Assessing the effectiveness of Artificial Neural Networks and PSLR models in predicting per capita food grain production in India

Narasimma Bharathi Venkatesa Palanichamy; Muthuswamy Kalpana; Natarajan Balakrishnan; Vasudevan Balamurugan; Appavu Suresh; Marimuthu Rajavel; Rajaram Dhivya; Mahalingam Santhosh Kumar

doi:10.14719/pst.7447

Authors

Venkatesa Palanichamy Narasimma Bharathi Office of the Dean (Agriculture), Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-1273-7347
Kalpana Muthuswamy Office of the Dean (Agriculture), Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-0201-6968
Balakrishnan Natarajan Office of the Dean (Agriculture), Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0001-6461-7374
Balamurugan Vasudevan Office of the Dean (Agriculture), Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0002-5236-9382
Suresh Appavu Office of the Dean (Agriculture), Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0009-0005-0999-6638
Rajavel Marimuthu Office of the Public Relations, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0000-0001-7133-7274
Dhivya Rajaram Department of Business Administration, PSGR Krishnammal College for Women, Coimbatore 641004, Tamil Nadu, India https://orcid.org/0000-0001-7121-6173
Santhosh Kumar Mahalingam Department of Agricultural and Rural Management, Tamil Nadu Agricultural University, Coimbatore 641 003, Tamil Nadu, India https://orcid.org/0009-0006-4618-3297

DOI:

https://doi.org/10.14719/pst.7447

Keywords:

ANN, food grain, India, per capita, PLSR

Abstract

Every living thing needs food. In addition to fostering social progress and economic expansion, agriculture is essential to our everyday existence. India has made great strides toward guaranteeing a sufficient supply of food since gaining its freedom. While India's population has tripled, food grain production has more than quadrupled. Consequently, there are now substantially more food grains available per individual. To meet the country's food needs, rice and wheat production is essential. Decision-makers need access to accurate forecasts to identify this need, put appropriate plans into place and allocate the required administrative resources. Based on artificial neural networks and PSLR, the per capita availability of food grain production in India was estimated. Indiastat and the FAO provided the historical data for the country from 1951 to 2022. To examine the food grain per capita availability (Kgs. Per Year), we used two effective analytical methodologies, artificial neural networks (ANNs) and Partial least squares (PLS) regression. The models' performances were compared using four relevant performance criteria to determine which model is best for future forecasting. The results show that, when it comes to accurately predicting the per capita number of dietary grains, ANN outperforms the PLSR model. For the ANN method, the values of MAE, MSE, RMSE and R2 were 3272.11, 1.748, 4194.28 and 0.956, in that order. The study discovered that PLS also functioned well, with very little difference between the two models' performance indicators.

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