An Integrated Electricity–Gas–Heat Energy System Based on the Synergy of Long- and Short-Term Energy Storage by Min Zhang, Jinhao Wang, Huiqiang Zhi, Jun Zhao, Xiao Chang, Shifeng Zhang, Xiangyu Guo, Tengxin Wang

“…Therefore, this paper proposes an integrated energy system planning and optimization method based on hybrid energy storage. Firstly, an adaptive noise integration empirical modal decomposition method based on the optimization improvement of the grey wolf algorithm is designed for the power allocation strategy of the hybrid energy storage system; secondly, for the electric–gas system, an energy management strategy for the hybrid electric–gas energy storage system, taking into account the operating characteristics of the alkaline electrolyzer, is proposed in order to strengthen the complementary mechanism between electric energy storage and gas energy storage. …”
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Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…This study integrated hyperspectral technology with machine learning algorithms to model complex nonlinear relationships and to select the optimal SWHC model. …”
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Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…A combined model was further constructed by integrating both feature sets, and model performance was compared to identify the optimal predictive model.Results‍　‍This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model. …”
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Revolutionize 3D-Chip Design With Open3DFlow, an Open-Source AI-Enhanced Solution by Yifei Zhu, Zhenxuan Luan, Dawei Feng, Weiwei Chen, Lei Ren, Zhangxi Tan

“…<italic>Open3DFlow</italic>&#x2019;s open-source nature allows seamless integration of custom AI optimization algorithms. As a showcase, we leverage large language models (LLMs) to help the bonding pad placement. …”
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Smart agriculture using IoT for automated irrigation, water and energy efficiency by Subir Gupta, Subrata Chowdhury, Ramya Govindaraj, Kassian T.T. Amesho, Sumarlin Shangdiar, Timoteus Kadhila, Sioni Iikela

“…This study presents an innovative smart agriculture system that integrates Internet of Things (IoT) technologies, predictive algorithms, and automated control mechanisms to optimize irrigation and enhance resource efficiency. …”
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Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network by Chinnakrit Banyong, Natthaporn Hantanong, Supanida Nanthawong, Chamroeun Se, Panuwat Wisutwattanasak, Thanapong Champahom, Vatanavongs Ratanavaraha, Sajjakaj Jomnonkwao

“…Practical implications include optimizing fare structures, enhancing service quality, and improving station accessibility to support sustainable adoption.…”
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Using machine learning techniques to evaluate the impact of future climate change on wheat yields in Xinjiang, China by Xuehui Gao, Jian Liu, Haixia Lin, Tehseen Javed, Feihu Yin, Rui Chen, Yue Wen, Jinzhu Zhang, Kefan Yi, Zhenhua Wang

“…Additionally, the impacts of climate change scenarios on wheat yield were predicted using two emission scenarios (SSP45 and SSP85) from global climate models (GCMs) and machine learning (ML) algorithms. …”
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Construction of a machine learning-based risk prediction model for depression in middle-aged and elderly patients with cardiovascular metabolic diseases in China: a longitudinal st... by Gege Zhang, Sijie Dong, Li Wang

“…LASSO regression was used to screen for risk factors, and three machine learning algorithms—logistic regression (LR), random forest (RF), and XGBoost—were employed to build predictive models. …”
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Intelligent Path Tracking for Single-Track Agricultural Machinery Based on Variable Universe Fuzzy Control and PSO-SVR Steering Compensation by Huanyu Liu, Zhihang Han, Junwei Bao, Jiahao Luo, Hao Yu, Shuang Wang, Xiangnan Liu

“…Additionally, a heading deviation prediction model based on Support Vector Regression (SVR) optimized by Particle Swarm Optimization (PSO) is introduced, and a steering angle compensation controller is designed to improve the turning accuracy. …”
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Investigation of Hysteresis Phenomena and Compensation in Piezoelectric Stacks for Active Rotor by Xiancheng Gu, Weidong Yang, Linghua Dong, Jinlong Zhou

“…Subsequently, the Bouc–Wen model is adopted to establish the hysteresis model of the piezoelectric actuator, with its parameters identified through the particle swarm optimization (PSO) algorithm. …”
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Construction of a Prediction Model for Sleep Quality in Embryo Repeated Implantation Failure Patients Undergoing Assisted Reproductive Technology Based on Machine Learning: A Singl... by Zhao Y, Xu C, Qin N, Bai L, Wang X, Wang K

