International Journal of Mathematics Trends and Technology
Volume 65 | Issue 10 | Year 2019 | Article Id. IJMTT-V65I10P508 | DOI : https://doi.org/10.14445/22315373/IJMTT-V65I10P508
Agriculture plays a pivotal role in the advancement of any country's economy. Its productivity has obvious increase income. However, it is greatly dependent on climatic changes. To help counter this, Artificial Neural Network models have been used as an approach for achieving practical and effective solutions in predicting crop yield using weather conditions and soil parameters as inputs. However, human population as a parameter has not been addressed in Artificial Neural Network models by most researchers. For this reason, this study intends to in-corporates population in a Generalised Regression Neural Network Model in predicting maize yield among other parameters like area of production, amount of rainfall and temperature, by factoring in a connection between the weights the number of neurons. Collected data from Trans-Nzoia County will be used for developing and validating the model. The developed model would be useful in helping the farmers predict the yield of maize for post-harvest management and marketing.
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Ratip A. O, Okoth A. W, Wanyonyi R.W, "A Generalised Regression Neural Network Model For Maize Production In Trans Nzoia County," International Journal of Mathematics Trends and Technology (IJMTT), vol. 65, no. 10, pp. 54-60, 2019. Crossref, https://doi.org/10.14445/22315373/IJMTT-V65I10P508
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