Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks by Aya M. A. Heikal, Shady H. E. Abdel Aleem, Ragab A. El-Sehiemy, Almoataz Y. Abdelaziz

“…Results demonstrate significant improvements in system reliability, cost efficiency, and flexible operation, validating the effectiveness of ANN-based AL to optimize EHs management and ensure sustainable operation complexities. …”
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Modified invasive weed optimization MPPT approach for PV system interfaced with BLDC motor for water pumping system by S. Nagaraja Rao, B. M. Kiran Kumar, B. M. Manjunatha, A. Suresh Kumar

“…Therefore, the modified invasive weed optimization (MIWO) approach integrated with P&O approach to improve performance under PSC. …”
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Optimized actuator design for flapping-wing robots: A multi-objective approach to mimic natural flapping dynamics by Peiqi Li, Zhiwei Ai, Mufan Zhang

“…The optimization utilized the NSGA-II algorithm. Additionally, a virtual prototype with rigid-flexible coupling was created for simulation assessments pre- and post-optimization. …”
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Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features by Qu FZ, Ding J, An XF, Peng R, He N, Liu S, Jiang X

“…Following the elimination of features with significant missing values, the remaining features were utilized to construct predictive models employing six machine learning algorithms. The optimal model was selected based on various performance metrics, including the area under the curve (AUC), accuracy, precision, recall, and F1 score. …”
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Optimizing Location of Car-Sharing Stations Based on Potential Travel Demand and Present Operation Characteristics: The Case of Chengdu by Yu Cheng, Xu Chen, Xiaohua Ding, Linting Zeng

“…This study aims to use different data source with statistical models and machine learning algorithm to help car-sharing operator to choose the optimal location of new stations and adjust the location of existing stations. …”
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Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…This study focuses on the multi-objective coordination problem in university campus planning and design, proposing an optimized methodology integrating an improved multi-objective decision-making framework. …”
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Peak Arm Current Reduction of Modular Multilevel Converter Based on Particle Swarm Optimizer for Circulating Current Injections by Riyadh Toman Thahab, Tahani Hamodi Al-Mhana

“…This paper uses a particle swarm optimisation (PSO) algorithm to determine the optimal values for the injected components. …”
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A Wi-Fi Indoor Localization Strategy Using Particle Swarm Optimization Based Artificial Neural Networks by Nan Li, Jiabin Chen, Yan Yuan, Xiaochun Tian, Yongqiang Han, Mingzhe Xia

“…We implement the proposed system on a mobile phone and the positioning results show that our algorithm can provide a higher localization accuracy and significantly improves the prediction speed.…”
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Decoding On-Field Roles in Football: A Sociological Analysis Using Intelligent MCDM Algorithm With Fuzzy Information for Player Positioning and Technical-Tactical Behavior by Lu Yan, Nannan Wang, Rui Chen

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Distributionally robust optimal scheduling of flexible distribution networks considering dynamic spatio-temporal correlation of renewable energy by Shunxiang Yu, Xiaoming Dong, Chengfu Wang, Tianguang Lu

“…By utilizing the 1-norm and ∞-norm to characterize the uncertainty sets between sources and loads, this strategy effectively minimizes operational costs while ensuring robust performance. The proposed model is linearized and relaxed through second-order cone programming and solved using the column and constraint generation (C&CG) algorithm. …”
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Precision Soil Moisture Monitoring Through Drone-Based Hyperspectral Imaging and PCA-Driven Machine Learning by Milad Vahidi, Sanaz Shafian, William Hunter Frame

“…The primary aim was to understand the relationship between root zone water content and canopy reflectance, pinpoint the depths where this relationship is most significant, identify the most informative wavelengths, and train a machine learning model using those wavelengths to estimate soil moisture. …”
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Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…This complex multi-million-dollar problem involves optimizing multiple parameters using computationally intensive reservoir simulations, often employing advanced algorithms such as optimization algorithms and machine/deep learning techniques to find near-optimal solutions efficiently while accounting for uncertainties and risks. …”
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A Distributed Economic Power Dispatch Strategy Considering State of Charge for Microgrids by Kaicheng Lu, Shufeng Dong, Yonghua Song

“…Every node estimates the average SoC of all battery energy storage systems(BESSs) in a microgrid and determines the power of the local BESS and microturbine (MT) autonomously to achieve SoC balancing and economic dispatch with component constraints and power balance constraints by peer-to-peer communication with its neighbors. To improve the effectiveness of power distribution, an improved average consensus algorithm(IACA) based on particle swarm optimization (PSO) is proposed to adjust the weight matrix of communication networks, which reduces the number of iterations to estimate the average SoC. …”
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Strength prediction and optimization for microwave sintering of large-dimension lithium hydride ceramics: GA-BP-ANN modeling by Hongzhou Yan, Huayan Chen, Wenyan Zhang, Maobing Shuai, Bin Huang

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Solving Action Semantic Conflict in Physically Heterogeneous Multi-Agent Reinforcement Learning with Generalized Action-Prediction Optimization by Xiaoyang Yu, Youfang Lin, Shuo Wang, Sheng Han

“…Conversely, completely independent agent parameters significantly escalate computational costs and training complexity. To address these challenges, we introduce an adaptive MARL algorithm named Generalized Action-Prediction Optimization (GAPO). …”
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On the Use of Azimuth Cutoff for Sea Surface Wind Speed Retrieval From SAR by Yuting Zhu, Giuseppe Grieco, Jiarong Lin, Marcos Portabella, Xiaoqing Wang

“…The methodology probabilistically combines SAR data with ancillary meteorological information and optimizes the retrieval process through a cost function that leverages the sensitivity of the azimuth cutoff to changes in wind vector fields. …”
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Neural network inspired efficient scalable task scheduling for cloud infrastructure by Punit Gupta, Arnaav Anand, Pratyush Agarwal, Gavin McArdle

“…In this work, we aim to use the Harmony Search Algorithm and neural networks to create a fault aware system for optimal usage of cloud resources. …”
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Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China by Jinze Li, Xiao Wang, Qiyan Zhang, Peng Tang

“…This framework uses corroborative multi-source data to analyze current EMS facilities and suggests improvements through preservation, expansion, and new facility introduction, carefully considering construction costs, resident usage efficiency, and access equity. …”
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Bayesian Network-Based Landslide Susceptibility Safe Route Assessment in the Face of Uncertain Knowledge and Various Information by Xinyu Gao, Bo Wang, Wen Dai, Yuanmin Liu

“…The BN model effectively integrates multi-source data and uncertainty knowledge to generate an accurate LSM, while the improved A* algorithm combines safety and efficiency considerations to optimize routes. …”
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Detection Method for Bolts with Mission Pins on Transmission Lines Based on DBSCAN-FPN by Zhenbing ZHAO, Shuai ZHANG, Wei JIANG, Peng WU

“…Then, the FPN model is improved: based on the prior knowledge of bolts, the convolutional network is used to achieve bottom-up feature extraction, the bilinear interpolation method is used to transfer the high-level semantic information of the features to each level from top to bottom, the convolution filtering method is used to laterally strengthen the information fusion of high-level semantic features and high-resolution features, and a more optimized feature expression of bolts with missing pins is obtained. …”
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