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301
A Novel Black Widow Optimization Algorithm Based on Lagrange Interpolation Operator for ResNet18
Published 2025-06-01“…In an attempt to surmount this challenge, evolutionary computation algorithms can automatically adjust the hyper-parameter learning rate to improve training efficiency and model performance. …”
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302
Theoretical knowledge enhanced genetic algorithm for mine ventilation system optimization considering main fan adjustment
Published 2024-11-01“…However, current algorithms encounter challenges when applied to large-scale mines, primarily due to the complexity of variables and limited attention to optimizing main fans. …”
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303
Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms
Published 2025-06-01“…In this research, we introduce the Improved Multi-Verse Optimizer (IMVO) algorithm, a novel feature selection method that integrates the Multi-Verse Optimizer (MVO) with local search algorithms (LSAs). …”
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304
A new stochastic multi-objective model for the optimal management of a PV/wind integrated energy system with demand response, P2G, and energy storage devices
Published 2025-07-01“…A demand response (DR) program is implemented for both electric and thermal loads to address the inherent uncertainty of renewable energy sources (RESs) and electrical load fluctuations. The proposed optimal management model is a multi-objective optimization problem aiming to minimize total losses, cost, and emissions while meeting energy demands. …”
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305
Application of improved GA in optimizing rural tourism routes
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306
Parameter Sensitivity Analysis and Algorithm Improvement of Optimization Scheduling Model for Cascade Pumping Stations
Published 2024-01-01“…ObjectiveThe low operating efficiency, massive energy consumption and large carbon emissions often exist in the operation of cascade pumping stations. To improve the operational efficiency of cascade pumping stations and vigorously promote dual carbon construction, an optimization scheduling model for cascade pumping stations was established with the goal of minimizing carbon emissions, and the Runge Kutta algorithm (RUN) was introduced to solve the model. …”
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307
Improved PICEA-g-based multi-objective optimization scheduling method for distribution network with large-scale electric vehicles
Published 2024-11-01“…Abstract Large-scale electric vehicle access to the distribution grid for charging can affect the security and economic operation of the grid. In this paper, an optimal scheduling method for large-scale EV access to the distribution grid based on the improved preference-inspired co-evolutionary algorithm using goal vectors (PICEA-g) is proposed. …”
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An Operation Plan Optimization Model for Integrated Customized and Conventional Bus Services Based on Cost Analysis
Published 2022-01-01“…A mixed-integer planning model and a hybrid genetic algorithm are used to optimize the operation plan for specific travel demands and supply capacities. …”
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310
Integrated optimization model for production and equipment dispatching in underground mines
Published 2018-09-01“…The model was validated in a large gold mine in China to work out the optimal equipment scheduling plan. …”
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311
CRASHWORTHINESS DESIGN AND OPTIMIZATION FOR COLLISION POST OF TRAIN
Published 2022-01-01“…In order to improve the crashworthiness of the collision post structure, the optimal cross-section configuration of the collision post was obtained based on the topology optimization method, and the impacting finite element model of the collision post was established in the explicit dynamics software Ls-Dyna. …”
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312
Optimization for Express/Local Train Stop Plans on City Rapid Rail Transit Lines
Published 2025-07-01“…[Result & Conclusion] The stop plan verifies the effectiveness of the proposed model and algorithm. While the optimized stop plan for express/local trains on city rapid rail transit lines reduces passenger travel costs by 19.48%, increases enterprise operational costs by 4.23%, and leads to an overall cost reduction of 4.18%. …”
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313
Integrated Scheduling Optimization for Multi-Line Production and Transportation of Prefabricated Components Considering Shared Resources
Published 2025-01-01“…With on-time delivery and lower costs as the goals, a scheduling optimization mathematical model is established for this scenario. …”
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314
Smart village construction and college students’ skills entrepreneurship path based on LSTM and simulated annealing algorithm
Published 2025-07-01“…At the same time, in order to improve the success rate and profitability of college students’ skill entrepreneurship projects, a series of simulation experiments were carried out with the help of simulated annealing algorithm, and an optimal path taking into account costs and benefits was determined through the simulation and comparison of different entrepreneurial models. …”
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A multi-objective path optimization method for plant protection robots based on improved A*-IWOA
Published 2024-12-01“…Methods To address the challenges of achieving low energy consumption and efficiency in path planning for plant protection robots operating in mountainous environments, a multi-objective path optimization approach was developed. This approach combines the improved A* algorithm with the Improved Whale Optimization Algorithm (A*-IWOA), utilizing a 2.5D elevation grid map. …”
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317
PSO Based Optimization of Testing and Maintenance Cost in NPPs
Published 2014-01-01“…Technical specification and maintenance-related parameters, that is, allowed outage time (AOT), maintenance period and duration, and so forth, in NPP are associated with controlling risk level and operating cost which need to be minimized. The above problems can be formulated by a constrained multiobjective optimization model, which is widely used in many other engineering problems. …”
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318
RSM-YOLOv11: Lightweight Steel Surface Defect Segmentation Algorithm Research Based on YOLOv11 Improvement
Published 2025-01-01“…The model size is reduced by 23.81%, and the computational cost is decreased by 15.38%. …”
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OPTIMIZATION OF FUZZY INVENTORY MANAGEMENT IN INDUSTRIAL PROCESSES USING DEEP LEARNING ALGORITHMS: A HYBRID APPROACH FOR ENHANCING DEMAND FORECASTING AND SUPPLY CHAIN EFFICIENCY
Published 2024-12-01“…A mathematical model and algorithmic implementation demonstrate the approach’s effectiveness and a numerical example highlights improvements in inventory control, including reduced holding costs. …”
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