An Effective Multiple Linear Regression-Based Forecasting Model for Demand-Based Constructive Farming

Autor/inn/en	Prabhu B. V., Balaji; Dakshayini, M.
Titel	An Effective Multiple Linear Regression-Based Forecasting Model for Demand-Based Constructive Farming
Quelle	In: International Journal of Web-Based Learning and Teaching Technologies, 15 (2020) 2, S.1-18, Artikel 1 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1548-1093
DOI	10.4018/IJWLTT.2020040101
Schlagwörter	Multiple Regression Analysis; Prediction; Agriculture; Agricultural Production; Foreign Countries; India + Suchen Sie Ihr Suchwort? Vorhersage; Landwirtschaft; Agriculture; Production; Produktion; Agrarproduktion; Landwirtschaftliche Produktion; Ausland; Indien
Abstract	Demand planning plays a very strategic role in improving the performance of every business, as the planning for a whole lot of other activities depends on the accuracy and validity of this exercise. The field of agriculture is not an exception; demand forecasting plays an important role in this area also, where a farmer can plan for the crop production according to the demand in future. Hence, a system which could forecasts the demand for day-to-day food harvests and assists the farmers in planning the crop production accordingly may lead to beneficial farming business. This paper would experiment by forecasting the demand using multiple linear regression (EMLR-DF) for different food commodities and implements the model to assists the farmers in demand based constructive farming. Implementation results have proved the effectiveness of the proposed system in educating the farmers in producing the yields mapping to the demand. Implementation and comparison results have proved the proposed EMLR-DF is more effective and accurate. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2022/1/01