Predicting sensory evaluation of spinach freshness using machine learning model and digital images. by Kento Koyama, Marin Tanaka, Byeong-Hyo Cho, Yusaku Yoshikawa, Shige Koseki

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A stacked ensemble model for traffic conflict prediction using emerging sensor data by Bowen Cai, Léah Camarcat, Nicolette Formosa, Mohammed Quddus

“…This model integrates a Random Forest (RF), three-layer Deep Neural Networks (DNN), Support Vector Machine Radial (SVM-R), and a Gradient Boosting Model (GBM) meta layer to enhance prediction accuracy. The Recursive Feature Elimination (RFE) algorithm is then employed to identify the most influential SSMs for conflict prediction in each scenario. …”
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Capturing the Characteristics of Car-Sharing Users: Data-Driven Analysis and Prediction Based on Classification by Jun Bi, Ru Zhi, Dong-Fan Xie, Xiao-Mei Zhao, Jun Zhang

“…We also propose a model that predicts the driver cluster based on the decision tree. …”
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Enhancing Cloud Job Failure Prediction With a Novel Multilayer Voting-Based Framework by Ahmed Elkaradawy, Ayman Elshenawy, Hany Harb

“…In modern cloud data centers, accurately predicting job failures before they occur is essential for ensuring system reliability, availability, and efficiency. …”
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Oilfield Production Prediction Method Based on Multi-Input CNN-LSTM With Attention Mechanism by Lihui Tang, Zhenpeng Wang, Yajun Gao, Hao Wu, Wenbo Zhang, Xiaoqing Xie

“…Oil production prediction is crucial for the formulation of adjustment strategies, enhancement of recovery rates, and guidance of production in oilfields. …”
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Biochemical Oxygen Demand Prediction Based on Three-Dimensional Fluorescence Spectroscopy and Machine Learning by Xu Zhang, Yihao Zhang, Xuanyi Yang, Zhiyun Wang, Xianhua Liu

“…The aim of this study was to propose a facile method for predicting biochemical oxygen demand by fluorescence signals using three-dimensional fluorescence spectroscopy and parallel factor analysis in combination with a machine learning algorithm. …”
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Radiodosiomics Prediction of Treatment Failures Prior to Chemoradiotherapy in Head-and-Neck Squamous Cell Carcinoma by Hidemi Kamezawa, Hidetaka Arimura

“…Moreover, deep (<i>D</i>) features were extracted from a deep learning-based prediction model. The Coxnet algorithm was employed to select significant features. …”
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PINN-Based Method for Predicting Flow Field Distribution of the Tight Reservoir after Fracturing by Jun Pu, Wenfang Song, Junlai Wu, Feifei Gou, Xia Yin, Yunqian Long

“…This study confirms that the adopted PINN model can provide algorithmic support for the accurate prediction of flow field distribution of the tight reservoirs.…”
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Remaining Useful Life Prediction of Rolling Bearings Based on Policy Gradient Informer Model by Jiahao XIONG, Feng LI, Baoping TANG, Yongchao WANG, Ling LUO

“…As a typical encoder–decoder, the transformer architecture has inherent limitations such as secondary time complexity, high memory usage, and a complex model structure; these issues can lead to lower prediction accuracy and decreased computational efficiency when applied to the prediction of the remaining useful life (RUL) of rolling bearings. …”
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Analyzing Momentum Shifts in Tennis: A Machine-Learning Approach to Predicting Match Outcomes by Yuean Xia, Changfeng Li, Tanran Zhang

“…Factor analysis identified key independent variables, while a decision-tree model optimized through random-forest and genetic algorithm techniques was employed to predict match outcomes. …”
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A Model‐Independent Strategy for the Targeted Observation Analysis and Its Application in ENSO Prediction by Weixun Rao, Youmin Tang, Yanling Wu, Xiaojing Li

“…This newly developed model‐independent strategy makes it feasible to design a robust oceanic observational network for ENSO prediction even using the current targeted observational algorithm, well serving the goal of international Tropical Pacific Observation System 2020 project.…”
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Development and application of advanced learning models for predicting the land subsidence due to coal mining by Shirin Jahanmiri, Majid Noorian-Bidgoli

“…This study leverages advanced machine learning techniques to enhance subsidence prediction accuracy and inform sustainable mining practices. …”
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InvarNet: Molecular property prediction via rotation invariant graph neural networks by Danyan Chen, Gaoxiang Duan, Dengbao Miao, Xiaoying Zheng, Yongxin Zhu

“…Predicting molecular properties is crucial in drug synthesis and screening, but traditional molecular dynamics methods are time-consuming and costly. …”
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Life Prediction Modeling Based on FOA and Interface Shapes Simulation Applicability Analysis of TBCs by Xiao Hu, Jing Tian, Yanting Ai, Yudong Yao, Tiannan Bao, Peng Guan

“…Based on the TBCs thermal fatigue experiment, a finite element model is established and combined with the Fruit Fly Optimization Algorithm (FOA), a TBCs life prediction model is established. …”
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Nodal Carbon Emission Factor Prediction for Power Systems Based on MDBO-CNN-LSTM by Lihua Zhong, Feng Pan, Yuyao Yang, Lei Feng, Haiming Shao, Jiafu Wang

“…In this study, we address these limitations by improving population initialization, search mechanisms, and iteration strategies and developing a hybrid strategy Modified Dung Beetle Optimization (MDBO) algorithm. This led to the development of an MDBO-enhanced Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) network hybrid prediction model for carbon emission prediction. …”
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TBM Enclosure Rock Grade Prediction Method Based on Multi-Source Feature Fusion by Yong Huang, Xiewen Hu, Shilong Pang, Wei Fu, Shuaipeng Chang, Bin Gao, Weihua Hua

“…Aiming to mitigate engineering risks such as tunnel face collapse and equipment jamming caused by poor geological conditions during the construction of tunnel boring machines (TBMs), this study proposes a TBM surrounding rock grade prediction method based on multi-source feature fusion. …”
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CNN-LSTM-Attention with PSO optimization for temperature and fault prediction in meat grinder motors by Yao Zhang, Pengfei Zhang, Wenchao Zhang, Mingwei Wang

“…Abstract Meat grinders are essential in meat production, and predicting the working parameters of the meat grinder motors can help prevent potential failures by providing timely warnings. …”
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Creep behavior of clayey soil and its model prediction in the Cangzhou land subsidence area by Jianfeng Qi, Yongjie Xie, Chen Li, Haipeng Guo, Yunlong Wang

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Rice Yield Prediction Based on Simulation Zone Partitioning and Dual-Variable Hierarchical Assimilation by Jiaoyang He, Yanxi Zhao, Ping He, Minglei Yu, Yan Zhu, Weixing Cao, Xiaohu Zhang, Yongchao Tian

“…Data assimilation can be used to predict crop yield by coupling remote sensing information with the crop growth model, but it often grapples with the challenge of enhancing the computational efficiency for the integrated model. …”
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Data-Driven Battery Remaining Life Prediction Based on ResNet with GA Optimization by Jixiang Zhou, Weijian Huang, Haiyan Dai, Chuang Wang, Yuhua Zhong

“…To this end, this paper proposes a data-driven lithium-ion battery life prediction method based on residual network (ResNet) and genetic algorithm (GA) optimization, which is designed to screen the features of the lithium-ion battery training data in order to effectively reduce the redundant features and improve the prediction performance of the model. …”
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