A machine learning model for hub-height short-term wind speed prediction by Zongwei Zhang, Lianlei Lin, Sheng Gao, Junkai Wang, Hanqing Zhao, Hangyi Yu

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Self-Adaptive Secondary Frequency Regulation Strategy Based on Distributed Model Predictive Control by CAO Yongji, ZHANG Jiangfeng, WANG Tianyu, ZHENG Keke, WU Qiuwei

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Leveraging pretrained deep protein language model to predict peptide collision cross section by Ayano Nakai-Kasai, Kosuke Ogata, Yasushi Ishihama, Toshiyuki Tanaka

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DINOV2-FCS: a model for fruit leaf disease classification and severity prediction by Chunhui Bai, Chunhui Bai, Chunhui Bai, Lilian Zhang, Lilian Zhang, Lilian Zhang, Lutao Gao, Lutao Gao, Lutao Gao, Lin Peng, Lin Peng, Lin Peng, Peishan Li, Peishan Li, Peishan Li, Linnan Yang, Linnan Yang, Linnan Yang

“…However, the current prediction of disease degree by machine learning methods still faces challenges, including suboptimal accuracy and limited generalizability.MethodsIn light of the growing application of large model technology across a range of fields, this study draws upon the DINOV2 visual large vision model backbone network to construct the DINOV2-Fruit Leaf Classification and Segmentation Model (DINOV2-FCS), a model designed for the classification and severity prediction of diverse fruit leaf diseases. …”
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Multi-task aquatic toxicity prediction model based on multi-level features fusion by Xin Yang, Jianqiang Sun, Bingyu Jin, Yuer Lu, Jinyan Cheng, Jiaju Jiang, Qi Zhao, Jianwei Shuai

“…Objectives: This article presents ATFPGT-multi, an advanced multi-task deep neural network prediction model for organic toxicity. Methods: The model integrates molecular fingerprints and molecule graphs to characterize molecules, enabling the simultaneous prediction of acute toxicity for the same organic compound across four distinct fish species. …”
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A Comparative Study of Drug Prediction Models using KNN, SVM, and Random Forest by Susi Eva Maria Purba

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A predictive model for calculating the likelihood of recurrent uterine fibroids after surgical intervention by V. B. Tskhay, S. Zh. Badmaeva, A. N. Narkevich, I. I. Tskhay, A. V. Mikhaylova

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Predictive modeling of longitudinal cracking in CRCP using PSO-tuned gradient boosting machines by Ali Alnaqbi, Ghazi G. Al-Khateeb, Waleed Zeiada

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Predicting young Chinese consumers' intentions to purchase Western brands: Structural model analysis. by Fei Long, Miraj Ahmed Bhuiyan, Norzalita Abd Aziz, Muhammad Khalilur Rahman

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Deep learning models to predict CO2 solubility in imidazolium-based ionic liquids by Amir Hossein Sheikhshoaei, Ali Sanati, Ali Khoshsima

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Predictive modeling of MB adsorption on activated olive stone through artificial neural networks by Özgül Çimen Mesutoğlu

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Predictive Modeling of Textile Heat Sinks for Enhanced Thermal Management in Space and Military Applications by Michal Frydrysiak, Piotr Kosobudzki

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Analysis of Risk Factors and the Establishment of a Predictive Model for Thrombosis in Patients with Immune Thrombocytopenia by Hui Liang MD, Lingxue Duan BSc, Manyu Long BSc, Songyuan Tie BSc, Changyan Sun BSc, Sha Ma PhD, Jing Wang PhD, Shuya Wang BSc

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Collective predictive coding as model of science: formalizing scientific activities towards generative science by Tadahiro Taniguchi, Shiro Takagi, Jun Otsuka, Yusuke Hayashi, Hiro Taiyo Hamada

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NOx Emission Prediction of Waste Gas Based on the Grey Self-memory Bernoulli Model by GUO Xiaojun; ZHANG Rui; SHEN Houxue; YOU Dan

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Ascites complications risk factors of decompensated cirrhosis patients: logistic regression and prediction model by Xiaolong Zheng, Wei Wei

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Using nonlinear model predictive control to find optimal therapeutic strategies to modulate inflammation by Judy Day, Jonathan Rubin, Gilles Clermont

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Monitoring and predicting cotton leaf diseases using deep learning approaches and mathematical models by Abdul Rehman, Nadeem Akhtar, Omar H. Alhazmi

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WoFSCast: A Machine Learning Model for Predicting Thunderstorms at Watch‐to‐Warning Scales by Montgomery L. Flora, Corey Potvin

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Development and Evaluation of Neural Network Architectures for Model Predictive Control of Building Thermal Systems by Jevgenijs Telicko, Andris Krumins, Agris Nikitenko

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