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6101
Research on Behavior Recognition and Online Monitoring System for Liaoning Cashmere Goats Based on Deep Learning
Published 2024-11-01“…Our improved model achieved the highest detection accuracy of 98.11% compared to other state-of-the-art (SOTA) target detection algorithms. …”
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6102
Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram
Published 2023-12-01“…In this study, four deep convolutional neural network models were designed with Occam's razor principle through hyperparameter settings on the algorithm structure aspect in the form of number of layers and optimization aspect in the form of optimizer type. …”
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6103
Experimental Study on Evaluation of Organization Collaboration in Prefabricated Building Construction
Published 2025-02-01“…The knowledge-driven part of this evaluation system used an evaluation model based on the analytic hierarchy process (AHP), while the data-driven part used a prediction model based on the BO-XGBoost algorithm to verify the validity of the AHP-based model. …”
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6104
Integrated Energy Management in Small-Scale Smart Grids Considering the Emergency Load Conditions: A Combined Battery Energy Storage, Solar PV, and Power-to-Hydrogen System
Published 2024-12-01“…Simulation results under various scenarios demonstrate the model’s superior performance. Compared to conventional evolutionary methods like particle swarm optimization, non-dominated sorting genetic algorithm III, and biogeography-based optimization, the proposed model exhibits remarkable improvements, outperforming them by 11.4%, 5.6%, and 11.6%, respectively. …”
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6105
Research on Unmanned Aerial Vehicle Path Planning for Carbon Emission Monitoring of Land-Side Heavy Vehicles in Ports
Published 2025-03-01“…The scheme analyzes the factors affecting the effectiveness of the scheme and establishes a hierarchy of these factors to optimize the monitoring path. Furthermore, a multi-objective path planning mathematical model is established in this article, introducing the optimal goals of economic and environmental costs to achieve the overall path planning objectives. …”
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6106
Hardware-in-loop implementation of an adaptive MPPT controlled PV-assisted EV charging system with vehicle-to-grid integration
Published 2025-08-01“…This paper developed and compared perturb and observe (P&O), Particle swarm optimization (PSO), and hybrid PSO + Adaptive neuro-fuzzy inference system (ANFIS) based algorithm for MPPT. …”
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6107
Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks
Published 2015-01-01“…Based on that, the proposed STD-VRP model can be converted into solving a normal time-dependent VRP (TD-VRP), and algorithms for such TD-VRPs can also be introduced to obtain the solution. …”
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6108
Predicting Ship Waiting Times Using Machine Learning for Enhanced Port Operations
Published 2025-01-01“…The XGBoost Regressor (XGBR) is optimized using genetic-algorithm-based hyperparameter tuning, reducing mean squared error (RMSE) from 20.9531 to 19.6387, mean absolute error (MAE) from 13.6821 to 12.6753, and improving coefficient of determination (R2) from 0.2791 to 0.2949. …”
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6109
Battery swapping scheduling for electric vehicles: a non-cooperative game approach
Published 2024-12-01“…To reduce the waiting time for battery swapping and improve the scheduling efficiency of EVs, a swapping process model inspired by the job-shop scheduling problem is proposed, and the cost function of each EV comprehensively considers the travel time, waiting time, and battery swapping price. …”
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6110
Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning
Published 2024-11-01“…Experimental results demonstrate that the optimized deep learning algorithm excels in precision (96.4%), recall (96.2%), and mAP50 (98.3), significantly outperforming other mainstream models. …”
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6111
Enhancing high pressure pulsation test bench performance: a machine learning approach to failure condition tracking
Published 2025-05-01“…The utilization of FCTT has enabled the prediction of HPPT failures, the optimization of maintenance schedules, the minimization of downtime, and the improvement of maintenance practices. …”
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6112
DGCLCMI: a deep graph collaboration learning method to predict circRNA-miRNA interactions
Published 2025-04-01“…Next, we present a joint model that combines an improved neural graph collaborative filtering method with a feature extraction network for optimization. …”
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6113
Utilization of Neural Network in the Diagnosis of Pes Planus and Pes Cavus with a Smartphone Camera
Published 2024-12-01“…Results: The CNN model demonstrated high accuracy in diagnosing Pes planus and Pes cavus, with an optimized area under the curve of 0.897 for Pes Planus and 0.898 for Pes cavus. …”
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6114
Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights
Published 2025-04-01“…This study introduces innovative ensemble learning models that integrate the randomizable filter classifier (RFC), regression by discretization (RBD), and attribute-selected classifier (ASC) with the random forest (RF) algorithm, resulting in hybrid models (RFC-RF, RBD-RF, and ASC-RF). …”
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6115
Coal mining equipment lifecycle management system architecture and key technology
Published 2025-02-01“…Analyzed the current status and existing problems of coal mining equipment state perception technology, studied indirect perception methods based on non-contact sensing technology, and reduced installation and operation costs while improving solution accuracy. We studied the technical path of remote operation and maintenance of physical models based on digital twin technology, proposed a geometric-mechanism-data model fusion driven operation control and maintenance strategy, and looked forward to the development direction of intelligent comprehensive management technology and system platform for the entire life cycle of coal mining equipment.…”
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6116
Node selection based on label quantity information in federated learning
Published 2021-12-01“…Aiming at the problem that the difference of node data distribution has adverse effect on the performance of federated learning algorithm, a node selection algorithm based on label quantity information was proposed.An optimization objective based on the label quantity information of nodes was designed, considering the optimization problem of selecting the nodes with balanced label distribution under a certain time consumption limit.According to the correlation between the aggregated label distribution of selected nodes and the convergence of the global model, the upper bound of the weight divergence of the global model was reduced to improve the convergence stability of the algorithm.Simulation results shows that the new algorithm had higher convergence efficiency than the existing node selection algorithm.…”
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6117
Electricity Demand Projection Using a Path-Coefficient Analysis and BAG-SA Approach: A Case Study of China
Published 2017-01-01“…The BAG-SA algorithm is employed to optimize the coefficients of the multiple linear and quadratic forms of electricity demand estimation model. …”
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6118
An AIoT-Based Automated Farming Irrigation System for Farmers in Limpopo Province
Published 2024-06-01“…A machine learning precipitation prediction algorithm optimizes water usage. The paper also describes a system with multiple sensors that detect soil parameters, and automatically irrigate land based on soil moisture by switching the motor on/off. …”
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6119
Node selection based on label quantity information in federated learning
Published 2021-12-01“…Aiming at the problem that the difference of node data distribution has adverse effect on the performance of federated learning algorithm, a node selection algorithm based on label quantity information was proposed.An optimization objective based on the label quantity information of nodes was designed, considering the optimization problem of selecting the nodes with balanced label distribution under a certain time consumption limit.According to the correlation between the aggregated label distribution of selected nodes and the convergence of the global model, the upper bound of the weight divergence of the global model was reduced to improve the convergence stability of the algorithm.Simulation results shows that the new algorithm had higher convergence efficiency than the existing node selection algorithm.…”
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6120
Lightweight YOLOv8s-Based Strawberry Plug Seedling Grading Detection and Localization via Channel Pruning
Published 2024-11-01“…To improve the detection efficiency and reduce the model's computational cost, the layer-adaptive magnitude-based pruning(LAMP) score-based channel pruning algorithm was applied to compress the base YOLOv8s model. …”
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