Brinjal Crop yield prediction using Shuffled shepherd optimization algorithm based ACNN-OBDLSTM model in Smart Agriculture

brinjal crop prediction using modified CNN

Authors

  • M Venkateswara Rao NRI Institute of Technology, Vijayawada
  • Y. Sreeraman The Apollo University
  • Srihari Varma Mantena Sagi Rama Krishnam Raju Engineering College, Bhimavaram
  • Venkateswarlu Gundu Koneru Lakshmaiah Education Foundation
  • D. Roja Chalapathi Institute of Technology, Guntur
  • Ramesh Vatambeti VIT-AP University

Keywords:

Shuffled shepherd optimization algorithm, CNN, Crop yield forecasting, Brinjal Crop prediction, Smart agriculture

Abstract

The need to ensure food security in the face of growing environmental concerns like climate change and natural catastrophes is raising the need for accurate crop output predictions. Predicting agricultural output is difficult because of the various non-linear interactions involved. So, instead of using traditional statistical tools, many researchers are turning to deep learning approaches to investigate these connections. Since brinjal is so important to the diets of Indians, protecting their ability to eat is of paramount importance. To this end, the attention-based convolution neural network with optimised bidirectional long short-term memory (ACNN-OBDLSTM) model is used to analyse and determine brinjal forecasts in this study. The shuffling shepherd optimisation method (SSOA) is used for hyperparameter tuning of the BDLSTM model, which improves detection performance. The research concludes that the proposed approach is applicable not just to India but also to other leading producing states. India as a whole and its individual states are compared in terms of yield projection. Improved government decision-making, as well as better education and more accurate forecasting, are among the most important outcomes of this study for farmers in India.

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Author Biographies

  • M Venkateswara Rao, NRI Institute of Technology, Vijayawada

    Department of CSE

  • Y. Sreeraman, The Apollo University

    Department of CSE, School of Technology

  • Srihari Varma Mantena, Sagi Rama Krishnam Raju Engineering College, Bhimavaram

    Department of Computer Science and Engineering

  • Venkateswarlu Gundu, Koneru Lakshmaiah Education Foundation

    Department of Computer Science and Engineering

  • D. Roja, Chalapathi Institute of Technology, Guntur

    Department of CSE-Data Science

  • Ramesh Vatambeti, VIT-AP University

    School of Computer Science and Engineering

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Published

2023-08-21

Issue

Section

Computer Sciences and Mathematics

URN

How to Cite

Rao, M. V., Sreeraman, Y., Mantena, S. V., Gundu, V., Roja, D., & Vatambeti, R. (2023). Brinjal Crop yield prediction using Shuffled shepherd optimization algorithm based ACNN-OBDLSTM model in Smart Agriculture . Journal of Integrated Science and Technology, 12(1), 710. https://pubs.thesciencein.org/journal/index.php/jist/article/view/a710

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