Supply chain management and optimization in transportation logistics by Saoussen Krichen

“…Generally speaking, a decision-making problem is split into the following three main components:</p><ul><li><em>The decision maker(s).…”
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Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation by Wanli Xiong, Qiqi Cao, Lu Jia, Min Chen, Tao Liu, Qingyan Zhao, Yanhong Tang, Bo Yang, Li Li, Shaobo Shi, He Huang, Congxin Huang, China Atrial Fibrillation Center Project Team

“…LAT incidence was assessed, and potential risk factors were analyzed. Machine learning algorithms, including decision tree, random forest, AdaBoost, k-Nearest Neighbor, and logistic regression, were employed to develop a predictive model for LAT. …”
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Deep reinforcement learning applications and prospects in industrial scenarios by JING TAN, Ligang YANG, Xiaorui LI, Zhaolin YUAN, Yunduan CUI, Chao YAO, Zongjie WANG, Xiaojuan BAN

“…Current research is categorized into three domains: (1) adaptive optimization in dynamic environments, enabling systems to respond to changes such as market fluctuations, equipment degradation, and operational disturbances; (2) decision-making under multi-objective and constrained conditions, with DRL balancing competing goals such as efficiency, cost, and sustainability while adhering to technical constraints; and (3) performance enhancement in complex systems, whereby DRL tackles high-dimensional, nonlinear, and coupled processes to improve stability, scalability, and operational excellence. …”
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Fast sparse representative tree splitting via local density for large-scale clustering by Renmin Wang, Jie Li

“…This paper proposes a novel large-scale clustering framework with three key innovations: (1) Parameter-free cluster discovery: unlike conventional methods requiring predefined cluster numbers, our algorithm autonomously identifies natural cluster structures through dynamic density-based splitting decisions. (2) Hybrid sampling-partitioning strategy: by integrating randomized sampling with K-means-based partitioning, we extract high-quality representative points that preserve data integrity with linear computational complexity. (3) Local density-driven MST segmentation: A minimum spanning tree (MST) constructed from representatives is adaptively partitioned using a local density criterion, which dynamically disconnects weakly associated edges by comparing density peaks between adjacent representative points. …”
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Pandemic velocity: Forecasting COVID-19 in the US with a machine learning & Bayesian time series compartmental model. by Gregory L Watson, Di Xiong, Lu Zhang, Joseph A Zoller, John Shamshoian, Phillip Sundin, Teresa Bufford, Anne W Rimoin, Marc A Suchard, Christina M Ramirez

“…Predictions of COVID-19 case growth and mortality are critical to the decisions of political leaders, businesses, and individuals grappling with the pandemic. …”
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A song for each moment: Identifying listening modes as reflexive practices in music streaming by Sebastian Cole

“…First, the article develops a framework for understanding reflexive decision-making in the context of music streaming. …”
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Explainable Machine Learning to Predict the Construction Cost of Power Plant Based on Random Forest and Shapley Method by Suha Falih Mahdi Alazawy, Mohammed Ali Ahmed, Saja Hadi Raheem, Hamza Imran, Luís Filipe Almeida Bernardo, Hugo Alexandre Silva Pinto

“…This investigation employed the Random Forest (RF) algorithm to estimate the overall construction cost of a power plant. …”
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Game Cross Efficiency for Systems with Two-Stage Structures by Chaoqun Ma, Debin Liu, Zhongbao Zhou, Wei Zhao, Wenbin Liu

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A Long-Term Shared Autonomous Vehicle System Design Problem considering Relocation and Pricing by Jingjing Tian, Hongfei Jia, Guanfeng Wang, Yu Lin, Ruiyi Wu, Ao Lv

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Multi-objective design optimisation of a delta coordinate measurement machine by Louw Jakobus Murray, de Ronde Willis, Marais Stephen, Maweni Thabisa

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Optimization Strategy of Building Energy System Based on Deep Reinforcement Learning by Wenzhe SHI, Bingjie LI, Peipei YOU, Ling ZHANG

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Leveraging haplotype information in heritability estimation and polygenic prediction by Jonas Meisner, Michael Eriksen Benros, Simon Rasmussen

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Task offloading and resource allocation for blockchain‐enabled mobile edge computing by Renbin Fang, Peng Lin, Yize Liu, Yan Liu

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Chemical Characteristics and Quality Assessment of Groundwater of Exploited Aquifers in Beijiao Water Source of Yinchuan, China: A Case Study for Drinking, Irrigation, and Industri... by Hao Wu, Jie Chen, Hui Qian, Xuedi Zhang

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A Novel Fault Diagnosis of Induction Motor by Using Various Soft Computation Techniques: BESO-RDFA by Kapu V. Sri Ram Prasad, K. Dhananjay Rao, Guruvulu Naidu Ponnada, Umit Cali, Taha Selim Ustun

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Link-State-Aware Proactive Data Delivery in Integrated Satellite–Terrestrial Networks for Multi-Modal Remote Sensing by Ranshu Peng, Chunjiang Bian, Shi Chen, Min Wu

“…By integrating satellite cache states, user cache states, and multi-modal data attributes (including imagery, metadata, and temporal request patterns) into a unified Markov decision process (MDP), our approach pioneers the application of the multi-actor-attention-critic with parameter sharing (MAPPO) algorithm to ISTNs push tasks. …”
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Development and validation of a nomogram for predicting cancer-related fatigue in patients with glioma: a multicenter study by Qiuxia Wu, Cuiqun Su, Manxia Xing, Liangmei Ouyang

“…A nomogram was constructed and its predictive accuracy and conformity was validated by ROC curves, calibration curves and decision curve analysis.ResultsCombining LASSO algorithm and multivariable logistic regression analyses, the cancer stage (p=0.014), and the scores of Perceived Social Support Scale (PSSS) (p&lt;0.001), physical functioning (PF) (p&lt;0.001), bodily pain (BP) (p=0.031), general health (GH) (p&lt;0.001), and mental health (MH) (p=0.009) were the independent risk factors for cancer-related fatigue of glioma patients. …”
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A method for the identification of lactate metabolism-related prognostic biomarkers and its validations in non-small cell lung cancer by Weiyang Yang, Miao Gu, Yabin Zhang, Yunfan Zhang, Tao Liu, Di Wu, Juntao Deng, Min Liu, Youwei Zhang

“…We proposed a Cox elastic-net regression combined with genetic algorithm (GA-EnCox) to predict prognosis and optimize the selection of key biomarkers. …”
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A Machine Learning-Based Guide for Repeated Laboratory Testing in Pediatric Emergency Departments by Adi Shuchami, Teddy Lazebnik, Shai Ashkenazi, Avner Herman Cohen, Yael Reichenberg, Vered Shkalim Zemer

“…The minimal decision tree (MDT) algorithm was selected for its interpretability and capacity to generate optimally pruned classification trees. …”
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Predicting ESWL success for ureteral stones: a radiomics-based machine learning approach by Ran Yang, Dan Zhao, Chunxue Ye, Ming Hu, Xiao Qi, Zhichao Li

“…Radiomic features were selected using the least absolute shrinkage and selection operator (LASSO) algorithm to calculate a radiomic score (Rad-score). …”
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