Search alternatives:
improve model » improved model (Expand Search)
Showing 2,341 - 2,360 results of 7,145 for search 'improve model optimization algorithm', query time: 0.28s Refine Results
  1. 2341
  2. 2342

    New PSO-GWO-based model for enhancing power quality in electrical networks interconnected with photovoltaic sources by Mehdi Sanaei, Hamidreza Akbari, Zohreh Beheshtipour, Somayeh Mousavi

    Published 2024-12-01
    “…A hybrid Particle Swarm Optimization-Gray Wolf Optimization (PSO-GWO) algorithm is proposed to obtain optimal solutions. …”
    Get full text
    Article
  3. 2343
  4. 2344
  5. 2345

    Tomato leaf disease detection method based on improved YOLOv8n by Ming Chen, Chunping Wang, Chengwei Liu, Ying Yu, Yuan Yuan, Jiaxuan Ma, Kaisheng Zhang

    Published 2025-07-01
    “…To address this issue, this paper proposes an optimized YOLOv8n algorithm, incorporating a C2f-DynamicConv optimization module. …”
    Get full text
    Article
  6. 2346
  7. 2347
  8. 2348
  9. 2349

    Cutting-Edge Stochastic Approach: Efficient Monte Carlo Algorithms with Applications to Sensitivity Analysis by Ivan Dimov, Rayna Georgieva

    Published 2025-04-01
    “…This knowledge helps in identifying critical factors that significantly influence the model’s outcomes and can guide efforts to improve the accuracy and reliability of predictions. …”
    Get full text
    Article
  10. 2350

    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. …”
    Get full text
    Article
  11. 2351

    Photovoltaic solar energy prediction using the seasonal-trend decomposition layer and ASOA optimized LSTM neural network model by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

    Published 2025-02-01
    “…To address these challenges, this research introduces an innovative method that integrates Robust Seasonal-Trend Decomposition (RSTL) with an Adaptive Seagull Optimisation Algorithm (ASOA)-optimized Long Short-Term Memory (LSTM) neural network. …”
    Get full text
    Article
  12. 2352
  13. 2353

    Prediction of Water Quality in Agricultural Watersheds Based on VMD-GA-LSTM Model by Yuxuan Luo, Xianglan Meng, Yutong Zhai, Dongqing Zhang, Kaiping Ma

    Published 2025-06-01
    “…In order to solve the nonlinear and non-stationary characteristics of water quality data, this paper proposes a combined model based on variational modal decomposition and genetic algorithm optimization of long short-term memory networks (VMD-GA-LSTM) for agricultural watershed water quality prediction. …”
    Get full text
    Article
  14. 2354
  15. 2355

    Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge–Kutta with Aquila Optimizer by Rana Muhammad Adnan, Wang Mo, Ahmed A. Ewees, Salim Heddam, Ozgur Kisi, Mohammad Zounemat-Kermani

    Published 2024-11-01
    “…Abstract This study investigates the efficacy of hybrid artificial neural network (ANN) methods, incorporating metaheuristic algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), gray wolf optimizer (GWO), Aquila optimizer (AO), Runge–Kutta (RUN), and the novel ANN-based Runge–Kutta with Aquila optimizer (LSTM-RUNAO). …”
    Get full text
    Article
  16. 2356

    Research on Comprehensive Control Strategy of Loop Closing Currentin 10 kV Distribution Network by LIU Song, HUANG Chun

    Published 2019-01-01
    “…An improved harmony algorithm based on dynamic parameters and Pareto optimal is used to solve the model, then a recursive algorithm is used to solve the action sequence of control elements considering process security. …”
    Get full text
    Article
  17. 2357

    An Optimization Method for PCB Surface Defect Detection Model Based on Measurement of Defect Characteristics and Backbone Network Feature Information by Huixiang Liu, Xin Zhao, Qiong Liu, Wenbai Chen

    Published 2024-11-01
    “…This paper proposes the YOLOv8_DSM algorithm for PCB surface defect detection, optimized based on the three major characteristics of defect targets and feature map visualization. …”
    Get full text
    Article
  18. 2358

    Resource Optimization Method Based on Spatio-Temporal Modeling in a Complex Cluster Environment for Electric Vehicle Charging Scenarios by Hongwei Wang, Wei Liu, Chenghui Wang, Kao Guo, Zihao Wang

    Published 2025-05-01
    “…Meanwhile, a composite self-organizing mechanism integrating a trust model is put forward. The trust model assists agents in choosing partners, and the Q-learning algorithm of the intelligent cluster realizes the independent evaluation of rewards and the optimization of relationship adaptation. …”
    Get full text
    Article
  19. 2359

    A New Comprehensive Model to Simulate and Optimize Fluid Flow in Complex Well‐Formation System for In Situ Leaching Uranium by Zhaokun Li, Xuebin Su, Yangquan Jiao, Yu Zhang, Yang Qiu, Xiaodong Hu

    Published 2025-03-01
    “…Furthermore, a hybrid multiobjective optimization algorithm was used to complete the parameter optimization of well‐storage coupling for ISL of uranium. …”
    Get full text
    Article
  20. 2360

    Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

    Published 2024-09-01
    “…Furthermore, metaheuristic algorithms like Smell Agent Optimization and Giant Trevally Optimizer were employed to optimize model's hyperparameters, with the intention of enhancing accuracy and precision in performance estimations. …”
    Get full text
    Article