Predictive models for the implementation of targeted reproductive management in multiparous cows on automatic milking systems by Fergus P. Hannon, Martin J. Green, Luke O'Grady, Chris Hudson, Anneke Gouw, Laura V. Randall

“…The utility of this data for the prediction of fertility has not been previously explored. …”
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Risk Factors Predicting Recurrent Small Intestinal Resection for Crohn’s Disease of the Terminal Ileum by Hanna Binder, Hugh J Freeman

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The good, the better and the challenging: Insights into predicting high-growth firms using machine learning by Sermet Pekin, Aykut Şengül

“…This research contributes valuable insights to financial analysts and investors in identifying high-growth firms and underscores the potential of machine learning in economic prediction.…”
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Short-Term Power Load Prediction Method Based on VMD and EDE-BiLSTM by Yibo Lai, Qifeng Wang, Gang Chen, Yu Bai, Peiyu Zhao, Xiaojing Liao, Shuang Wu, Changyou Men, Quan Sun

“…Each modal component is modelled individually, and the final prediction is derived by summing the predicted values of all components. …”
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Predictive performance of oximetry in detecting sleep apnea in surgical patients with cardiovascular risk factors. by Rida Waseem, Matthew T V Chan, Chew Yin Wang, Edwin Seet, Frances Chung

“…There is a need for an easy and accessible home device in predicting sleep apnea. The objective of the study is to determine the predictive performance of the overnight pulse oximetry in predicting OSA in at-risk surgical patients.…”
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Conv‐ELSTM: An ensemble deep learning approach for predicting short‐term wind power by Guibin Wang, Xinlong Huang, Yiqun Li, Hong Wang, Xian Zhang, Jing Qiu

“…However, the chaotic nature of wind power presents a significant challenge in utilizing data for effective short‐term forecasting, such as 60‐min predictions. This article introduces a hybrid data‐driven framework that employs an ensemble deep learning model to provide highly precise short‐term wind power predictions. …”
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Predicting the delisted companies of Tehran Stock Exchange using machine learning based algorithms by Aminollah Zarghami, Meysam Doaei, Abtin Boostani

“…Then, with data mining techniques, which are among the most efficient and up-to-date models of artificial intelligence, and with the help of multi-layered perceptron neural network classifiers, decision tree, and Bayesian theory classifiers, stock delisted companies have been predicted.Findings: The findings show that the Bayesian classifier had the best performance and the multilayer perceptron neural network was in the second place and the decision tree classifier was in the third place.Originality/Value: Little research has been done in the field of predicting delisted companies from the Iran capital market. …”
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Prediction of shallow bit position based on vibration signal monitoring of bit broken rock by Jinping Yu, Deyong Zou

“…Based on the above background, the purpose of this article is to predict the position of shallow bit based on the vibration signal monitoring of bit broken rock. …”
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Spatio-Temporal Segmented Traffic Flow Prediction with ANPRS Data Based on Improved XGBoost by Bo Sun, Tuo Sun, Pengpeng Jiao

“…Traffic prediction is highly significant for intelligent traffic systems and traffic management. eXtreme Gradient Boosting (XGBoost), a scalable tree lifting algorithm, is proposed and improved to predict more high-resolution traffic state by utilizing origin-destination (OD) relationship of segment flow data between upstream and downstream on the highway. …”
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A New Implementable Prediction-Correction Method for Monotone Variational Inequalities with Separable Structure by Feng Ma, Mingfang Ni, Zhanke Yu

“…In this paper, we develop a new prediction-correction method for monotone variational inequalities with separable structure. …”
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Prediction of Soil Moisture-Holding Capacity with Support Vector Machines in Dry Subhumid Tropics by Jacob Kaingo, Siza D. Tumbo, Nganga I. Kihupi, Boniface P. Mbilinyi

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An Integrated Stacking Ensemble Model for Natural Gas Purchase Prediction Incorporating Multiple Features by Junjie Wang, Lei Jiang, Le Zhang, Yaqi Liu, Qihong Yu, Yuheng Bu

Subjects: “…natural gas purchase prediction…”
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Defects and Improvement of Predicting Mine Water Inflow by Virtual Large Diameter Well Method by Zhimin Xu, Tianci Chen, Jianfeng Li, Yajun Sun, Chenghang Zhang, Ge Chen, Yating Gao, Ye He

“…In order to prevent the occurrence of water inrush accidents, it is particularly important to predict the mine water inrush, especially the accurate prediction of the mine water inflow in the coal mining process. …”
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A Novel Cancer Stemness-Related Signature for Predicting Prognosis in Patients with Colon Adenocarcinoma by Wei Wang, Congrong Xu, Yan Ren, Shiwei Wang, Chunli Liao, Xiaoyan Fu, Haixia Hu

“…We developed a cancer stemness-related signature using fifteen genes (including RAB31, COL6A3, COL5A2, CCDC80, ADAM12, VGLL3, ECM2, POSTN, DPYSL3, PCDH7, CRISPLD2, COLEC12, NRP2, ISLR, and CCDC8) for prognosis prediction of COAD. Low-risk score was associated with significantly preferable OS in comparison with high-risk score, and the area under the ROC curve (AUC) for OS prediction was 0.705. …”
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PREDICTING USD/ TL EXCHANGE RATE IN TURKEY: THE LONG-SHORT TERM MEMORY APPROACH by Abdul-razak Bawa Yussif, Fatih Mangır, Zeynep Karaçor, Ayten Yağmur

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Mitigating bias in AI mortality predictions for minority populations: a transfer learning approach by Tianshu Gu, Wensen Pan, Jing Yu, Guang Ji, Xia Meng, Yongjun Wang, Minghui Li

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Numerical Simulations as Tool to Predict Chemical and Radiological Hazardous Diffusion in Case of Nonconventional Events by J.-F. Ciparisse, A. Malizia, L. A. Poggi, O. Cenciarelli, M. Gelfusa, M. C. Carestia, D. Di Giovanni, S. Mancinelli, L. Palombi, C. Bellecci, P. Gaudio

“…CFD (Computational Fluid Dynamics) simulations are widely used nowadays to predict the behaviour of fluids in pure research and in industrial applications. …”
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A Two-Layer Architecture for Failure Prediction Based on High-Dimension Monitoring Sequences by Xue Wang, Fan Liu, Yixin Feng, Jiabao Zhao

“…Experiments are conducted on the data provided by one of the largest security companies, and the results demonstrate the predictability of the proposed approach.…”
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Research on the Prediction Model of the Friction Coefficient of Asphalt Pavement Based on Tire-Pavement Coupling by Miao Yu, Xinquan Xu, Chuanhai Wu, Shanqiang Li, Mingxia Li, Haifeng Chen

“…By integrating the above influence factors, the BP neural network method was applied to the regression of the prediction model for the asphalt pavement friction coefficient. …”
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Comparison of Morphological and Functional MRI Assessments of Periprostatic Fat for Predicting Prostate Cancer Aggressiveness by David Freire Maia Vieira, Cecília Vidal de Souza Torres, André de Freitas Secaf, Matheus de Moraes Palma, Gabriel de Lion Gouvea, Jorge Elias Júnior, Rodolfo Borges Reis, Valdair Muglia

“…ABSTRACT Purpose: The objective of this study was to evaluate whether morphological (linear measurements) and functional (ADC value) assessments of periprostatic fat can predict the aggressiveness of prostate cancer (PCa) over a 5-year follow-up period. …”
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