Showing 6,241 - 6,260 results of 7,771 for search '(( improve (most OR post) optimization algorithm ) OR ( improved model optimization algorithm ))', query time: 0.60s Refine Results
  1. 6241

    Soft Measurement of Wastewater Treatment System Based on PSOGA-WNN by LIU Yuhui, MAI Wenjie, LI Xiaoyong, ZHAO Yinzhong, HE Xinzhong, HUANG Mingzhi

    Published 2023-01-01
    “…To accurately predict the SS<sub>eff</sub> (effluent SS) content and COD<sub>eff</sub> (effluent COD) concentration in water quality parameters and further improve the water quality early warning mechanism,this paper proposes the PSOGA-WNN soft measurement model of paper wastewater effluent quality to obtain the main water quality technical parameters,COD<sub>inf</sub> (influent COD),Q (influent flow),pH (influent pH),SS<sub>inf</sub> (influent SS),T (influent temperature),DO (influent dissolved oxygen),COD<sub>eff</sub>,and SS<sub>eff,</sub> for predicting the quality of wastewater from the wastewater treatment plant.Among them,the prediction results of PSOGA-WNN are compared with the neural networks of PSO-WNN,GA-WNN,and PSOGA-BP.The results show that the PSOGA-WNN neural network has the highest prediction accuracy,which indicates that the PSOGA hybrid parameter optimization algorithm based on the genetic algorithm and particle swarm algorithm has obvious superiority in optimizing the prediction accuracy of the model.The WNN neural network has certain advantages over BP neural network in terms of fitting degree as well as error accuracy and is an effective means of simulation prediction.…”
    Get full text
    Article
  2. 6242

    Electric vehicle charging load prediction method based on multi-objective modal decomposition and NAHL neural network by GUO Xinzhe, WANG Yeqin, WANG Chao, WU Mingjiang, YANG Yan, ZHANG Chu

    Published 2025-03-01
    “…The improved NSGAII-LDSBX algorithm is used to optimize the parameters of VMD, decompose the signal into several subsequences, and reconstruct the subsequences through fuzzy entropy (FE). …”
    Get full text
    Article
  3. 6243

    Resource Scheduling with Uncertain Execution Time in Cloud Computing by LI Cheng-yan, CAO Ke-han, FENG Shi-xiang, SUN Wei

    Published 2019-02-01
    “…For the problem of cloud computing resource scheduling, based on the fuzzy programming theory, a fuzzy cloud resource scheduling model under timecost constraint was set up, the uncertain execution time of tasks is represented by the triangular fuzzy number, and the target is to minimize the average value and standard deviation of the evaluation function An improved chaotic ant colony algorithm was proposed to solve the model, the elitist strategy is introduced to optimize the pheromone updating, a chaotic mapping with infinite folding times is used for chaotic search, and the adaptive chaotic disturbance mechanism is designed to enhance the global searching ability The model and algorithm were tested on the Cloudsim platform, the reliability of the model was proved, and the experimental results showed that the proposed algorithm had better performance in convergence speed, solution ability and load balance…”
    Get full text
    Article
  4. 6244
  5. 6245

    Energy Harvesting for Throughput Enhancement of Cooperative Wireless Sensor Networks by Van-Dinh Nguyen, Chuyen T. Nguyen, Oh-Soon Shin

    Published 2016-07-01
    “…We then propose an iterative power allocation algorithm which converges to a locally optimal solution at a Karush-Kuhn-Tucker point. …”
    Get full text
    Article
  6. 6246

    Influence of artificial intelligence on higher education reform and talent cultivation in the digital intelligence era by Limin Qian, Weiran Cao, Lifeng Chen

    Published 2025-02-01
    “…Abstract In order to solve the problems of inefficient allocation of teaching resources and inaccurate recommendation of learning paths in higher education, this paper proposes a smart education optimization model (SEOM) by combining the improved random forest algorithm (RFA) based on adaptive enhancement mechanism and the Graph Neural Network (GNN) algorithm. …”
    Get full text
    Article
  7. 6247

