Prediction of Commodities in Rationing System Using an Enhanced Regression Neural Network Algorithm

Predictive analytics is an area of data mining that deals with extracting information from data and using it to predict trends and behaviour patterns. The paper predicts the usage of the food commodities in public distribution system in the coming years using the general regression neural network algorithm. The algorithm is enhanced using the NTP algorithm which trains the data as per the requirements of ration system in Tamilnadu. A memory-based network that provides estimates of continuous variables and converges to the underlying (linear or nonlinear) regression surface. This general regression neural network (GRNN) is a one-pass learning algorithm with a highly parallel structure. Even with sparse data in a multidimensional measurement space, the algorithm provides smooth transitions from one observed value to another. [email protected] KeywordNTP, NNT, PDS2, PGR, AAY