTICLE: Effects of Curcumin-coated Nanomicelles on Cerebral Ischemia Injury in Rats by Regulating lncRNA GAS5 and NF-κB Signaling Pathways by Zhiyue Zhang, Lei Zhang, Xuan Cai, Xing Li, Cheng Wei, Gangli Yan, Fengguang Li

    Published 2023-12-01
    “…These results indicate that the computer intelligent algorithm can be used to evaluate the behaviour of rats, EEG can reflect the changes of cerebral cortical function, and Cur-PLG-mPEG-PCL can improve neurological function and degree of brain injury.…”
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  20. 4720

    Handling method for GPS outages based on PSO-LSTM and fading adaptive Kalman filtering by Xiaoming Li, Xianchen Wang, Can Pei

    Published 2025-04-01
    “…The PSO algorithm is utilized to optimize two hyperparameters, neuron count and learning rate, which are essential to improve the training efficiency and prediction accuracy in the LSTM model. …”
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    Article