COMPUTER MODELLING METHODS FOR PREDICTING PERFORMANCE OF CATHODE MATERIALS FOR LITHIUM-ION BATTERIES by M.Yu.. Arsent'ev, P.A. Tikhonov, M.V. Kalinina, T.L. Egorova, A.V. Shmigel

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Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction by GUO Li-jin, WU Hao-tian

Subjects: “…water quality prediction|ceemdan decomposition|fuzzy dispersion entropy|mantis search algorithm|hybrid model…”
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Evapotranspiration Prediction Method Based on K-Means Clustering and QPSO-MKELM Model by Chuansheng Zhang, Minglai Yang

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Bearing Degradation Process Prediction Based on the Support Vector Machine and Markov Model by Shaojiang Dong, Shirong Yin, Baoping Tang, Lili Chen, Tianhong Luo

“…After the bearing degradation process is predicted by SVM model, the Markov model is used to improve the prediction accuracy. …”
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PREDICTION STAGES OF THE DIFFICULT INERTIA SYSTEM BEHAVIOR WITH THE USE OF THE DEVELOPED SYSTEM MODEL by Vasyl V. Bychenkov

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Prediction of power grid fault repair time based on multi-model fusion by Jianyue PAN, Yizhen WU, Hanlin XU

“…There are many types of power grid faults,and the reasons are complicated.The prediction of fault repair time is difficult.Due to the rise of new technologies such as deep learning,it is feasible to accurately mine the faulty worksheet and accurately predict the fault repair time.Taking the historical grid fault repair worksheet as the research object,the multi-model fusion prediction method was proposed,and the prediction results of LightGBM,XGBoost and LSTM were weighted and fused.The experimental results show that the multi-model fusion prediction method can accurately estimate the fault repair time and provide better support for the automation and intelligence of grid fault repair.…”
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Large language model trained on clinical oncology data predicts cancer progression by Menglei Zhu, Hui Lin, Jue Jiang, Abbas J. Jinia, Justin Jee, Karl Pichotta, Michele Waters, Doori Rose, Nikolaus Schultz, Sulov Chalise, Lohit Valleru, Olivier Morin, Jean Moran, Joseph O. Deasy, Shirin Pilai, Chelsea Nichols, Gregory Riely, Lior Z. Braunstein, Anyi Li

“…Analyzing 39,319 radiology impression notes from 4002 patients, it achieved an overall area under the receiver operating characteristic curve (AUROC) of 0.97 for cancer progression prediction on MSK data, including a notable 0.98 AUROC for pancreatic cancer. …”
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AI Knows You: Deep Learning Model for Prediction of Extroversion Personality Trait by Anam Naz, Hikmat Ullah Khan, Sami Alesawi, Omar Ibrahim Abouola, Ali Daud, Muhammad Ramzan

“…The state-of-the-art shallow machine learning, ensemble modelling and deep learning models are applied. The main novelty is the exploration of latest sentence embeddings which captures semantic information of content in a better manner. …”
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PREDICT LEARNERS’ PERFORMANCE USING AN ONTOLOGICAL-BASED MODEL ON AN E-LEARNING PLATFORM by Safa Ridha Albo Abdullah

“…In learning analytics and educational data mining, a prominent challenge is posed by the lack of portability and transferability of predictive models across different courses. A novel ontology-based decision tree model is introduced in this study, which significantly enhances portability by incorporating semantic features. …”
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Thermal Performance of Lightweight Earth: From Prediction to Optimization through Multiscale Modeling by Séverine Rosa Latapie, Vincent Sabathier, Ariane Abou-Chakra

“…Mean-field homogenization techniques, including the Mori-Tanaka as well as double inclusion models, are used to develop predictive tools for thermal behavior, using rigorously selected experimental data. …”
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A Robust Hybrid CNN–LSTM Model for Predicting Student Academic Performance by Kuburat Oyeranti Adefemi, Murimo Bethel Mutanga

“…However, many existing models struggle with generalizability and fail to effectively manage data challenges such as class imbalance and missing data, leading to suboptimal predictive performance. …”
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Predicting the Evolution of Shallow Cumulus Clouds With a Lotka‐Volterra Like Model by Jingyi Chen, Samson Hagos, Jerome Fast, Zhe Feng

“…Abstract In numerical weather prediction and climate models, boundary‐layer clouds are controlled by a wide range of subgrid‐scale processes. …”
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Construction of a disease risk prediction model for postherpetic pruritus by machine learning by Zheng Lin, Yuan Dou, Ru-yi Ju, Ping Lin, Yi Cao

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Risk prediction model for waitlist mortality in patients with left ventricular assist devices by Anjan Tibrewala, MD, MS, Duc Thinh Pham, MD, Mo Hu, MS, Lucia C. Petito, PhD, Jonathan D. Rich, MD, Finn Gustafsson, MD, PhD, Theo M.M.H. de By, MBA, PhD, Kevin Veen, MD, PhD, Donald M. Lloyd-Jones, MD, ScM, Sanjiv J. Shah, MD

“…We sought to derive and validate a risk prediction model for waitlist mortality in LVAD patients. …”
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Numerically predicting deflections of mat-sand interaction model under gravity loadings by Md. Foisal Haque, Nure Ashraf, Jahidul Islam Chalkder, Abu Salem Musa

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Time series analysis for modeling and predicting confirmed cases of influenza a in Algeria by Djillali Seba, N. Benaklef, K. Belaide

“…This study employed a comprehensive approach to develop a model for predicting confirmed cases of Influenza A in Algeria. …”
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Rainfall‐Runoff Modeling in Rocky Headwater Catchments for the Prediction of Debris Flow Occurrence by Martino Bernard, Matteo Barbini, Matteo Berti, Mauro Boreggio, Alessandro Simoni, Carlo Gregoretti

“…These findings suggest that a well‐tuned hydrological model can predict the discharge from intense, short rainfall events that typically trigger debris flows, as well as the early stages of these phenomena.…”
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Prediction Model of Interval Grey Numbers with a Real Parameter and Its Application by Bo Zeng, Chuan Li, Xue-Yu Zhou, Xian-Jun Long

“…Grey prediction models have become common methods which are widely employed to solve the problems with “small examples and poor information.” …”
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A Bitcoin price prediction model assuming oscillatory growth and lengthening cycles by Guizhou Wang, Kjell Hausken

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AKI prediction model in acute aortic dissection surgery: nomogram development and validation by Rui Du, Lai Wang, Yan Wang, Zhitao Zhao, Dahong Zhang, Shanshan Zuo

“…ObjectivesThis multicenter study developed and internally validated a biomarker-enhanced risk prediction nomogram integrating hemodynamic parameters and novel urinary biomarkers to stratify postoperative acute kidney injury (AKI) risks in patients undergoing emergency surgical repair for acute Stanford Type A aortic dissection (ATAAD).MethodsA cohort of 1,277 patients from the China Aortic Dissection Alliance (CADA) registry was chronologically split into derivation (70%, n = 894) and validation (30%, n = 383) sets. …”
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