Abstract:
Neural networks(NN) are a very popular
data mining, classification, and image-processing
tool.In this paper, neural network model is used to
classify the specific features of rice. The purpose
of rice grading is to ensure that the rice produced
for the market meets the quality requirements of
consumer and to help the experts whose decision
process will benefit for grading of the product.The
grading of rice is important in the rice production
industry becauserice quality affects the price and
market demand. The purpose of this paper is to
design a NN model for rice grading based on the
type of rice (Emata, Zeera, Ngasein) and to
showthe accuracy of NN based on mean square
error. Rules are extracted from trained datasets
and these rules are used for grading of rice. There
are 300 data in the dataset. These data are the
features of rice that are received from the
Department of Consumer Affairs, Ministry of
Commerce.
