Analysis of Smart Grid Optimal Scheduling considering the Demand Response of Different EV Owners by Xiaohua Zhang, Chongyang Liao, Xingrui Chen, Kuiheng Deng, Bolin Chen, Yibo Gong

“…Compared to previous studies, the proposed classified scheduling method exhibits significant improvements in terms of revenue maximization, load distribution among different types of EVs, generation cost savings, and load variance reduction.…”
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A Hierarchical Evolutionary Search Framework with Manifold Learning for Powertrain Optimization of Flying Vehicles by Chenghao Lyu, Nuo Lei, Chaoyi Chen, Hao Zhang

“…Specifically, it achieves a 5.3% improvement in fuel economy, a 7.4% mitigation in battery SOH degradation, and a 1.7% reduction in system manufacturing cost compared to standard NSGA-III-based optimization.…”
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Optimal Allocation of SVG Considering Voltage Mitigation of DG Grid-connected Inverter and APF by Jing XU, Shuya TIAN, Tiejun ZHAO, Xiaogang GAO, Ju YE, Lingyan BU, Wenmiao LIU

“…A multi-objective SVG optimal allocation model is established with minimum total cost of SVG and optimal mitigation effect of system voltage deviation, and the improved genetic algorithm is used to solve the allocation model. …”
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Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

“…However, traditional methods for crack detection often suffer from low efficiency and limited accuracy, necessitating improvements in the accuracy of existing crack detection algorithms. …”
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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

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Formative research to optimize pre-eclampsia risk-screening and prevention (PEARLS): study protocol by Nicole Minckas, Alim Swarray-Deen, Sue Fawcus, Rosa Chemwey Ndiema, Annie McDougall, Jennifer Scott, Samuel Antwi Oppong, Ayesha Osman, Alfred Onyango Osoti, Katherine Eddy, Mushi Matjila, George Nyakundi Gwako, Joshua P. Vogel, A. Metin A. Gülmezoglu, Adanna Uloaku Nwameme, Meghan A. Bohren, the PEARLS Trial collaborative group

“…By identifying factors that can influence implementation of pre-eclampsia prevention and care pathways, the findings will inform successful execution of the PEARLS trial, and post-research scale-up activities. This, in turn, can help reduce the prevalence of pre-eclampsia, and improve maternal and newborn outcomes in high-burden settings. …”
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DDPG-Based UAV-RIS Framework for Optimizing Mobility in Future Wireless Communication Networks by Yasir Ullah, Idris Olalekan Adeoye, Mardeni Roslee, Mohd Azmi Ismail, Farman Ali, Shabeer Ahmad, Anwar Faizd Osman, Fatimah Zaharah Ali

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Class-aware multi-source domain adaptation algorithm for medical image analysis using reweighted matrix matching strategy. by Huiying Zhang, Yongmeng Li, Lei He, Wenbo Zhang, Yuchen Shen, Lumin Xing

“…This algorithm employs a class-aware strategy to strengthen positive transfer effects between similar classes. …”
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Joint Configuration and Optimization of Multi-microgrid Shared Energy Storage Based on Coalition Game by Congwei JIANG, Qinghe OU, Zhongchao WU, Jian ZHANG, Shu YANG, Jianan ZHU, Qian AI

“…Considering that the capacity configuration and operation optimization of energy storage equipment are coupled, this paper adopts an energy cell–organization framework, proposes a two-stage multi-objective optimal configuration scheme of the shared energy storage based on a coalition game, and fairly allocates the coalition cooperation costs by using the Shapley method. …”
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Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases by A. Naderi Beni, H. Bagherpour, J. Amiri Parian

“…Today, deep convolutional neural networks (DCNNs), a novel approach to image classification, have become the most crucial detection method. DCNNs improve detection or classification accuracy by developing machine-learning models with many hidden layers to extract optimal features. …”
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Optimization and benefit evaluation model of a cloud computing-based platform for power enterprises by Xueli Yin, Xuguang Zhang, Luyao Pei, Rong Hu, Kaihui Ye, Kangkang Cai

“…In addition, through containerized deployment and intelligent orchestration, it achieves a 43% reduction in monthly operating costs. A multi-level benefit evaluation system—spanning power generation, grid operations, and end-user services—is established, integrating historical data, expert weighting, and dynamic optimization algorithms to enable quantitative performance assessment and decision support. …”
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ADMET evaluation in drug discovery: 21. Application and industrial validation of machine learning algorithms for Caco-2 permeability prediction by Dong Wang, Jieyu Jin, Guqin Shi, Jingxiao Bao, Zheng Wang, Shimeng Li, Peichen Pan, Dan Li, Yu Kang, Tingjun Hou

“…We believe that the model developed in this study could represent a reliable tool for assessing Caco-2 permeability during early-stage drug discovery and the chemical transformation rules derived here could provide insights for optimizing Caco-2 permeability. Scientific contribution A comprehensive validation of various machine learning algorithms combined with diverse molecular representations on a large dataset for predicting Caco-2 permeability was reported. …”
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A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm. by Jingnan Yan, Yue Wu, Kexin Ji, Cheng Cheng, Yili Zheng

“…Next, k-means clustering is applied with the optimal k-value to initialize the parameters of the Gaussian Mixture Model, which are then refined and trained through the Expectation-Maximization algorithm. …”
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Adaptive Optimization and Dynamic Representation Method for Asynchronous Data Based on Regional Correlation Degree by Sichao Tang, Yuchen Zhao, Hengyi Lv, Ming Sun, Yang Feng, Zeshu Zhang

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Data enhanced iterative few-sample learning algorithm-based inverse design of 2D programmable chiral metamaterials by Zhao Zeyu, You Jie, Zhang Jun, Du Shiyin, Tao Zilong, Tang Yuhua, Jiang Tian

“…In this way, the DEIFS algorithm replaces the time-consuming iterative optimization process with a faster and simpler approach that achieves accurate inverse design with dataset whose amount is at least one to two orders of magnitude less than most previous deep learning methods, reducing the dependence on simulated spectra. …”
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Adaptive Control and Market Integration: Optimizing Distributed Power Resources for a Sustainable Grid by Josue N. Otshwe, Bin Li, Songsong Chen, Feixiang Gong, Bing Qi, Ngouokoua J. Chabrol

“…System performance is improved using advanced control strategies together with real-time market-responsive changes and predictive algorithms. …”
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Integrated Time Series Analysis, Clustering, and Forecasting for Energy Efficiency Optimization and Tariff Management by Anderson Jhones Passos Nascimento, Menaouar Berrehil El Kattel, Jose Antonio Fernandes de Macedo, Fernando Luiz Marcelo Antunes

“…The research demonstrated that energy costs for the analyzed public units could be reduced by approximately 2.7 million reais. …”
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Improved energy efficiency using meta-heuristic approach for energy harvesting enabled IoT network by Rekha, Ritu Garg

“…In this article, we propose an optimization algorithm, based on meta-heuristic, to enhance the energy efficiency of amplify and forward relay IoT networks. …”
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Seasonal optimization of solar PV tilt angles for enhanced energy efficiency in Rajasthan, India by Saaransh Choudhary, Shiv Lal, Sumit Verma

“…For this purpose, a general algorithm for the optimization of the solar tilt angle is investigated based on MATLAB software for four different locations in Rajasthan, India. …”
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The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT by LI Xiaohui, YANG Jie, XIA Qin

“…But most of them had the time cost exceeding 80ms, making them could not perform real-time calculations. …”
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