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1941
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1942
Ensemble Learning-Based Wine Quality Prediction Using Optimized Feature Selection and XGBoost
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1943
Optimizing urban energy flows: Integrative vehicle-to-building strategies and renewable energy management
Published 2025-04-01“…This study introduces a scalable, multi-objective optimization model that utilizes Vehicle-to-Building (V2B) interactions to mitigate grid load by leveraging EVs as mobile energy storage units. …”
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1944
Multi-Objective Optimization of Insulation Thickness with Respect to On-Site RES Generation in Residential Buildings
Published 2024-11-01“…This paper investigates the optimization of insulation thickness with respect to the integration of renewable energy systems in residential buildings in order to improve energy efficiency, maximize the contribution of renewables and reduce life cycle costs. …”
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1945
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1946
A dual-layer planning method based on improved MOPSO for distribution networks considering source–load temporal uncertainty
Published 2025-07-01“…Third, an improved multi-objective particle swarm optimization (MOPSO) algorithm with adaptive inertia weights accelerates the convergence by 25%. …”
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1947
Optimization of Graphene Oxide’s Characteristics with TOPSIS Using an Automated Decision-Making Process
Published 2023-06-01“…Moreover, their advantages and inconveniences could be investigated better once this investigation provides information on optimizing its candidates. In the current research work, a novel automated decision-making process was used with the TOPSIS algorithm using the Łukasiewicz disjunction, which helped detect the confusion of properties and determine its impact on the rank of candidates. …”
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1948
A Day-Ahead Optimal Battery Scheduling Considering the Grid Stability of Distribution Feeders
Published 2025-02-01“…This study presents a comprehensive framework for optimizing energy management systems by integrating advanced methodologies for weather forecasting, energy cost analysis, and grid stability using a mixed-integer linear programming (MILP) algorithm. …”
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1949
Analysis of Smart Grid Optimal Scheduling considering the Demand Response of Different EV Owners
Published 2023-01-01“…According to charging and vehicle-to-grid (V2G) data of EV owners, the K-means clustering algorithm (K-means) is used to classify EV owners, and the demand response (DR) model is established based on the classification results. …”
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1950
Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation
Published 2025-07-01“…The optimization model is solved using the Modified Water Evaporation algorithm. …”
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1951
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1952
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1953
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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1954
State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach
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1955
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1956
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1957
Robust Optimization for Microgrid Management With Compensator, EV, Storage, Demand Response, and Renewable Integration
Published 2024-01-01“…Numerical simulations on a test system validate the effectiveness of the proposed model and solution algorithm, showing a significant reduction in the operating costs of the microgrid. …”
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1958
Enhanced medical image segmentation using novel level set evolution and efficient optimization
Published 2025-05-01“…Unlike prior edge-based algorithms, which frequently fail with noisy images and have large computing costs, our method incorporates an improved edge indicator term into the level set architecture, considerably improving performance on degraded images. …”
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1959
Optimization method of investment package based on Markowitz portfolio theory
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Article -
1960
Short-term load estimation based on improved DBN-LSTM
Published 2025-07-01“…The pruning algorithm is used to optimize the redundant structure of the model, reduce the complexity and training time of the model, and maintain or improve the forecasting accuracy. …”
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Article