An Ensemble Machine Learning Framework for Cotton Crop Yield Prediction Using Weather Parameters: A Case Study of Pakistan-Reference-Cited by-同舟云学术

An Ensemble Machine Learning Framework for Cotton Crop Yield Prediction Using Weather Parameters: A Case Study of Pakistan

Published:2024 Issue: Volume:12 Page:124045-124061
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Haider Syed Tahseen¹^ORCID,Ge Wenping²,Li Jianqiang¹^ORCID,Rehman Saif Ur³^ORCID,Imran Azhar⁴^ORCID,Sharaf Mohamed Abdel Fattah⁵^ORCID,Haider Syed Muhammad³^ORCID

Affiliation:

1. School of Software Engineering, Beijing University of Technology, Beijing, China

2. School of Computer Science and Technology, Xinjiang University, Ürümqi, Xinjiang, China

3. University Institute of Information Technology, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, Pakistan

4. Faculty of Computing and Artificial Intelligence, Air University, Islamabad, Pakistan

5. Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia

Funder

King Saud University, Riyadh, Saudi Arabia, through the Researchers Supporting Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10664030.pdf?arnumber=10664030

Reference31 articles.

1. Response of maize phenology to climate warming in Northeast China between 1990 and 2012

2. Impact of Climate Smart Agriculture (CSA) Practices on Cotton Production and Livelihood of Farmers in Punjab, Pakistan

3. Determinants and resource use efficiency of “better cotton”: An innovative cleaner production alternative

4. RANDOM FORESTS FOR CLASSIFICATION IN ECOLOGY

5. Impact of Climate Change on Cotton Production in Pakistan: An ARDL Bound Testing Approach