Application of Mechanistic Models and the Gaussian Process Model to Predict Bacterial Growth on Baby Spinach During Refrigerated Storage by Sriya Sunil, Sarah I. Murphy, Ruixi Chen, Wei Chen, Joseph Guinness, Li-Qun Zhang, Renata Ivanek, Martin Wiedmann

“…Thus, our aim was to compare the performance of mechanistic (M) models and the Gaussian process (GP) model (i.e., an ML approach) for predicting bacterial growth on spinach from a US-based supply chain as well as a China-based supply chain; models were developed using previously published data, as well as new data collected in this study from the China-based supply chain. …”
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Gaussian process modeling and multi-step prediction for time series data in wireless sensor network environmental monitoring by Yan CHEN, Zi-jian WANG, Ze ZHAO, Dong LI, Li CUI

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Efficient prediction of aerodynamic forces in rarefied flow using convolutional neural network based multi-process method by Haifeng Huang, Guobiao Cai, Chuanfeng Wei, Baiyi Zhang, Xiang Cui, Yongjia Zhao, Huiyan Weng, Weizong Wang, Lihui Liu, Bijiao He

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Predicting Academic Quality based on School Culture: Mediating role of Self-system Processes in High School Students by Maryam khastan, Seyed Mahmood Mirzamani Bafghi, Beheshteh Niosha

“…Objective: The primary objective of the ongoing study was to make predictions regarding the academic  quality by analyzing the influence of school culture, considering the mediating role of the self-system's processes of high school students. …”
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Multi-Genotype Rice Yield Prediction Based on Time-Series Remote Sensing Images and Dynamic Process Clustering by Qian Li, Shaoshuai Zhao, Lei Du, Shanjun Luo

“…The goal of this work was to create a stable, high-precision estimate model for the yield prediction of multi-genotype rice combined with dynamic growth processes. …”
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A New Capillary and Adsorption‒Force Model Predicting Hydraulic Conductivity of Soil During Freeze‒thaw Processes by Shufeng Qiao, Rui Ma, Yunquan Wang, Ziyong Sun, Helen Kristine French, Yanxin Wang

“…Abstract Understanding the change in soil hydraulic conductivity with temperature is key to predicting groundwater flow and solute transport in cold regions. …”
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PREDICTION AND CONTROL OF THINNING RATE OF DEFORMATION ZONE THICKNESS IN METAL SHEET SINGLE POINT INCREMENTAL FORMING PROCESS by FAN Yuan, LI Yan, YANG MingShun, YAO ZiMeng, BAI Lang

“…A relatively high accuracy formula to predict the deformation zone thickness is fitted by using the simulation results. the impact of process parameters such as tool diameter,layer step,feeding speed,sheet thickness,forming angle on thinning rate were analyzed respectively. …”
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Intelligent Prediction of the Horizontal Deformation During the Excavation Process Based on Particle Swarm Optimisation and Support Vector Machine by Yu Zhang, Chen Zhang, Zhiduo Zhu, Liu Yang, Hao Tang

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ATT-BLKAN: A Hybrid Deep Learning Model Combining Attention is Used to Enhance Business Process Prediction by Junyi Xu, Xianwen Fang

Subjects: “…Business process prediction…”
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Prediction of thermal conductivity of 93W–Ni–Fe alloys in sintering process based on finite element analysis by YIN Gang, PAN Qian, ZHAO Teng, YIN Haiqing, WANG Yongwei, QU Xuanhui, XIONG Ning

“…The existing thermal conductivity measurement equipment and methods cannot measure the thermal conductivity of refractory metals during high temperature sintering. Based on the prediction model of 93W–Ni–Fe refractory metals with the PixelMapPaint method, the thermal conductivity of 93W–Ni–Fe alloy billets formed by cold isostatic pressing was predicted at different temperatures during the sintering process, and the thermal conductivity was verified by laser flash method. …”
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Wind Tunnel Process Mach Number Prediction Based on Modal, Stage, and Intra-Stages Three-Layer Partitioning by Haixuan Yuan, Jin Guo, Wenshan Yu, Luping Zhao

“…Considering the nonlinearity of the data, a kernel partial least squares prediction model is constructed for the stable process. …”
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Prediction of Al2O3 leaching recovery in the Bayer process using statistical multilinear regresion analysis by Đurić I., Đorđević P., Mihajlović I., Nikolić Đ., Živković Ž.

Subjects: “…prediction…”
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Dog and Guardian Relationships: Application of a Dual-Process Actor–“Partner” Interdependence Model to Predict Regular Walking by Sarah B. E. Hough, Chris A. Graham, Alfred S. Y. Lee, Ryan E. Rhodes

“…This study applied the Actor–Partner Interdependence Model (APIM) to examine how guardians’ and dogs’ dual-process constructs influence walking behaviour. A sample of 127 Canadian dog guardians reported their walking habits, hedonic motivation, and expectations (Time 1) for themselves and their dogs, with follow-up walking behaviour assessed after three weeks (Time 2). …”
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A Novel Mechanism-Equivalence-Based Tweedie Exponential Dispersion Process for Adaptive Degradation Modeling and Life Prediction by Jiayue Wu, Yujie Liu, Han Wang, Xiaobing Ma, Yu Zhao

Subjects: “…Tweedie exponential dispersion process…”
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Predicting the Evolution of Capacity Degradation Histograms of Rechargeable Batteries Under Dynamic Loads via Latent Gaussian Processes by Daocan Wang, Xinggang Li, Jiahuan Lu

“…Accurate prediction of lithium-ion battery capacity degradation under dynamic loads is crucial yet challenging due to limited data availability and high cell-to-cell variability. …”
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Gaussian process modeling and multi-step prediction for time series data in wireless sensor network environmental monitoring by Yan CHEN, Zi-jian WANG, Ze ZHAO, Dong LI, Li CUI

Subjects: “…WSN environmental monitoring;time serie;Gaussian process;multi-step prediction…”
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Machine learning approaches to identify hydrochemical processes and predict drinking water quality for groundwater environment in a metropolis by Zhan Xie, Weiting Liu, Si Chen, Rongwen Yao, Chang Yang, Xingjun Zhang, Junyi Li, Yangshuang Wang, Yunhui Zhang

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Editorial: Application of artificial intelligence-supported process-based climate models to understand the atmosphere/weather patterns and their prediction by Amit Awasthi, Kanhu Charan Pattnayak, Kanhu Charan Pattnayak, Pushp Raj Tiwari

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Prediction of the Effect of Polymer Membrane Composition in a Dry Air Humidification Process via Neural Network Modeling by M. Fakhroleslam, A. Samimi, S.A. Mousavi, R. Rezaei

“…The results showed that the feed- forward neural network models, especially FFGA, were suitable for prediction of the effect of membrane composition and operating conditions on the performance of this type of membrane humidifiers…”
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LEAN-TECHNOLOGIES AS A RESOURCE OF EDUCATION MODERNIZATION by A. R. Groshev, G. E. Karataeva

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