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2401
Experimental acoustic study of small horizontal axis wind turbines based on computational fluid dynamics and artificial intelligence approaches
Published 2024-12-01“…However, the extensive numerical computations required for accurate evaluation often hinder the implementation of multi-objective optimization strategies. This paper introduces an innovative approach to address this issue, leveraging a combination of neural network-based reduced order modeling and a multi-objective genetic algorithm. …”
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2402
Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment
Published 2025-03-01“…Moreover, understanding the relative importance and contribution of different waste properties to HHV prediction is critical for improving the model's predictive capability and optimizing the waste-to-energy (WTE) process. …”
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2403
IntelliGrid AI: A Blockchain and Deep-Learning Framework for Optimized Home Energy Management with V2H and H2V Integration
Published 2025-02-01“…The proposed approach can dynamically optimize household energy flows, deploying real-time data and adaptive algorithms to balance energy demand and supply. …”
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2404
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2405
Leveraging RRT<sup>*</sup>: Probabilistically Interpreted Mechanisms Enhanced With P-HOPE and FLEX-OPT for Complex Path Planning
Published 2025-01-01“…Second, a flexible mechanism FLEX-OPT is developed to adaptively and dynamically adjust the search strategy through real-time feedback and monitoring of the cost function to tackle the above-mentioned local minima problem, which significantly improves the convergence speed and path quality of the algorithm. …”
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2406
Strategic Integration of Battery Energy Storage Systems for Effective EV Charging Demand Management in Transactive Energy Markets
Published 2025-01-01“…Using the DIgSILENT PowerFactory power system software for modeling and simulation, the active and reactive power dispatch of BESS is optimized via a differential evolution (DE) algorithm. …”
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2407
SIDDA: SInkhorn Dynamic Domain Adaptation for image classification with equivariant neural networks
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2408
Optimal Sizing, Techno-Economic Feasibility and Reliability Analysis of Hybrid Renewable Energy System: A Systematic Review of Energy Storage Systems’ Integration
Published 2025-01-01“…The findings show that integrating HRES with ESS can lead to more sustainable energy systems, providing a long-term, reliable, and cost-effective solution. Findings emphasize the need for further study of optimization methods, meta-heuristic algorithm strategies, system components, design constraints, and desired techniques.…”
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2409
A Classification-Based Blood–Brain Barrier Model: A Comparative Approach
Published 2025-05-01“…Feature selection algorithms play a crucial role in identifying the most relevant descriptors, thereby enhancing prediction accuracy. …”
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2410
Research on early warning model of coal spontaneous combustion based on interpretability
Published 2025-05-01“…XGBoost, SVR, RF, LightGBM and BP models were selected as base models to establish an early warning model for CSC based on the stacking integration architecture. The grid search algorithm was utilized to optimize the model parameters, ensuring the selection of the most suitable parameter configurations. …”
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2411
Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach
Published 2025-05-01“…Accurate prediction of electricity price (EP) is crucial for energy utilities and grid operators for enhancing the energy trading, grid stability studies, resource allocations and pricing strategies, thereby improving the overall grid reliability, efficiency, and cost-effectiveness. …”
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2412
A Miniaturized and Intelligent Lensless Holographic Imaging System With Auto-Focusing and Deep Learning-Based Object Detection for Label-Free Cell Classification
Published 2024-01-01“…Our system uses unstained cells suspended in solution as samples and employs a threshold segmentation-based auto-focusing algorithm to determine the optimal focusing distance for each imaging session. …”
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2413
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2414
An intelligent incentive-based demand response program for exhaustive environment constrained techno-economic analysis of microgrid system
Published 2025-01-01“…Abstract The cost-effective scheduling of distributed energy resources through sophisticated optimization algorithms is the main focus of recent work on microgrid energy management. …”
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2415
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2416
Empowering Fuel Cell Electric Vehicles Towards Sustainable Transportation: An Analytical Assessment, Emerging Energy Management, Key Issues, and Future Research Opportunities
Published 2024-10-01“…To address these challenges, smart energy management involving appropriate converters, controllers, intelligent algorithms, and optimizations is essential for enhancing the effectiveness of FCEVs towards sustainable transportation. …”
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2417
Torsional Vibration Characterization of Hybrid Power Systems via Disturbance Observer and Partitioned Learning
Published 2025-05-01“…In contrast, incorporating the parameter self-learning algorithm reduces the RMSE to 2.36 N·m, representing an 85.2% improvement in estimation accuracy. …”
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2418
An enhanced approach for automatic annotation of error codes based on Seq2edit
Published 2025-07-01“…By dividing the code into statements with independent meanings and introducing a cost coefficient to improve the Levenshtein algorithm, this method optimizes the calculation of edit distance and enhances the ability to align tokens. …”
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2419
A Hybrid Evolutionary Fuzzy Ensemble Approach for Accurate Software Defect Prediction
Published 2025-03-01“…To address this, effective feature selection is essential but remains an NP-hard challenge best tackled with heuristic algorithms. This study introduces a binary, multi-objective starfish optimizer for optimal feature selection, balancing feature reduction and classification performance. …”
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2420
Agricultural Machinery Movement Trajectory Recognition Method Based on Two-Stage Joint Clustering
Published 2024-12-01“…The silhouette coefficient method is used to determine the optimal number of clusters k for the K-Means algorithm, thus reducing the data scale. …”
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