Integrated Additive Manufacturing Trajectory Control and Repair Management for Spiral Bevel Gear Using Fractional-Order PID and Adaptive Fuzzy Neural Inference System by Hiyam Adil Habeeb, Abdul Hadi Azman, Mohd Rizal Alkahari, Dzuraidah Abd Wahab, Nurhasyimah Abd Aziz

“…The research objectives concentrate on constructing an adaptive control algorithm for gear repair using metal powder bed fusion technology and assessing these algorithms against state-of-the-art methods. …”
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Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: A machine-learning approach. by Wei-Hsuan Lo-Ciganic, Julie M Donohue, Eric G Hulsey, Susan Barnes, Yuan Li, Courtney C Kuza, Qingnan Yang, Jeanine Buchanich, James L Huang, Christina Mair, Debbie L Wilson, Walid F Gellad

“…This study aimed to improve the accuracy of a machine-learning algorithm to predict opioid overdose risk by integrating human services and criminal justice data with health claims data to capture the social determinants of overdose risk. …”
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Identification of Key Genes Related to Intramuscular Fat Content of Psoas Major Muscle in Saba Pigs by Integrating Bioinformatics and Machine Learning Based on Transcriptome Data by Zixia Huang, Yongli Yang, Jinhua Lai, Qiang Chen, Xiaoyi Wang, Shuyan Wang, Mingli Li, Shaoxiong Lu

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Research on Lithium-Ion Battery State of Health Prediction Based on XGBoost–ARIMA Joint Optimization by Chen Fei, Zhuo Lu, Weiwei Jiang, Liang Zhao, Fan Zhang

“…Subsequently, an XGBoost-based model is constructed to perform the initial SOH estimation. To further enhance the estimation accuracy, we introduce the Autoregressive Integrated Moving Average Model (ARIMA) model for post-estimation correction, effectively refining the preliminary results. …”
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SH-SDS: a new static-dynamic strategy for substation host security detection by Yang Diao, Hui Chen, Wei Liu, Abdur Rasool

“…To reduce the subjectivity in manually selecting features, we combine classified protection for cybersecurity-related standards and construct the requirement generation algorithm to construct a network security detection standard library for the substation host. …”
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A Multi-granularity Heterogeneous Ensemble Model for Point and Interval Forecasting of Carbon Prices by Di Sha, Xianyi Zeng, Kim-Phuc Tran, Lin Xia, Ruolin Wang

“…Third, the Grey Wolf Optimization (GWO) algorithm is applied to calculate the optimal weights for each individual model. …”
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Design an Efficient Neural Network to Determine the Rate of Contamination in the Tigris River in Baghdad City by Luma N. M. Tawfiq, Farah F. Ghazi, T. A. Jawad

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Production Quality Evaluation of Electronic Control Modules Based on Deep Belief Network by Hua Gong, Wanning Xu, Congang Chen, Wenjuan Sun

“…A Multi-mutation Differential Evolution algorithm is designed to optimize the initial network weights of the Deep Belief Network (DBN) and integrate the production quality information into the pre-training phase. …”
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Joint Optimization Method for Preventive Maintenance and Train Scheduling of Subway Vehicles Based on a Spatiotemporal Network Graph by Chuanzhen Liu, Zhongwei Xu, Meng Mei, Wenqing Li

“…Finally, an improved genetic algorithm is employed to solve the model and determine the optimal scheduling and maintenance strategy. …”
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Coalmine image super-resolution reconstruction via fusing multi-dimensional feature and residual attention network by Jian CHENG, Lifei MI, Hao LI, Heping LI, Guangfu WANG, Yongzhuang MA

“…Experimental results indicate that the proposed method significantly outperforms existing mainstream algorithms in both objective evaluation metrics and subjective visual analysis. …”
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Robust Variable Selection via Bayesian LASSO-Composite Quantile Regression with Empirical Likelihood: A Hybrid Sampling Approach by Ruisi Nan, Jingwei Wang, Hanfang Li, Youxi Luo

“…By constructing a hybrid sampling mechanism that incorporates the Expectation–Maximization (EM) algorithm and Metropolis–Hastings (M-H) algorithm within the Gibbs sampling scheme, this approach effectively tackles variable selection in high-dimensional settings with outlier contamination. …”
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Interpretable Machine Learning for Multi-Energy Supply Station Revenue Forecasting: A SHAP-Driven Framework to Accelerate Urban Carbon Neutrality by Zhihui Zhao, Minjuan Wang, Jin Wei, Xiao Cen, Shengnan Du, Ziwen Wu, Huanying Liu, Weiqiang Wang

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Intent-Based Multi-Cloud Storage Management Powered by a Fine-Tuned Large Language Model by Jingya Zheng, Gaofeng Tao, Shuxin Qin, Dan Wang, Zhongjun Ma

