Results 21 to 30 of about 17,286,028 (305)

Soybean Price Prediction Based on Random Forest Model [PDF]

ITM Web of Conferences
Accurate soybean price prediction is critical for stabilizing the global food supply chain. However, traditional forecasting methods struggle to capture the multidimensional, nonlinear characteristics of soybean prices and often overlook time lag effects.
Cai Ling
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Heatwave Damage Prediction Using Random Forest Model in Korea

Applied Sciences, 2020
Climate change increases the frequency and intensity of heatwaves, causing significant human and material losses every year. Big data, whose volumes are rapidly increasing, are expected to be used for preemptive responses.
Minsoo Park, Daekyo Jung, Seungsoo Lee, Seunghee Park   +3 more
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Application of Machine Learning and Process-Based Models for Rainfall-Runoff Simulation in DuPage River Basin, Illinois

Hydrology, 2022
Rainfall-runoff simulation is vital for planning and controlling flood control events. Hydrology modeling using Hydrological Engineering Center—Hydrologic Modeling System (HEC-HMS) is accepted globally for event-based or continuous simulation of the ...
Amrit Bhusal, Utsav Parajuli, Sushmita Regmi, Ajay Kalra   +3 more
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DATA MINING USING RANDOM FOREST, NAÏVE BAYES, AND ADABOOST MODELS FOR PREDICTION AND CLASSIFICATION OF BENIGN AND MALIGNANT BREAST CANCER

Pilar Nusa Mandiri, 2022
This study predicts and classifies benign and malignant breast cancer using 3 classification models. The method used in this research is Random Forest, Naïve Bayes and AdaBoost.
Bahtiar Imran, Hambali Hambali, Ahmad Subki, Zaeniah Zaeniah, Ahmad Yani, Muhammad Rijal Alfian   +5 more
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Random Forest Based Prediction Model

, 2023
Random Forest Based Prediction ...
Hasan Zulfiqar (11942393)
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A Random Forest Model for Predicting Social Functional Improvement in Chinese Patients with Schizophrenia After 3 Months of Atypical Antipsychotic Monopharmacy: A Cohort Study

Neuropsychiatric Disease and Treatment, 2021
Yange Li,1 Lei Zhang,1 Yan Zhang,1 Hui Wen,1 Jingjing Huang,1,2 Yifeng Shen,1– 3 Huafang Li1– 3 1Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 2Shanghai Key Laboratory of ...
Li Y, Zhang L, Zhang Y, Wen H, Huang J, Shen Y, Li H   +6 more
doaj  

Classification results of the random forest model.

, 2022
Classification results of the random forest model.
Sophia Hsin-Jung Li (9317012), Zemer Gitai (204500), Ned S. Wingreen (9027878), Di Zhang (197959), Christopher G. King (9317015), Zhiyuan Li (205620)   +5 more
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Random Forest Model of Ultralow‐Frequency Magnetospheric Wave Power

Earth and Space Science, 2020
Models of magnetospheric ultralow‐frequency (ULF) waves can be used to study wave phenomena and to calculate the effect of these waves on the energization and transport of radiation belt electrons.
S. N. Bentley, J. R. Stout, T. E. Bloch, C. E. J. Watt   +3 more
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Prediction of arrhythmia after intervention in children with atrial septal defect based on random forest

BMC Pediatrics, 2021
Background Using random forest to predict arrhythmia after intervention in children with atrial septal defect. Methods We constructed a prediction model of complications after interventional closure for children with atrial septal defect.
Hongxiao Sun, Yuhai Liu, Bo Song, Xiaowen Cui, Gang Luo, Silin Pan   +5 more
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Random Forest as a Model for Czech Forecasting [PDF]

Prague Economic Papers, 2021
Random forest models have recently gained popularity for economic forecasting. Earlier studies demonstrated their potential to provide early warnings of recession and serve as a competitive method to older prediction models. This study offers the first evaluation of the random forest forecast for the Czech economy.
openaire   +1 more source