A Graph Representation Learning-Based Method for Event Prediction by Xi Zeng, Guangchun Luo, Ke Qin, Pengyi Zheng

“…However, events typically encompass a myriad of elements and intricate relationships, necessitating an enhancement in the precision of event prediction. However, the existing methods suffer from poor data quality, insufficient feature information, limited generalization capability of the models, and difficulties in evaluating prediction errors. …”
Get full text

Optimal prediction method for CO2 solubility in saline aquifers by DONG Lifei, DONG Wenzhuo, ZHANG Qi, ZHONG Pinzhi, WANG Miao, YU Bo, WEI Haiyu, YANG Chao

“…The predicted values of the grey Markov model were more consistent with the measured data, and the prediction performance of the model was better, so as to provide a new method for predicting the solubility of CO2 in underground salt water.…”
Get full text

A Method of Productivity Prediction for Multi-Fractured Horizontal Well by YANG Fan, GAO Yanwu, SHAO Guanghui, LIU Jieli, XU Rui, ZHOU Jufeng

“…On this basis, the productivity prediction model of horizontal wells is established by using the method of multiple linear regression. …”
Get full text

PREDICTION METHOD FOR ACUTE TRAUMATIC PANCREATITIS IN SHOCK-INDUCING POLYTRAUMA by M. F. Cherkasov, O. L. Degtyarev, A. B. Lageza, K. A. Demin

“…Implementation of the scoring evaluation method to identify the risk of pathology onset based on combinations of risk factors considerably increased informative value of predictions and improved the efficiency of individually tailored preventive measures corresponding to the risk of pancreatopathy in shock-inducing polytrauma cases.The authors declare no conflict of interest.The authors confirm that they respect the rights of the people participated in the study, including obtaining informed consent when it is necessary, and the rules of treatment of animals when they are used in the study. …”
Get full text

Quantitative method for network security situation based on attack prediction by Hao HU, Run-guo YE, Hong-qi ZHANG, Ying-jie YANG, Yu-ling LIU

“…To predict the attack behaviors accurately and comprehensively as well as to quantify the threat of attack,a quantitative method for network security situation based on attack prediction was proposed.By fusing the situation factors of attacker,defender and network environment,the capability of attacker and the exploitability rate of vulnerability were evaluated utilizing the real-time detected attack events,and the expected time-cost for attack-defense were further calculated.Then an attack prediction algorithm based on the dynamic Bayesian attack graph was designed to infer the follow-up attack actions.At last,the attack threat was quantified as the security risk situation from two levels of the hosts and the overall network.Experimental analysis indicates that the proposed method is suitable for the real adversarial network environment,and is able to predict the occurrence time of attack accurately and quantify the attack threat reasonably.…”
Get full text

Quantitative method for network security situation based on attack prediction by Hao HU, Run-guo YE, Hong-qi ZHANG, Ying-jie YANG, Yu-ling LIU

“…To predict the attack behaviors accurately and comprehensively as well as to quantify the threat of attack,a quantitative method for network security situation based on attack prediction was proposed.By fusing the situation factors of attacker,defender and network environment,the capability of attacker and the exploitability rate of vulnerability were evaluated utilizing the real-time detected attack events,and the expected time-cost for attack-defense were further calculated.Then an attack prediction algorithm based on the dynamic Bayesian attack graph was designed to infer the follow-up attack actions.At last,the attack threat was quantified as the security risk situation from two levels of the hosts and the overall network.Experimental analysis indicates that the proposed method is suitable for the real adversarial network environment,and is able to predict the occurrence time of attack accurately and quantify the attack threat reasonably.…”
Get full text

A Hybrid GARCH and Deep Learning Method for Volatility Prediction by Hailabe T. Araya, Jane Aduda, Tesfahun Berhane

“…Volatility prediction plays a vital role in financial data. The time series movements of stock prices are commonly characterized as highly nonlinear and volatile. …”
Get full text

Student Dropout Prediction Using Random Forest and XGBoost Method by Lalu Ganda Rady Putra, Didik Dwi Prasetya, Mayadi Mayadi

“…Objective: This study aims to evaluate the effectiveness of the Random Forest and XGBoost algorithms in predicting student attrition based on demographic, socioeconomic, and academic performance factors. …”
Get full text

Evaluation of predictive maintenance efficiency with the comparison of machine learning models in machining production process in brake industry by Can Aydın, Burak Evrentuğ

“…Methods This study aims to predict machine faults using data analysis methods and enhance the accuracy performance of these predictions for an industrial company that produces braking components. …”
Get full text