“…Additionally, the system constructs a collaborative intent decomposition method, which guarantees the integrity of intents. …”
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Integrated multi-omics analysis and machine learning identify G protein-coupled receptor-related signatures for diagnosis and clinical benefits in soft tissue sarcoma by Duo Wang, Duo Wang, Duo Wang, Jihao Tu, Jihao Tu, Jianfeng Liu, Jianfeng Liu, Yuting Piao, Yuting Piao, Yiming Zhao, Yiming Zhao, Ying Xiong, Ying Xiong, Jianing Wang, Jianing Wang, Xiaotian Zheng, Xiaotian Zheng, Bin Liu, Bin Liu

“…We developed a novel machine learning framework that incorporated 12 machine learning algorithms and their 127 combinations to construct a consensus GPRS to screen biomarkers with diagnostic significance and clinical translation, which was assessed by the internal and external validation datasets. …”
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Identification and verification of biomarkers associated with neutrophils in acute myocardial infarction: integrated analysis of bulk RNA-seq, expression quantitative trait loci, a... by Guoqing Liu, Xiangwen Lv, Jiahui Qin, Xingqing Long, Miaomiao Zhu, Chuwen Fu, Jian Xie, Peichun He

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Machine-Learning-Based Integrated Mining Big Data and Multi-Dimensional Ore-Forming Prediction: A Case Study of Yanshan Iron Mine, Hebei, China by Yuhao Chen, Gongwen Wang, Nini Mou, Leilei Huang, Rong Mei, Mingyuan Zhang

“…Combined with spectral and elemental analysis, the universality of alteration features such as chloritization and carbonation, which are closely related to the mineralization process, was further verified. (3) Based on the spectral and elemental grade data of rock and mineral samples, a training model for ore grade–spectrum correlation was constructed using Random Forests, Support Vector Machines, and other algorithms, with the SMOTE algorithm applied to balance positive and negative samples. …”
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Local Back-Propagation for Forward-Forward Networks: Independent Unsupervised Layer-Wise Training by Taewook Hwang, Hyein Seo, Sangkeun Jung

“…To address this discrepancy, the Forward-Forward (FF) algorithm was introduced. Although FF enables deep learning without backward passes, it suffers from instability, dependence on artificial input construction, and limited generalizability. …”
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Investigation and Application of Water-Saving Monitoring Technology in Public Institutions by WANG Kang, ZHENG Yongjie, ZHANG Zhen, TANG Yanping, SONG Wenhao, GUO Xiaoming

“…Considering the characteristics of water use and the current situation of water facilities in public institutions,this study comprehensively employs the Internet of Things (IoT),cloud deployment,databases,three-dimensional (3D) visualization,and other advanced techniques to create a water-saving reconstruction scheme with integrated software and hardware for public institutions.Therefore,a smart water management platform for public institutions is built to implement advanced water-saving concepts and improve the water management level.The main research results are as follows:① By intelligent remote monitoring equipment,the multiclass water measurement network is designed to realize the fine collection of zonal water use data;② this study designs a reconstruction scheme of water facilities and explores the utilization mode of unconventional water sources to improve the utilization efficiency of water resources;③ multiple algorithms and statistical methods are used to analyze the time series of water use data,and thus this study realizes the analysis of pipeline network leakage and damage,identification of water use anomalies,and water-saving statistical analysis,and the investigation of water use laws;④ the platform with functions of monitoring and early warning is established to achieve real-time remote monitoring of water use,statistical analysis of historical water use,and identification and warning of pipe network leakage,so as to detect water anomalies in time and save water.The research results are first applied to the construction of the water-saving institution of the Pearl River Water Resources Commission to build a benchmark for the construction of water-saving institutions in the southern region.On the basis of application experience,the comprehensively integrated monitoring technology for water-saving in public institutions is developed,which provides a new idea for public institutions to save water.…”
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Evaluating Ecological Vulnerability and Its Driving Mechanisms in the Dongting Lake Region from a Multi-Method Integrated Perspective: Based on Geodetector and Explainable Machine... by Fuchao Li, Tian Nan, Huang Zhang, Kun Luo, Kui Xiang, Yi Peng

“…Furthermore, the LightGBM algorithm was used for feature optimization, followed by the construction of six machine learning models—Multilayer Perceptron (MLP), Extremely Randomized Trees (ET), Decision Tree (DT), Random Forest (RF), LightGBM, and K-Nearest Neighbors (KNN)—to conduct multi-class classification of ecological vulnerability. …”
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Assessment of flood vulnerability in a coastal metropolitan city for sustainable environmental using machine learning methods by Rana Alabdan, C. Sharmila, Nuha Alruwais, Haya Mesfer Alshahrani, S. Anbukkarasi, M. Sujatha, S. Vivek

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