Enhanced Elman Spike neural network optimized with Red Fox optimization algorithm for sugarcane yield grade prediction-Reference-Cited by-同舟云学术

Enhanced Elman Spike neural network optimized with Red Fox optimization algorithm for sugarcane yield grade prediction

Published:2023-07-03 Issue:3 Volume:11 Page:568-582
ISSN:2308-0477
Container-title:Smart Science
language:en
Short-container-title:Smart Science

Author:

Deepanayaki M.¹,Vidyaathulasiraman ²

Affiliation:

1. Research Scholar, Department of Computer Science, Periyar University, Salem, India

2. Assistant Professor and HOD, Department of Computer Science, Government Arts & Science College (W), Barugur, India

Funder

grant from funding agencies in the public

Publisher

Informa UK Limited

Subject

Computational Mathematics,Computer Networks and Communications,Fluid Flow and Transfer Processes,General Engineering,Energy (miscellaneous),Modeling and Simulation,Chemistry (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/23080477.2023.2229173

Reference26 articles.

1. Sugarcane Yield Prediction Through Data Mining and Crop Simulation Models

2. Performance Analysis on Machine Learning Algorithms with Deep Learning Model for Crop Yield Prediction

3. Sugarcane Harvester for In-field Data Collection: State of the Art, Its Applicability and Future Perspectives

4. Fine-scale prediction of biomass and leaf nitrogen content in sugarcane using UAV LiDAR and multispectral imaging

5. An improved workflow for calibration and downscaling of GCM climate forecasts for agricultural applications – A case study on prediction of sugarcane yield in Australia

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