Machine Learning Approaches to Predict Rice Yield of Bangladesh-Reference-Cited by-同舟云学术

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Machine Learning Approaches to Predict Rice Yield of Bangladesh

Published:2022-02-26 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Innovations in Science, Engineering and Technology (ICISET)
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Author:

Rahman Tasnia¹,Aktar Sakifa²

Affiliation:

1. Rajshahi University of Engineering and Technology,Department of Computer Science and Engineering,Rajshahi,Bangladesh,6204

2. Bangabandhu Sheikh Mujibur Rahman Science and Technology University,Department of Computer Science and Engineering,Gopalganj,Bangladesh,8100

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9775773/9775774/09775835.pdf?arnumber=9775835

Reference16 articles.

1. Linear regression;gareth;An Introduction to Statistical Learning,2021

2. Polynomial regression as an alternative to neural nets;xi;arXiv preprint arXiv 1806 06850,2018

3. Support vector regression;fan;Machine Learning,2020

4. Analysis of the mean absolute error (MAE) and the root mean square error (RMSE) in assessing rounding model;weijie;IOP Conference Series: Materials Science and Engineering,2018

5. Root mean square error (RMSE) or mean absolute error (MAE)?;chai,2014

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Zone-II & III: Machine Learning based Rice Yield Prediction in Andhra Pradesh;MATEC Web of Conferences;2024

2. Forecasting Rice Production in Indonesia using Regression Techniques: A Comparative Analysis of Support Vector Machine, Linear Regression, and XGBoost Regression;2023 10th International Conference on ICT for Smart Society (ICISS);2023-09-06

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