“…Yanjun Zhao,1,&amp;ast; Chenying Xu,1,&amp;ast; Ningxin Qin,2,&amp;ast; Lina Bai,1 Xuelu Wang,1 Ke Wang2 1Operating Room, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, People’s Republic of China; 2Reproductive Medicine Center, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, People’s Republic of China&amp;ast;These authors contributed equally to this workCorrespondence: Xuelu Wang, Email wangxuelu@51mch.com Ke Wang, Email wangkeyfy@126.comObjective: Constructing a predictive model for sleep quality in embryo Repeated Implantation Failure(RIF) patients using multiple machine learning algorithms, verifying its performance, and selecting the optimal model.Methods: Retrospective collection of clinical data from RIF patients who underwent assisted reproductive technology at the Reproductive Medicine Center of Tongji University Affiliated Obstetrics and Gynecology Hospital from January 2022 to June 2022, divided into a training set and a validation set in an 8:2 ratio. …”
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The outcome prediction method of football matches by the quantum neural network based on deep learning by Yang Sun, Hongyang Chu

“…During the model training phase, gradient descent is used to optimize weight parameters, and quantum algorithms are integrated to continuously adjust network weights to minimize prediction errors. …”
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Ensemble machine learning prediction accuracy: local vs. global precision and recall for multiclass grade performance of engineering students by Yagyanath Rimal, Yagyanath Rimal, Navneet Sharma

“…The grid search for random forest algorithms achieved a score of 79% when optimally tuned; however, the training accuracy was 99%. …”
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Review of Maglev Train Dynamics Research by WEN Yanfeng, ZHANG Weifeng, CAI Wenfeng, XU Hao

“…Introducing suspension models into UM software can optimize suspension parameters and dynamics indicators, improving train operational stability and safety. …”
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Application of Fuzzy Logic Sliding Mode Control Approach With PID Structure for Electro-Hydraulic Actuator Tracking System by Muhamad Fadli Ghani, Ahmad Athif Mohd Faudzi, Rozaimi Ghazali, Shahrol Mohamaddan

“…The proposed control strategy was designed with the switching function modification based on an FL approach in the conventional SMC algorithm. Due to the difficulty of concurrent hybrid design, a particle swarm optimization (PSO) algorithm was employed to determine the optimal control variables value. …”
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Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study by Mengting Gu, Wenjie Zou, Huilin Chen, Ruilin He, Xingyu Zhao, Ningyang Jia, Wanmin Liu, Peijun Wang

“…Compared with the two models aforementioned, the Radiology MLP model demonstrated a 33.4%-131.3% improvement in NRI and a 9.3%-50% improvement in IDI, showing better discrimination, calibration and clinical usefulness in three sets, which was selected as the optimal predictive model. …”
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Facial emotion based smartphone addiction detection and prevention using deep learning and video based learning by C. Joseph, P. Uma Maheswari

“…Additionally, face emotion detection algorithms tuned with MnasNet-Teaching Learning Based Optimization (TLBO) and Convolution Neural Networks (CNN)-Cuckoo Search Optimization (CSO) are employed for accurate emotion recognition. …”
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Research status of gearboxes for high-power nuclear power circulation pumps by WEI Fude, WANG Huanhuan, YANG Shuncheng

“…Many scholars are committed to in-depth research on high-power nuclear power circulating pump gearboxes from the perspectives of dynamics, mechanical design, big data, optimization algorithms, etc., in response to the above-mentioned issues. …”
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Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…At the same time, the ReLU transfer function ensures robustness, mainly when dealing with noisy or incomplete image segments. Feature vector optimization is performed using a chaotic particle swarm algorithm, enhancing the model’s overall accuracy, reliability, and ease of implementation. …”
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High voltage direct current system-based generation and transmission expansion planning considering reactive power management of AC and DC stations by Ehsan Akbari, Ahad Faraji Naghibi, Mehdi Veisi, Sasan Pirouzi, Sheila Safaee

“…The scheme incorporates a non-linear model. The Red Panda Optimization (RPO) is utilized to solve the provided model in order to attain a dependable and optimal solution. …”
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