Sustainable Development Forecasting of the Agricultural Sector using Machine Learning

Olena Vasyl’yeva, Lidiia Horoshkova, Denis Morozov, Olena Trokhymets

2022

Abstract

Sustainable development paradigm is a combination of economic, social and environmental components represented by a significant number of interconnected factors. Their comprehensive impact determines the ways and dynamics of achieving sustainable development goals. Sustainable development forecasting is accompanied by the analysis and processing of a significant set of indicators and requires special methods of data processing. The neural network modelling allowed to form a multifactorial impact model on the final indicator, namely labour productivity, according to the sustainable development goals. The proposed model allows not only to model and forecast, based on the previously obtained indicators and their dynamics, but also to set target benchmarks to obtain a range of possible scenarios of system development, which depends on the forecasting conditions and parameters. They do not only increase the validity of managerial decision-making, but also ensures relevant adaptation of the management object to the changing environment, affects not only the final result, but also the process of its achievement, including optimization of sustainable development levers.

Paper Citation

in Harvard Style

Vasyl’yeva O., Horoshkova L., Morozov D. and Trokhymets O. (2022). Sustainable Development Forecasting of the Agricultural Sector using Machine Learning. In Proceedings of the 5th International Scientific Congress Society of Ambient Intelligence - Volume 1: ISC SAI, ISBN 978-989-758-600-2, pages 187-196. DOI: 10.5220/0011347100003350

in Bibtex Style

@conference{isc sai22,
author={Olena Vasyl’yeva and Lidiia Horoshkova and Denis Morozov and Olena Trokhymets},
title={Sustainable Development Forecasting of the Agricultural Sector using Machine Learning},
booktitle={Proceedings of the 5th International Scientific Congress Society of Ambient Intelligence - Volume 1: ISC SAI,},
year={2022},
pages={187-196},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011347100003350},
isbn={978-989-758-600-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Scientific Congress Society of Ambient Intelligence - Volume 1: ISC SAI,
TI - Sustainable Development Forecasting of the Agricultural Sector using Machine Learning
SN - 978-989-758-600-2
AU - Vasyl’yeva O.
AU - Horoshkova L.
AU - Morozov D.
AU - Trokhymets O.
PY - 2022
SP - 187
EP - 196
DO - 10.5220/0011347100003350