Bangladeshi Agricultural Product Forecasting Approach Using Permutation Driven Machine Learning Algorithm-Reference-Cited by-同舟云学术

Bangladeshi Agricultural Product Forecasting Approach Using Permutation Driven Machine Learning Algorithm

Published:2022-12-26 Issue: Volume: Page:
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Container-title:2022 International Conference on Recent Progresses in Science, Engineering and Technology (ICRPSET)
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Author:

Islam Arfanul¹,Khair Imranul¹,Ifty Rashedul Arefin¹,Hossain Sakawat¹,Arefin Muhammed Nazmul¹,Bin Al Abid Faisal¹

Affiliation:

1. International Islamic University Chittagong,Department of Computer Science and Engineering,Chattogram,Bangladesh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10188498/10188499/10188538.pdf?arnumber=10188538

Reference19 articles.

1. Applying data mining techniques to predict annual yield of major crops and recommend planting different crops in different districts in bangladesh;ahamed;2015 IEEE/ACIS 16th In-ternational Conference on Software Engineering Artificial Intelligence Networking and Parallel/Distributed Computing (SNPD),2015

2. Predicting rice yield for Bangladesh by exploiting weather conditions

3. An efficient crop yield prediction system using machine learning algorithm

4. Crop Yield Estimation in India Using Machine Learning

5. Impact of Machine Learning Techniques in Precision Agriculture

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