Constructing a Predictive Model to Evaluate the Risk of CHD Based on New Metabolic Indicators by Wang W, Du Z, Xie P

“…Wenqiang Wang,1 Zonghan Du,2 Peng Xie3 1Department of Nursing, Beijing Anzhen Nanchong Hospital of Capital Medical University & Nanchong Central Hospital, Nanchong, Sichuan, 637000, People’s Republic of China; 2Department of Gastroenterology, Beijing Anzhen Nanchong Hospital of Capital Medical University & Nanchong Central Hospital, Nanchong, Sichuan, 637000, People’s Republic of China; 3Department of Cardiovascular Medicine, Beijing Anzhen Nanchong Hospital of Capital Medical University & Nanchong Central Hospital, Nanchong, Sichuan, 637000, People’s Republic of ChinaCorrespondence: Peng Xie, Department of Cardiovascular Medicine, Beijing Anzhen Nanchong Hospital of Capital Medical University & Nanchong Central Hospital, Nanchong, Sichuan, 637000, People’s Republic of China, Email billxiewang@163.comObjective: Constructing a predictive model to evaluate the risk of coronary heart disease (CHD) for early identification of patients with CHD risk based on new metabolic indicators.Methods: A retrospective analysis was conducted based on NHANES databases. …”
Get full text

A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…This study presents a comparative analysis of hyper-parameter optimization methods used in developing predictive models for patients at risk of heart failure readmission and mortality. …”
Get full text

Evaluating the Uncertainty and Predictive Performance of Probabilistic Models Devised for Grade Estimation in a Porphyry Copper Deposit by Raymond Leung, Alexander Lowe, Arman Melkumyan

“…One problem is the lack of industry guidelines for evaluating the uncertainty and predictive performance of probabilistic ore grade models. …”
Get full text

Evaluating the Predictive Accuracy of an AI-Based Tool for Postoperative Vault Estimation in Phakic Intraocular Lens Implantation by Zaldivar R, Zaldivar R, Cummings AB, Cummings BK, Mertens EL, Ang RE, Zarate Piscopo LI, Quintero G, Cerviño A

“…The purpose of this study was to evaluate the predictive accuracy of an AI-based tool that integrates high-resolution ultrasound biomicroscopy (UBM) imaging with biometric data, for estimating postoperative vault in myopic patients.Settings: The study was performed at four centers: Instituto Zaldivar (Argentina), Wellington Eye Clinic (Ireland), Medipolis Eye Center (Belgium), and Asian Eye Institute (Philippines).Methods: In this retrospective, multicenter study, 347 eyes from 228 myopic patients (mean age 31.3 ± 7.7 years) underwent ICL implantation. …”
Get full text

Cardiac Clues in Major Depressive Disorder: Evaluating Electrical Risk Score as a Predictive Electrocardiography Biomarker by Ulker Atilan Fedai, Halil Fedai, Zulkif Tanriverdi

Get full text

Evaluating the Predictive Value of HOMA-IR in Gestational Diabetes: A Case–Control Study from Romania by Ait el Haj Iman, Cristina Onel, Gheorghe Furau, Cristian Furau, Roxana Furau, Mihai Lucan, Mircea Sandor, Liliana Sachelarie, Anca Huniadi

“…This study aimed to evaluate the predictive value of the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) in diagnosing GDM and to explore its correlation with clinical and anthropometric parameters in a Romanian population. …”
Get full text

Evaluating IL22RA1 expression as a predictive indicator in human colon cancer progression by Xuan Yin, Renhao Geng, Junjun Chen, Bin Xu, Hui Ma, Yingting Liu, Xiao Zheng, Lujun Chen

Get full text

Using Impact Evaluation Tools to Unpack the Black Box and Learn What Works by Laura R Peck

Get full text

Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model by Kai Cheng, Xiaokang Zhang, Keping Zhou, Chenao Zhou, Jielin Li, Chun Yang, Yurong Guo, Ranfeng Wang

Get full text

Experimental evaluation of an advanced predictive control technique for variable-speed wind turbine systems by Farah Echiheb, Btissam Majout, Ismail EL Kafazi, Badre Bossoufi, Abdelhamid Rabhi, Nicu Bizon, Anton Zhilenkov, Saleh Mobayen

Get full text

Model Predictive Control Strategies Performance Evaluation over a Pipeline Transportation System by Jorge Cardenas-Cabrera, Luis Diaz-Charris, Andrés Torres-Carvajal, Narciso Castro-Charris, Elena Romero-Fandiño, José David Ruiz Ariza, Javier Jiménez-Cabas

Get full text