    High-Precision Pose Measurement of Containers on the Transfer Platform of the Dual-Trolley Quayside Container Crane Based on Machine Vision by Jiaqi Wang, Mengjie He, Yujie Zhang, Zhiwei Zhang, Octavian Postolache, Chao Mi

    Published 2025-04-01
    “…An enhanced EPnP optimization algorithm incorporating lockhole coplanar constraints is proposed, establishing a 2D–3D coordinate transformation model that reduces pose-estimation errors to millimeter level (planar MAE-P = 0.024 m) and sub-angular level (MAE-<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>θ</mi></semantics></math></inline-formula> = 0.11°). …”
    Get full text
    Article
  8. 6248

    Cerebral gray matter volume identifies healthy older drivers with a critical decline in driving safety performance using actual vehicles on a closed-circuit course by Handityo Aulia Putra, Kaechang Park, Kaechang Park, Fumio Yamashita

    Published 2025-05-01
    “…Feature selection and classification were performed using the Random Forest machine learning algorithm, optimized to identify the most predictive GM regions.ResultsOut of 114 GM regions, eleven were selected as optimal predictors: left angular gyrus, frontal operculum, occipital fusiform gyrus, parietal operculum, postcentral gyrus, planum polare, superior temporal gyrus, and right hippocampus, orbital part of the inferior frontal gyrus, posterior cingulate gyrus, and posterior orbital gyrus. …”
    Get full text
    Article
  9. 6249

    Automatic Identification and Segmentation of Overlapping Fog Droplets Using XGBoost and Image Segmentation by Dongde Liao, Xiongfei Chen, Muhua Liu, Yihan Zhou, Peng Fang, Jinlong Lin, Zhaopeng Liu, Xiao Wang

    Published 2025-03-01
    “…In order to accurately measure the droplet size and grasp the droplet distribution pattern, this study proposes a method based on the optimized XGBoost classification model combined with improved concave-point matching to achieve multi-level overlapping-droplet segmentation. …”
    Get full text
    Article
  10. 6250

    Automatic license-plate recognition by A. V. Poltavskii, T. G. Yurushkina, M. V. Yurushkin

    Published 2020-03-01
    “…Quality of the system is provided through the optimization of various models with different modifications. …”
    Get full text
    Article
  11. 6251

    PolicySegNet: a policy-based reinforcement learning framework with pretrained embeddings and transformer decoder for joint brain tumors segmentation and classification in MRI by Vishv Patel, Vandana Patel, Aakash Shinde

    Published 2025-08-01
    “…PolicySegNet uniquely integrates a policy-based reinforcement learning algorithm—specifically proximal policy optimization (PPO)—to jointly optimize the decoder and classifier based on a reward signal that balances segmentation accuracy with classification performance. …”
    Get full text
    Article
  12. 6252

    Stochastic economic placement and sizing of electric vehicles charging station with renewable units and battery bank in smart distribution network by Mehdi Veisi

    Published 2025-07-01
    “…Benders decomposition algorithm is used to extract the optimal solution. …”
    Get full text
    Article
  13. 6253

    Detection of false data injection in electric energy metering platforms using gradient lifting decision trees and MLP neural networks by Yakui Zhu, Yangrui Zhang, Chao Zhang, Bingyu Zhang, Hongying Wang, Shaokang Feng

    Published 2024-12-01
    “…The discriminator used a multilayer perceptron (MLP) neural network, combined with difference analysis between the predicted and actual values, to determine false data injection. The improved Cauchy mutation grey Wolf optimization algorithm is used to optimize the model training to improve the detection accuracy. …”
    Get full text
    Article
  14. 6254

    Software and hardware co-design of lightweight authenticated ciphers ASCON for the internet of things by Jing WANG, Lesheng HE, Zhonghong LI, Luchi LI, Hang YANG

