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2001
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2002
RFID‐Based Enhanced Resource Optimization for 5G/6G Network Applications
Published 2025-06-01“…RFID readers strategically placed across the network continuously captured this data, which was processed by a centralized controller using a custom‐designed optimization algorithm. This algorithm dynamically managed key network resources, including spectrum allocation, load balancing, and energy consumption, ensuring efficient operation under varying network conditions. …”
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Article -
2003
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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Article -
2004
Optimizing TCP Performance in Multi-AP Residential Broadband Connections via Minislot Access
Published 2013-01-01Get full text
Article -
2005
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2006
Application of Artificial Intelligence with Ant Colony Algorithm in construction projects schedule
Published 2018-11-01“…So useMethodology of Scheduling of Projects with Artificial Intelligence and with the Approach of Ant Colony Algorithm for Organizations MethodOptimal and practical among other methods. …”
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Article -
2007
Ensemble Learning-Based Wine Quality Prediction Using Optimized Feature Selection and XGBoost
Published 2025-10-01Get full text
Article -
2008
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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Article -
2009
Three-Dimensional Path Planning for Unmanned Aerial Vehicles Based on Hybrid Multi-Strategy Dung Beetle Optimization Algorithm
Published 2025-05-01“…This paper proposes a novel UAV path planning method based on the Hybrid Multi-Strategy Dung Beetle Optimization Algorithm (HMSDBO), which effectively reduces path length and improves path smoothness. …”
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2010
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2011
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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Article -
2012
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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Article -
2013
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2014
Source-storage-load optimization control technology of DC microgrid with virtual energy storage
Published 2025-04-01“…On this basis, under the coordinated control of source and storage of DC microgrid, particle swarm optimization algorithm is used to optimize the design of virtual capacitance values in different periods of time to improve the economic benefits of the system. …”
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2015
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2016
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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Article -
2017
Optimization Study of PVT Coupled Water Loop Heat Pump Energy Supply System
Published 2025-01-01“…This study designs a building energy supply system integrating PVT and a water-loop heat pump based on Tianjin's meteorological data, using TRNSYS software to establish a dynamic model. By employing the Hooke-Jeeves algorithm, the system's design and operation parameters were optimized with annual cost and system COP as objective functions. …”
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Article -
2018
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2019
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 -
2020