Wind speed forecasting approach using conformal prediction and feature importance selection by Cesar Vinicius Zuege, Stefano Frizzo Stefenon, Cristina Keiko Yamaguchi, Viviana Cocco Mariani, Gabriel Villarrubia Gonzalez, Leandro dos Santos Coelho

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Prediction of moisture content of hummus peach based on multi-burr hyperspectral data by GAO Aidi, QIAO Fengzhang, ZHU Wenxuan, ZHONG Xiaopin, DENG Yuanlong

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Numerical Prediction of Chloride Penetration in Concrete Exposed to a Marine Environment at Tide by Sung In Hong, Ki Yong Ann

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Support Vector Machine and Granular Computing Based Time Series Volatility Prediction by Yuan Yang, Xu Ma

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Predicting Coronary Heart Disease Using Data Mining and Machine Learning Solutions by VIJAI M. MOORTHY, BHUPAL N. DHARAMSOTH, VIJAYALAKSHMI MUTHUKARUPPAN, ARUL ELANGO, KALAIARASI GANESAN

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Hourly and Day Ahead Power Prediction of Building Integrated Semitransparent Photovoltaic System by S. Kaliappan, R. Saravanakumar, Alagar Karthick, P. Marish Kumar, V. Venkatesh, V. Mohanavel, S. Rajkumar

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Prediction of Total Organic Carbon Content in Shale Based on PCA-PSO-XGBoost by Yingjie Meng, Chengwu Xu, Tingting Li, Tianyong Liu, Lu Tang, Jinyou Zhang

“…The four principal components were also identified as input features through PCA processing. The XGBoost prediction model, established after selecting the parameters through PSO intelligence, had the highest accuracy with an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> and RMSE of 0.90 and 0.1545, respectively, which are superior to the values of the other models. …”
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Mine microseismic signal denoising method and application based on Adaboost_LSTM prediction by Xueyi SHANG, Yong CHEN, Jie CHEN, Linlin CHEN, Yuanyuan PU

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Assessing the impact on quality of prediction and inference from balancing in multilevel logistic regression by Carolina Gonzalez-Canas, Gustavo A. Valencia-Zapata, Ana Maria Estrada Gomez, Zachary Hass

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Hybrid sequence learning with interpretability for multi-class quality prediction in injection molding by Varathorn Punyangarm, Supatchaya Chotayakul

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Intelligent prediction for face straightness based on sensor data and human operation information by SUN Yan, FU Xiang, WANG Ranfeng, JIA Yifan, ZHANG Zhixing

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A web-based machine learning framework for building energy efficiency prediction by B.S.S.V. Ramana, S. Chanikya Kumar, N. Bharath Kumar, Attuluri R. Vijay Babu

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Prediction of Prognosis in Patients with Hepatocellular Carcinoma Based on Molecular Subtypes of Immune Genes by Suming Du, Jinhui Xu, Jiajia Shen, Xiaojin Zhang, Huanzhang Hu, Xinghua Huang

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Classification of Muscle Invasive Bladder Cancer to Predict Prognosis of Patients Treated with Immunotherapy by Zhifeng Wang, Xiqing Li, Xiaoqing Wang, Jie Liu, Lingdian Wang, Wei Wei, Xiaoyu Duan, Degang Ding

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Predicting Mortality in Hospitalized COVID-19 Patients in Zambia: An Application of Machine Learning by Clyde Mulenga, Patrick Kaonga, Raymond Hamoonga, Mazyanga Lucy Mazaba, Freeman Chabala, Patrick Musonda

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Bridging the gap: A comparative analysis of traditional and neural network regression methods for predicting university entrant performance in SUAST examination by Nikka A. Singh, Diether C. Montejo

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Lightweight joint source-channel coding method based on MIMO-CSI prediction by YU Chuangyu, XU Yanyan, PAN Shaoming

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Predicting BRAF Mutations in Cutaneous Melanoma Patients Using Neural Network Analysis by Oleksandr Dudin, Ozar Mintser, Vitalii Gurianov, Nazarii Kobyliak, Dmytro Kaminskyi, Alina Matvieieva, Roman Shabalkov, Artem Mashukov, Oksana Sulaieva

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Prediction and Assessment of Myocardial Infarction Risk on the Base of Medical Report Text Collection by Margaryta Prazdnikova

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Predicting the shield effectiveness of carbon fiber reinforced mortars utilizing metaheuristic algorithms by Mana Alyami, Irfan Ullah, Furqan Ahmad, Hisham Alabduljabbar

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