Analysis of demand forecasting of agriculture using machine learning algorithm

The state of India was situated on fertile land and river deltas with appropriate agricultural land. In 2019, agricultural fields, primarily cropland, occupy more than 40% of the country's total surface area. Moreover, agricultural industry revenues less than 3% of the country's Gross Prov...

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Bibliographic Details
Published in:Environment, development and sustainability development and sustainability, 2024-01, Vol.26 (1), p.1731-1747
Main Authors: Chelliah, Balika J., Latchoumi, T. P., Senthilselvi, A.
Format: Article
Language:English
Subjects:
Agribusiness
Agricultural industry
Agricultural land
Agriculture
Algorithms
Centralization
Cost assessments
Deltas
Demand analysis
Destinations
Directing
Earth and Environmental Science
Ecology
Economic Geology
Economic Growth
Economics
Environment
Environmental Economics
Environmental Management
Farmers
Fixation
Industrialization
Insurance
Machine learning
Profitability
Revenue
Supply
Supply chains
Sustainable Development
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Summary:The state of India was situated on fertile land and river deltas with appropriate agricultural land. In 2019, agricultural fields, primarily cropland, occupy more than 40% of the country's total surface area. Moreover, agricultural industry revenues less than 3% of the country's Gross Provincial Product (GPP). While manufacturing has become the country's major financial activity, accounting countries represent half of GPP's revenues. The objective of the study is to find a way to improve the financial profitability and efficiency of farming supply chain networks as follows: (1) Fixation of national-level targets for zonal-level groups information after assessment and forecasts that affect production and distribution of agriculture. (2) Producers risk can be reduced by directing people to multiple factory and industrialization options based on market assessment. (3) Insurance costs and reduction of bank borrowing by standardizing the connection between bankers and producers using the structure to centralise land information. (4), Stabilize the agricultural sector by looking at nearby potential destinations for production and regulation of the Public Distribution System (PDS) flow for the security stock. In this paper, the novel ML target prediction algorithm to inform the farmers about the market target product and improve the relationships between the farmer and bankers for centralizing the information about recent government plans. The crop prediction ML algorithm proposed to improve the revenue of agriculture field.
ISSN:1573-2975
1387-585X
1573-2975
DOI:10.1007/s10668-022-02783-9