Predictive process monitoring for collaborative business processes: concepts and application by Andrea Delgado, Daniel Calegari, Carolina Espino, Nicolás Ribero

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Damage Prediction in the Wire Drawing Process by Álvaro González, Marcela Cruchaga, Diego Celentano, Jean-Philippe Ponthot

“…In this study, the prediction of damage in the wire drawing process of 2011 aluminum alloy was investigated through both experimental and numerical methods. …”
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Prediction of the risk of recurrence of the leprosy process by G. N. Genatullina, A. L. Yasenyavskaya, A. A. Tsibizova, M. A. Samotrueva

“…The aim of the study was to study the degree of neutrophil granulocyte myeloperoxidase activity in peripheral blood of patients with leprosy in order to predict the possible recurrence of the infectious process.Materials and methods. …”
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Assessment of Information predictability of stochastic processes by A. V. Ausiannikau

“…The necessary theoretical information for parameter estimation algorithms informational predictability of stochastic processes. We consider examples of algorithms for estimating the predictability of information for the processes described by the optimal difference schemes, equivalent prognostic models in the form of stochastic differential equations.…”
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Predictable and non-stationary processes of interval PREDICTION BASED ON stochastic differential equations by A. V. Ausiannikau

“…The task of interval prediction of non-stationary processes of stochastic differential equations described by models is considered. …”
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Karin Kukkonen: Probability Designs: Literature and predictive processing by Petter Aaslestad

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Application of AI-based Predictive Maintenance for Industrial Processes by Marko Fabić

“…Modern industry is increasingly relying on digital technologies to optimize maintenance processes, reduce costs and ultimately increase productivity. …”
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Application of Generalized Predictive Control in Sewage Treatment Process by SONG Guohui

Subjects: “…generalized predictive control…”
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Analysis OF information predictability OF process with random structure by A. V. Ausiannikau, V. M. Kozel, K. A. Kharytovich

Subjects: “…information predictability…”
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Predictions on Pre-cooling Process of Potato Seeds by 孙勇, 陈忠海, 冀卫兴, 曲春民

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Information predictability of stochastic processes in discrete time by A. V. Ausiannikau, V. M. Kozel

“…The definition of one-step information predictability stochastic process in discrete time is given. …”
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Predictability in process-based ensemble forecast of influenza. by Sen Pei, Mark A Cane, Jeffrey Shaman

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Information predictability of stochastic processes in continuous time by A. V. Ausiannikau

“…The definition of information predictability stochastic process and its parameters is given in the article. …”
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PREDICTIVE ASSESSMENT OF TECHNICAL MEANS OF FEED GRAIN PROCESSING FOR LIVESTOCK by Dmitry I. Chistyakov

“…A process model for forming technical-and-economic indices in estimating mechanical equipment for feed grain processing for livestock is offered. …”
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Uncertainty-Aware Predictive Process Monitoring in Healthcare: Explainable Insights into Probability Calibration for Conformal Prediction by Maxim Majlatow, Fahim Ahmed Shakil, Andreas Emrich, Nijat Mehdiyev

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Energy prediction and optimization for robotic stereoscopic statue processing by Xu-Hui Cheng, Fang-Chen Yin, Cong-Wei Wen, Ye Wang, Yi-Hao Li, Ji-Xiang Huang, Shen-Gui Huang

“…Subsequently, the spindle power of the robot is predicted based on the relationship between force and power variations during the grinding process. …”
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Transformer-based latency prediction for stream processing task by Zheng Chu, Baozhu Li, Changtian Ying

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Parametric evaluation and predictive modelling of formability in μ-SPIF process by Sahu Vijay Kumar, Das Purnendu, Adhikary Avishek, Bandyopadhyay Kaushik

“…This study emphasizes the integration of experimental data, process analysis, and predictive modelling as a means of creating a digital twin framework for µ-SPIF.…”
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Earthquake prediction method based on seismogenic process tracking by Xuezhong Chen, Yan’e Li, Lijuan Chen

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The Degradation Process Modeling and Shelf Life Prediction of Drug by ZHOU Zhen, LI Han-bin, QI Jia, MA De-zhong

“…To solve the problem of individual difference in the same batch cannot be considered during the traditional degradation process modeling, an effective method is proposed to fuse priori degenerate data with site degraded data which can predict shelf life for the monolithic drug and new drugs Determining the distribution of model parameters based on prior information, fusion of field data to update parameters by Bayes On this basis, predict the shelf life of the monolithic drug The results show that the No5 loaded and bottled drugs’ shelf life predicted values are 4395 and 4747 weeks The relative errors are 0043 and 0051 And the feasibility of fusing degradation data to predict the shelf life of the monolithic drug and new drugs is verified…”
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