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2141
Optimization Design of Node Placement Manipulators Based on Working Area and Response Speed
Published 2024-01-01“…As the key equipment of data acquisition in oil and gas exploration, the node can be replaced by a mechanical arm because of its long-term continuous work and high efficiency, but the structure rigidity is weak and the motion ability is poor, so the structure optimization and lightweight design are carried out to improve the structure rigidity and motion ability. …”
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2142
Integrative electricity need prediction utilizing enhanced squeeze net and flexible Coyote optimization algorithm A combination of RCPs SSPs and socioeconomic
Published 2025-07-01“…The effectiveness of the compact network is increased by using the Flexible Coyote Optimization Algorithm (FCOA), which plays a vital role in optimizing parameters and accelerating convergence. …”
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2143
Optimization and benefit evaluation model of a cloud computing-based platform for power enterprises
Published 2025-07-01“…The proposed model focuses on resource scheduling optimization, task load balancing, and improvements in computational efficiency. …”
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2144
A Deep Reinforcement Learning-Driven Seagull Optimization Algorithm for Solving Multi-UAV Task Allocation Problem in Plateau Ecological Restoration
Published 2025-06-01“…To solve this model, a deep reinforcement learning-based seagull optimization algorithm (DRL-SOA) is proposed, which integrates deep reinforcement learning with the seagull optimization algorithm (SOA) for adaptive optimization. …”
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2145
Fusion of Visible and Infrared Images Using a Reinforcement Learning System Based on Fuzzy Logic and Convolution Optimized with Wild Horse Algorithm
Published 2025-05-01“…This hybrid reinforcement learning system was optimized using algorithms including wild horse optimization (WHO), genetic algorithm (GA), and particle swarm optimization (PSO) to improve specific fusion metrics such as image correlation, similarity coefficient, image entropy, and signal-to-noise ratio. …”
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2146
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2147
Short-term prediction of regional energy consumption by metaheuristic optimized deep learning models
Published 2024-11-01“…Second, a newly developed metaheuristic optimization algorithm, JS, was used to improving model accuracy. …”
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2148
PM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decoder Model
Published 2021-01-01“…By combining the GA-based feature selection algorithm and the E-D model, our proposed approach further improves the accuracy by at least 13.7%.…”
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2149
Sustainable energy: Advancing wind power forecasting with grey wolf optimization and GRU models
Published 2024-12-01“…This paper introduces a novel method that combines the Grey Wolf Optimization (GWO) algorithm with data compression techniques to enhance feature selection and reduce redundancy in wind speed prediction. …”
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2150
Leveraging Game Theory to Design Incentive-Compatible Time-Varying electricity pricing with Demand-Side management
Published 2024-10-01“…This study investigates a novel approach to improve energy efficiency through a Demand Response (DR) program with a Game Theory (GT)-based Time-of-Use (ToU) pricing model. …”
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2151
Application of Simulated Annealing Algorithm in the Construction of Online Examination System for Tax Law Courses
Published 2025-01-01“…This study proposes a simulated annealing (SA)-based optimization model for dynamically generating balanced online examinations in tax law courses. …”
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2152
PSO-NMPC control strategy based path tracking control of mining LHD (scraper)
Published 2024-11-01“…To address these issues, this paper proposes a PSO-NMPC control strategy that integrates a particle swarm optimization algorithm (PSO) into the NMPC controller to enhance path tracking for LHDs. …”
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2153
A hybrid optimization algorithm based on cascaded (1 + PI)-PI-PID controller for load frequency control in interconnected power systems
Published 2024-12-01“…This study introduces a cascaded (1+PI)-PI-PID controller optimized using the improved Artificial Bee Colony-Particle Swarm Optimization (IABC-PSO) algorithm for LFC in interconnected power systems, aiming to address complex challenges associated with LFC in modern power systems. …”
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2154
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2155
Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases
Published 2024-12-01“…Today, deep convolutional neural networks (DCNNs), a novel approach to image classification, have become the most crucial detection method. DCNNs improve detection or classification accuracy by developing machine-learning models with many hidden layers to extract optimal features. …”
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2156
Task offloading optimization in mobile edge computing based on a deep reinforcement learning algorithm using density clustering and ensemble learning
Published 2025-01-01“…Secondly, DCEDRL utilizes an optimized density clustering method to identify and classify computing tasks with similar characteristics to improve subsequent task scheduling and resource allocation efficiency. …”
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2157
A new neurodynamic model with Adam optimization method for solving generalized eigenvalue problem
Published 2021-06-01“…The experiments demonstrate that our algorithm using Adam optimizer, in comparison with other stochastic optimization methods like gradient descent works well in practice and improves complexity and accuracy of convergence.…”
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2158
Advanced Vehicle Routing for Electric Fleets Using DPCGA: Addressing Charging and Traffic Constraints
Published 2025-05-01“…A large number of experimental results demonstrate that DPCGA significantly outperforms traditional algorithms in terms of performance, achieving an average 3% improvement in customer satisfaction and a 15% reduction in computation time. …”
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2159
FlexSim-Simulated PCB Assembly Line Optimization Using Deep Q-Network
Published 2024-10-01“…The PCB assembly line model is constructed using the FlexSim simulation tool, and the optimal scheduling strategy is learned through the DQN algorithm. …”
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2160
End-to-end throughput evaluation model and optimization method for dual-mode mesh network
Published 2025-07-01“…The proposed resource allocation algorithm improves throughput by 10% compared with traditional resource allocation algorithms. …”
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