Closure to “Evaluating the Performance of Self-Organizing Maps to Estimate Well-Watered Canopy Temperature for Calculating Crop Water Stress Index in Indian Mustard ( <i>Brassica juncea</i> )” by Navsal Kumar, Vijay Shankar, Rabee Rustum, and Adebayo J. Adeloye-Reference-Cited by-同舟云学术

Closure to “Evaluating the Performance of Self-Organizing Maps to Estimate Well-Watered Canopy Temperature for Calculating Crop Water Stress Index in Indian Mustard ( Brassica juncea )” by Navsal Kumar, Vijay Shankar, Rabee Rustum, and Adebayo J. Adeloye

Published:2022-08 Issue:8 Volume:148 Page:
ISSN:0733-9437
Container-title:Journal of Irrigation and Drainage Engineering
language:en
Short-container-title:J. Irrig. Drain Eng.

Author:

Kumar Navsal¹^ORCID,Shankar Vijay²,Rustum Rabee³^ORCID,Adeloye Adebayo J.⁴

Affiliation:

1. Assistant Professor, School of Mechanical, Civil, and Electrical Engineering, Shoolini Univ., Himachal Pradesh 173229, India (corresponding author). ORCID: .

2. Associate Professor, Dept. of Civil Engineering, National Institute of Technology Hamirpur, Himachal Pradesh 177005, India.

3. Associate Professor, School of Energy, Geoscience, Infrastructure, and Society, Heriot-Watt Univ., Dubai 294345, United Rab Emirates. ORCID: .

4. Professor (Emeritus), School of Energy, Geoscience, Infrastructure, and Society, Heriot-Watt Univ., Edinburgh EH14 4AS, UK.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Agricultural and Biological Sciences (miscellaneous),Water Science and Technology,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29IR.1943-4774.0001693

Reference8 articles.

1. Neural computing modeling of the reference crop evapotranspiration

2. The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation

3. Kreyszig, E., H. Kreyszig, and E. J. Norminton. 2011. Advanced engineering mathematics. 10th ed. New York: Wiley.

4. Statistics for Engineering and the Sciences Student Solutions Manual

5. Application of self-organising maps and multi-layer perceptron-artificial neural networks for streamflow and water level forecasting in data-poor catchments: the case of the Lower Shire floodplain, Malawi