A Dendritic Neural Network-Based Model for Residential Electricity Consumption Prediction by Ting Jin, Rui Xu, Kunqi Su, Jinrui Gao

“…In this study, a dendritic neural network-based model (DNM), combined with the AdaMax optimization algorithm, is used to predict residential electricity consumption. …”
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Deep Learning Shield Attitude Prediction Model Based on Grey Correlation Analysis by Ke MAN, Zongxu LIU, Yan SHANG, Zhifei SONG, Xiaoli LIU, Bao SU

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Urban Wastewater utilization Potential Prediction Modeling Based on Blind-number Theory by HE Xinchun, SHAO Donggua, LI Jie

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Prediction of loess collapsibility coefficient using bayesian optimized random forest model by Wan Zhang, Jiangtao Guo, Zhaopeng Li, Ruifang Cheng, Cuiping Ning, Hongfeng Niu, Ze Liu

“…These findings indicate that the proposed model is capable of reliably predicting the collapsibility coefficient of loess.…”
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Safety Prejudging Method for Power Transformer Based on Multi-Prediction Model Fusion by Dianyang LI, Yujie ZHANG, Shanyuan WANG, Jian FENG, Hongzhe WANG, Ling QIN

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Variational autoencoder-based model improves polygenic prediction in blood cell traits by Xiaoqi Li, Elena Kharitonova, Minxing Pang, Jia Wen, Laura Y. Zhou, Laura Raffield, Haibo Zhou, Huaxiu Yao, Can Chen, Yun Li, Quan Sun

“…Polygenic risk scores (PRSs) offer a way to aggregate information across the genome, enabling personalized risk prediction for complex traits and diseases. However, conventional PRS calculation methods that rely on linear models are limited in their ability to capture complex patterns and interaction effects in high-dimensional genomic data. …”
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Effectiveness of three machine learning models for prediction of daily streamflow and uncertainty assessment by Luka Vinokić, Milan Dotlić, Veljko Prodanović, Slobodan Kolaković, Slobodan P. Simonovic, Milan Stojković

“…This study evaluates three Machine Learning (ML) models—Temporal Kolmogorov-Arnold Networks (TKAN), Long Short-Term Memory (LSTM), and Temporal Convolutional Networks (TCN)—focusing on their capabilities to improve prediction accuracy and efficiency in streamflow forecasting. …”
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Distinct creep regimes of methane hydrates predicted by a monatomic water model by Henrik Andersen Sveinsson, Pinqiang Cao

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Daily Automated Prediction of Delirium Risk in Hospitalized Patients: Model Development and Validation by Kendrick Matthew Shaw, Yu-Ping Shao, Manohar Ghanta, Valdery Moura Junior, Eyal Y Kimchi, Timothy T Houle, Oluwaseun Akeju, Michael Brandon Westover

“…ResultsThe boosted tree model achieved the greatest predictive power, with an area under the receiver operator characteristic curve (AUROC) of 0.92 (95% CI 0.913-9.22), followed by the random forest (AUROC 0.91, 95% CI 0.909-0.918), multilayer perceptron (AUROC 0.86, 95% CI 0.850-0.861), and logistic regression (AUROC 0.85, 95% CI 0.841-0.852). …”
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IGWO-MSVR model for predicting stress in coal seam during drilling process by Jian Tan, Yanfeng Geng, Liangke Xu

“…Furthermore, Back Propagation Neural network model (BP), Spatial Autoregressive model (SAR) and MSVR model were adopted to perform the stress prediction, and the stress prediction accuracy from these models was analyzed. …”
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Calibrated muscle models improve tracking simulations without enhancing gait predictions. by Filippo Maceratesi, Míriam Febrer-Nafría, Josep M Font-Llagunes

“…<h4>Objectives</h4>This study presents two main aims: (i) to assess functionally-calibrated musculoskeletal models (FCMs) in both tracking and predictive simulations of human motion, against non-linearly scaled models (NSMs), and (ii) to examine the effects of three different variations of our baseline functional calibration approach on the results of tracking and predictive simulations.…”
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Comparative Analysis of Deep Learning Models for Stock Price Prediction in the Indian Market by Moumita Barua, Teerath Kumar, Kislay Raj, Arunabha M. Roy

“…This research presents a comparative analysis of various deep learning models—including Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), Gated Recurrent Units (GRU), and Attention LSTM—in predicting stock prices of major companies in the Indian stock market, specifically HDFC, TCS, ICICI, Reliance, and Nifty. …”
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Mammalian piRNA target prediction using a hierarchical attention model by Tianjiao Zhang, Liang Chen, Haibin Zhu, Garry Wong

“…Finally, this model was utilized to predict the targets of all mouse and human piRNAs available in the piRNA database. …”
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Research on Urban Rainfall Runoff Pollution Prediction Model Based on Feature Fusion by Junping Yao, Tianle Sun

“…The neural network algorithm is optimized and trained according to the sample data to obtain the sample features; the sample data are predicted according to the extracted sample features, and the prediction model is generated by using the feature fusion technology for two groups of prediction results to generate the prediction model and realize the water drop prediction. …”
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Validation of a Chemotherapy Toxicity Prediction Model in Older Adults With Cancer in Taiwan by Chieh-Ying Chang MD, Yu-Shin Hung MD, Ming-Chung Kuo MD, Wen-Chi Chou MD, PhD

“…Introduction The Cancer and Aging Research Group (CARG) model predicts chemotherapy-related toxicities in older patients; however, its applicability has not been validated in Taiwanese patients. …”
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Critical Gaps in ARDS Prediction Models: A Call for Clinical Pragmatism [Letter] by Li J

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Comprehensive Performance Assessment of Multi-Neural Ensemble Model for Mortality Prediction in ICU by M. Fathima Begum, Subhashini Narayan

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A Prediction Model Based on the Long Electrode Source for Fault Anomaly in Tunnel by Daiming Hu, Hao Liu, Xiaodong Yang, Mingxin Yue

“…The accuracy of the algorithm is verified by using the long electrode source model. By a lot of numerical simulations, a prediction model of a long electrode source for tunnel detection is firstly proposed. …”
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Improving deceased donor kidney utilization: predicting risk of nonuse with interpretable models by Ruoting Li, Sait Tunç, Osman Y. Özaltın, Matthew J. Ellis

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Cycle-efficient modeling for degradation staging and early life prediction of lithium batteries by Can Wang, Renjie Wang, Jianming Li, Zhuangzhuang Li, Quanqing Yu

“…An effective and time-saving early life prediction model is crucial for rapid battery assessment. …”
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