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2001
An Optimization Framework for Waste Treatment Center Site Selection Considering Nighttime Light Remote Sensing Data and Waste Production Fluctuations
Published 2024-11-01“…Using Beijing as a case study, the gradient boosting regression algorithm yielded a prediction accuracy of 92%. Furthermore, in light of the substantial costs associated with waste recovery route planning and site selection for treatment facilities, this research further devised a location and distribution framework for waste treatment centers based on high-precision predictions of waste production while employing multi-objective evolutionary algorithms (MOEAs) alongside the non-dominated sorting genetic algorithm II (NSGA-II) for optimization. …”
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2002
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2003
Fields2Benchmark: An open-source benchmark for coverage path planning methods in agriculture
Published 2025-12-01“…The agricultural coverage path planning problem focuses on optimizing coverage paths for agricultural operations. …”
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2004
Performance Analysis of Diabetes Detection Using Machine Learning Classifiers
Published 2024-10-01“…Despite performing well in almost all of the metrics, SGD’s low recall score shows that it is not the most optimal algorithm. Given that recall score is prioritized in the context of clinical diagnostics, Random Forest emerges as a strong candidate due to its balanced performance across key metrics.…”
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2005
Two-Stage Optimization of Mobile Energy Storage Sizing, Pre-Positioning, and Re-Allocation for Resilient Networked Microgrids with Dynamic Boundaries
Published 2024-11-01“…While previous research has optimized the locations of mobile energy storage (MES) devices, the critical aspect of MES capacity sizing has been largely neglected, despite its direct impact on costs. …”
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2006
A Mixed Integer Linear Formulation and a Grouping League Championship Algorithm for a Multiperiod-Multitrip Order Picking System with Product Replenishment to Minimize Total Tardin...
Published 2022-01-01“…A mixed integer linear programming formulation is proposed for this new problem. The model is optimally solved for small-size problems. For larger instances, grouping metaheuristic algorithms are proposed based on particle swarm optimization and the league championship algorithm that use group-based operators to generate reasonable batches of orders. …”
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2007
Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks
Published 2025-01-01“…The main objectives are to reduce the number of unserved demands and operational costs. A simulation model was developed in MATLAB, utilizing the Non-dominated Sorting Genetic Algorithm (NSGA-II), a powerful multi-objective optimization technique that balances conflicting objectives to achieve the best trade-offs for operational efficiency. …”
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2008
Fine-Tuned Machine Learning Classifiers for Diagnosing Parkinson’s Disease Using Vocal Characteristics: A Comparative Analysis
Published 2025-03-01“…This study seeks to assess the effectiveness of machine learning algorithms optimized to classify PD based on vocal characteristics to serve as a non-invasive and easily accessible diagnostic tool. …”
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2009
Enhancing Last-Mile Logistics: AI-Driven Fleet Optimization, Mixed Reality, and Large Language Model Assistants for Warehouse Operations
Published 2025-04-01“…Due to the rapid expansion of e-commerce and urbanization, Last-Mile Delivery (LMD) faces increasing challenges related to cost, timeliness, and sustainability. Artificial intelligence (AI) techniques are widely used to optimize fleet management, while augmented and mixed reality (AR/MR) technologies are being adopted to enhance warehouse operations. …”
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2010
RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction
Published 2025-07-01“…The graphs are processed using a graph neural network with DiffPool. To optimize feature integration, we incorporate an improved dung beetle optimization algorithm, which adaptively assigns fusion weights during inference. …”
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2011
Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes
Published 2025-03-01“…Predictive control uses the Newton-Raphson as the optimization algorithm and a multi-layer feedforward neural network for the state prediction. …”
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2012
A two-stage robust optimization model for emergency service facilities location-allocation problem under demand uncertainty and sustainable development
Published 2025-01-01“…Finally, we examine the influence of demand uncertainty and environmental impact cost on the optimal solution, yielding valuable managerial insights.…”
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2013
Forecast-Aided Converter-Based Control for Optimal Microgrid Operation in Industrial Energy Management System (EMS): A Case Study in Vietnam
Published 2025-06-01“…The forecasted load data is then used to optimize charge/discharge schedules for energy storage systems (ESS) using a Particle Swarm Optimization (PSO) algorithm. …”
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2014
Micro hole drilling and multi criteria optimization of soda lime glass via ultrasonic assisted rotary electrochemical discharge drilling
Published 2025-05-01“…Machine learning-based algorithms are also used to predict the responses using Random Forest and Gradient Boost approaches. …”
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2015
Management of the business system of the enterprise
Published 2021-12-01“…An algorithm for determining the optimal share of sales costs in revenue is proposed. …”
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2016
LGN-YOLO: A Leaf-Oriented Region-of-Interest Generation Method for Cotton Top Buds in Fields
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2017
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2018
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2019
Enhanced recurrent attention-deep Q learning with optimal node constrains and effective penalty based model for data transmission scheduling on wireless sensor networks
Published 2025-06-01“…Additionally, the algorithm’s efficiency contributes to cost savings and resource conservation, making it a socially responsible choice for managing wireless sensor networks.…”
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2020
Enhancing resilience of distribution system under extreme weather: Two-stage energy storage system configuration strategy based on robust optimization
Published 2025-06-01“…Finally, a two-stage robust optimization model for the ESS is established to improve DN resilience with the objective of minimizing the comprehensive economic cost of the ESS and the annual comprehensive weighted load loss, which is solved using the column-and-constraint generation algorithm (C&CG). …”
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