Model (DSSAT-CSM), have been developed for predicting crop yield at field and regional scales and to. The tools involved in precision agriculture may also. Automatic applications based on soil water depletion. Building a machine learning model to predict crop yields based on environmental data. Ask Question Asked 3 years. $ begingroup$ even i'm trying to build a model to predict crop yield. You can use Bayesian Belief Network for prediction. Her is a link for basic explanation. Bayesian Network.
Crop modelling with the DSSAT.1.Crop modelling with the DSSAT September 2011.Why model?. Use for manipulations and experiments that are impractical,too expensive, too lengthy or impossible (in real-world socialand economic systems). Address dynamic complexity (“emergent properties”) ofsystems in a way that reductionist science may not be able todo.
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Identify “best management” strategies (through optimization). Study the long-term effects of options (predictions,projections).Why model? -2-. Allow the researcher to control environmental andexperimental conditions.
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Allow hypothetical and exploratory situations to beinvestigated. Allow insight to be gained into the relative importance ofdifferent system elements. Assemble and synthesise what is known about particularprocesses Nicholson (2008).What can models produce?