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Optimal Configuration Method for Electric-thermo-hydrogen System Considering Safety Risks
Published 2024-09-01“…Furthermore, the safety risk coefficient is used to convert the safety risk of the hydrogen storage tank into the objective function. The optimal configuration model of the ETHS is then established with the system investment cost, operation cost, and safety risk as optimization objectives, and the tabu chaotic quantum particle swarm optimization (TCQPSO) algorithm is employed to solve the model. …”
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963
Towards Automated Cadastral Map Improvement: A Clustering Approach for Error Pattern Recognition
Published 2025-04-01Get full text
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964
Identifying, Evaluating and Ranking Effective Factors in Improving the Quality of War Tourism in Iran (Rahyan Noor Travels)
Published 2023-02-01“…Due to the uncertainty in determining the importance of the factors based on every criterion, ranking is based on the Fuzzy TOPSIS algorithm. Findings: According to the results, optimizing camp time has been selected as the first and most crucial factor, with a relative proximity index of 0.53467. …”
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965
Robust Optimization of Active Distribution Networks Considering Source-Side Uncertainty and Load-Side Demand Response
Published 2025-07-01“…The simulation results based on the improved IEEE33 bus system show that the proposed method reduces the operation cost by 5.7% compared with the traditional robust optimization, and the cut-load capacity is significantly reduced at a confidence level of 0.95. …”
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966
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967
A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources
Published 2025-03-01“…Additionally, an enhanced Kepler Optimization Algorithm (EKOA) was proposed, incorporating chaos mapping and adaptive learning rate strategies to improve search scope, convergence speed, and solution efficiency. …”
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968
Reliability Analysis of High-Pressure Tunnel System Under Multiple Failure Modes Based on Improved Sparrow Search Algorithm–Kriging–Monte Carlo Simulation Method
Published 2024-11-01“…Then, the improved sparrow search algorithm (ISSA) is used to optimize the hyper-parameters of the Kriging surrogate model, in order to improve the computational efficiency and accuracy of the reliability analysis model. …”
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969
Joint Service Caching and Computing Offloading Strategies for Electrical Equipment Intelligent IoT Platform
Published 2022-04-01“…The simulation results show that the proposed strategy can effectively improve the task processing efficiency, reduce the computing cost of suppliers, and improve the service revenue of the service providers.…”
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970
Hybrid adaptive ant lion optimization with traditional controllers for driving and controlling switched reluctance motors to enhance performance
Published 2025-04-01“…To address these issues, this work introduces a novel hybrid adaptive ant lion optimization (HAALO) algorithm, combined with PI and FOPID controllers, to improve SRM performance. …”
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971
Optimizing Route Planning via the Weighted Sum Method and Multi-Criteria Decision-Making
Published 2025-05-01“…Secondly, this study compares seven heuristic algorithms—the genetic algorithm (GA), particle swarm optimization (PSO), the tabu search (TS), genetic-particle swarm optimization (GA-PSO), the gray wolf optimizer (GWO), and ant colony optimization (ACO)—to solve the TOPSIS model, with GA-PSO performing the best. …”
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972
Efficiency multi-agent model assisted Moea/D algorithm for optimization design for building taking into account annual energy consumption and annual user discomfort hours
Published 2024-12-01“…Then it introduces a multi-agent model auxiliary mechanism to improve the decomposition based multi-objective evolutionary optimization algorithm, and then solves the multi-objective optimization model for building energy efficiency. …”
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973
Optimized multi-unit coordinated scheduling based on improved IGDT: Low-carbon scheduling research for the electric-heat-oxygen integrated energy system
Published 2025-06-01“…This model combines the entropy weight method (EWM) and non-dominated sorting genetic algorithm II (NSGA-II), improving the objectivity and rationality of uncertainty weight settings in risk-averse strategy (RAS) and risk-seeking strategy (RSS). …”
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974
Robust Path Tracking Control with Lateral Dynamics Optimization: A Focus on Sideslip Reduction and Yaw Rate Stability Using Linear Quadratic Regulator and Genetic Algorithms
Published 2025-05-01“…To address this issue, this study proposes the optimization of the linear quadratic regulator (LQR) control system by using the genetic algorithm (GA) to support the vehicle in following the predefined path accurately, minimizing the sideslip, and stabilizing the vehicle’s yaw rate. …”
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A novel research on network security situation prediction based on iteratively optimized RBF-NN
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977
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978
The human-on-the-loop evaluation of multiobjective optimization algorithms for solving a real-world problem that integrates the food-energy-water nexus security and climate change...
Published 2025-09-01“…Such research areas include incorporating machine learning to predict, using performance data, the most suitable algorithm to solve a specific problem, and advancing interactive learning and user adjustments of the optimization process.…”
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979
Multi-objective DG placement in radial distribution systems using the IbI logic algorithm
Published 2024-11-01“…This paper presents a unique optimization method based on the incomprehensible but intelligible-in-time (IbI) logic algorithm (ILA) to optimally place dispersed generators in small, medium, large, and very large (16-, 33-, 69-, and 118-bus) radial distribution power networks to reduce power losses, the total operating cost, and the voltage deviation and improve the voltage level. …”
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980
Advanced Computational Methods for Mitigating Shock and Vibration Hazards in Deep Mines Gas Outburst Prediction Using SVM Optimized by Grey Relational Analysis and APSO Algorithm
Published 2021-01-01“…Moreover, adaptive particle swarm optimization (APSO) was used to optimize the penalty factor and kernel parameters of the support vector machine to improve the global search ability and avoid the occurrence of the local optimal solutions. …”
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