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241
Bi-Level Game Strategy for Virtual Power Plants Based on an Improved Reinforcement Learning Algorithm
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242
Ultra Short-Term Charging Load Forecasting Based on Improved Data Decomposition and Hybrid Neural Network
Published 2025-01-01Get full text
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243
Small Target Detection Algorithm for UAV Aerial Images Based on Improved YOLOv7-tiny
Published 2025-05-01“…;Results and Discussions1) The network structure of the improved algorithm is proposed, and the principles and components of each improvement are introduced. …”
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244
A Lightweight Algorithm for Detection and Grading of Olive Ripeness Based on Improved YOLOv11n
Published 2025-04-01“…Olives are a crucial woody oil crop, the harvesting of which predominantly relies on manual labor, which is characterized by high costs, low efficiency, and challenges in ensuring optimal harvesting timing. …”
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245
A Model Predictive Control to Improve Grid Resilience
Published 2025-04-01“…Previous work on MPCs has focused on narrowly targeted control applications such as improving electric vehicle (EV) charging infrastructure or reducing the cost of integrating Energy Storage Systems (ESSs) into the grid. …”
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246
TBESO-BP: an improved regression model for predicting subclinical mastitis
Published 2025-04-01“…The TBESO algorithm notably enhances the efficacy of the BP neural network in regression prediction, ensuring elevated computational efficiency and practicality post-improvement.…”
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247
Load forecasting of microgrid based on an adaptive cuckoo search optimization improved neural network
Published 2024-11-01“…Finally, the weights and biases of the forecasting model were optimized by the improved cuckoo search algorithm. …”
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248
Improved Nonprobabilistic Global Optimal Solution Method and Its Application in Bridge Reliability Assessment
Published 2019-01-01“…Utilizing the improved one-dimensional optimization algorithm conveniently solved the nonprobabilistic reliability index, however, only searching the part of probable failure points. …”
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249
Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy
Published 2024-12-01“…Based on the experimental data of corrosion rates of 3C steel in different seawater environments, an improved Elman neural network model was established by using the whale optimization algorithm. …”
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250
Robust Improvement Strategy for Power Grid Hosting Capacity with Integration of High Proportion of Renewable Energy
Published 2023-09-01“…And then, based on the two-stage robust optimization theory, a strategy model for improving the hosting capacity of the power grid is constructed, and the column and constraint generation (C&CG) algorithm is used to solve the model. …”
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251
Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Vo...
Published 2023-01-01“…It is established that the proposed GOMOHSA finds the optimal deployment of optimally sized RE generators, and the investment cost of deployment of these RE generators can be recovered within a time period that is less than 5 years. …”
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252
Optimization of fuzzy bottleneck cost transportation models in the decision framework of congruence modulo technique
Published 2025-08-01“…This article investigates the Congruence Modulo algorithm and time freezing method as innovative solutions for addressing fuzzy bottleneck cost transportation problems. …”
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253
Sugarcane Feed Volume Detection in Stacked Scenarios Based on Improved YOLO-ASM
Published 2025-07-01“…At the stereo matching level, we enhance the SGBM (Semi-Global Block Matching) algorithm through improved cost calculation and cost aggregation, resulting in Opti-SGBM (Optimized SGBM). …”
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254
A Bi-Objective Optimal Scheduling Method for the Charging and Discharging of EVs Considering the Uncertainty of Wind and Photovoltaic Output in the Context of Time-of-Use Electrici...
Published 2024-09-01“…Finally, the model was solved using an improved multi-objective barebones particle swarm optimization algorithm. …”
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255
Optimization method improvement for nonlinear constrained single objective system without mathematical models
Published 2018-11-01“…In addition, samples are needed to solve such system optimization problems. Therefore, to improve the optimization accuracy of nonlinear constrained single objective systems that are without accurate mathematical models while considering the cost of obtaining samples, a new method based on a combination of support vector machine and immune particle swarm optimization algorithm (SVM-IPSO) is proposed. …”
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256
IMPROVEMENT OF METHODOLOGY ACCOUNTING MANUFACTURING STOCKS OF ENTERPRISE: PROBLEMS AND AREAS OF SETTLEMENT
Published 2018-03-01“…Also content of the article highlights the practical aspects of the turnover, business continuity and rhythm of a single enterprise. By improving the process accounting of manufacturing stocks was developed algorithm optimization of inventory accounting. …”
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257
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Improving Earth surface temperature forecasting through the optimization of deep learning hyper-parameters using Barnacles Mating Optimizer
Published 2024-09-01“…This study proposes a hybrid forecasting model for Earth surface temperature using Deep Learning (DL). To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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259
Research of UAV 3D path planning based on improved Dwarf mongoose algorithm with multiple strategies
Published 2025-07-01“…To enhance UAV adaptability in such environments, improve rapid and efficient path planning capabilities, and reduce operational costs, this paper proposes a 3D UAV path planning algorithm based on an improved Dwarf Mongoose Optimization (DMO) algorithm enhanced with multiple strategies. …”
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260
Cost-Effective Optimization of Sizing and Charging Profiles for PHEV Parking Lots in Smart Microgrids Using Harmony Search Algorithm
Published 2025-01-01“…However, EV participation significantly reduces ohmic losses and improves the grid load profile. The proposed HS algorithm outperforms the DE algorithm by achieving lower microgrid costs and better convergence efficiency. …”
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