    Published 2022-12-01
    “…ASCON was the most promising algorithm to become an international standard in the 2021 NIST lightweight authenticated encryption call for proposals.The algorithm was designed to achieve the best performance in IoT resource-constrained environments, and there was no hardware IP core implementation based on this algorithm in the open literature.A software-hardware collaborative implementation method of ASCON was proposed, which improved the speed and reduced the memory footprint of ASCON in IoT security authentication applications through hardware means such as S-box optimization, prior calculation and advanced pipeline design.As a comparison, ASCON has been transplanted on the common IoT embedded processor platform.The results showed that the described method was more than 7.9 times faster, while the memory footprint was reduced by at least 90%.The schemes can be used for the design and implementation of IoT security application-specific integrated circuits or SoCs.…”
    Get full text
    Article
  15. 6255

    Underwater Target 3D Reconstruction via Integrated Laser Triangulation and Multispectral Photometric Stereo by Yang Yang, Yimei Liu, Eric Rigall, Yifan Yin, Shu Zhang, Junyu Dong

    Published 2025-04-01
    “…At the same time, we propose to optimize the laser place calibration and laser line separation processes, further improving the reconstruction performance of underwater laser triangulation and multispectral photometric stereo. …”
    Get full text
    Article
  16. 6256

    Vehicle Routing Problem for Collaborative Multidepot Petrol Replenishment under Emergency Conditions by Guangcan Xu, Qiguang Lyu

    Published 2021-01-01
    “…As a method to solve the model, genetic variation of multiobjective particle swarm optimization algorithm is considered. …”
    Get full text
    Article
  17. 6257

    Exploring a QoS Driven Scheduling Approach for Peer-to-Peer Live Streaming Systems with Network Coding by Laizhong Cui, Nan Lu, Fu Chen

    Published 2014-01-01
    “…The main contributions of this paper are: (i) We introduce a new network coding method to increase the content diversity and reduce the complexity of scheduling; (ii) we formulate the push scheduling as an optimization problem and transform it to a min-cost flow problem for solving it in polynomial time; (iii) we propose a push scheduling algorithm to reduce the coding overhead and do extensive experiments to validate the effectiveness of our approach. …”
    Get full text
    Article
  18. 6258

    Predicting hospital outpatient volume using XGBoost: a machine learning approach by Lingling Zhou, Qin Zhu, Qian Chen, Ping Wang, Hao Huang

    Published 2025-05-01
    “…Accurate prediction of outpatient demand can significantly enhance operational efficiency and optimize the allocation of medical resources. This study aims to develop a predictive model for daily hospital outpatient volume using the XGBoost algorithm. …”
    Get full text
    Article
  19. 6259

    Energy Storage Regulation Method of Base Stations in 5G Integrated Distribution Network Based on Energy Sharing and Trading Coordination by Yanru WANG, Xiyang YIN, Qinghai OU, Wenjie MA, Hui LIU, Zhigang DU

    Published 2023-06-01
    “…Then, with the optimization objectives of promoting energy sharing of 5G base stations, improving operation efficiency of base stations, and participating in peak shaving and valley filling, the optimization problem of energy storage regulation of base stations in a 5G integrated distribution network is constructed, and an energy storage regulation algorithm of 5G base stations based on energy sharing and trading coordination is proposed. …”
    Get full text
    Article
  20. 6260

    High-Dimensional Projected Clustering for Learner Competency Analysis in Medical Training Programs by Sandhya Harikumar, C. S. Jayamohan Pillai, V. Vani Chithra, Raghu Raman, Mr Kaimal, Kai-Yu Tang, Prema Nedungadi

    Published 2024-01-01
    “…Additionally, weak learners deficient in crucial healthcare areas are identified, and the model recommends the most qualified professionals for specific critical care cases.…”
    Get full text
    Article