AGRICULTURAL DATA ANALYSIS
Journal: International Journal of Advanced Research (Vol.9, No. 8)Publication Date: 2021-08-20
Authors : Shobana S.; M. Sujithra;
Page : 807-815
Keywords : Data Mining Accomplishing Agriculture Environment Variability;
Abstract
In agriculture sector where farmers and agribusinesses have to make innumerable decisions every day and intricate complexities involves the various factors influencing them. An essential issue for agricultural planning intention is the accurate yield estimation for the numerous crops involved in the planning. Data mining techniques are necessary approach for accomplishing practical and effective solutions for this problem. Agriculture has been an obvious target for big data. Environmental conditions, variability in soil, input levels, combinations and commodity prices have made it all the more relevant for farmers to use information and get help to make critical farming decisions. This paper focuses on the analysis of the agriculture data and finding optimal parameters to maximize the crop production using Machine learning techniques like random forest regressor and Linear Regression. Mining the large amount of existing crop, soil and climatic data, and analysing new, non-experimental data optimizes the production and makes agriculture more resilient to climatic change.
Other Latest Articles
- SOCIO-ECONOMIC STRUCTURE AND DEVELOPMENT: LEVELS OF DEVELOPMENT IN RUDRAPRAYAG DISTRICT, UTTARAKHAND, INDIA
- EFFECTS OF EXERCISE ON MENTAL HEALTH AMONST ADULTS: A REVIEW OF LITERATURE
- TEACHERS RESEARCH PRODUCTIVITY, EMOTIONAL INTELLIGENCE AND INSTRUCTIONAL SUPERVISION AS DETERMINANTS OF TEACHERS PERFORMANCE IN AUGUSTINIAN HIGHER EDUCATION INSTITUTIONS
- DETERMINACIA N DE ALTERACIONES HEMODINAÂMICAS TRANSOPERATORIAS CON MONITOREO POR BIORREACTANCIA EN CIRUGAÂA DE COLUMNA
- CHARACTERIZATION OF LATERITIC SOILS FOR USE IN THE MANUFACTURE OF COMPRESSED EARTH BLOCKS (CEB)
Last modified: 2021-09-14 16:54:16