Vegetable Price Prediction using Adaptive Neuro-Fuzzy Inference System

Authors

  • N Hemageetha Department of computer Science, Govt Arts College for women, Salem, India
  • GM Nasira Department of Computer Applications , Chikkanna Govt. Arts College , Tirupur, India

Keywords:

Data mining, Back-Propagation neural network (BPNN), Redial basis Function (RBF), ANFIS, Vegetible Price

Abstract

The Agricultural sector is a very important one in the developing countries. In agriculture domain it is very difficult to predict the price of the vegetable, so making use of the prediction technique like neural networks the price is predicted. In this paper a prediction model is established with the help of Adaptive neuro-fuzzy inference system and compares the result with other models. The result for the proposed prediction model is more efficient and accurate than other neural network models for predicting the price of the vegetables.

References

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G.M. Nasira and N. Hemageetha, “Forecasting Model for Vegetable Price Using Back Propagation Neural Network” International Journal of Computational Intelligence and Informatics,Vol. 2: No. 1, pp.110—115, Sep 2012.

N. Hemageetha and G.M. Nasira, “Redial bassis function model for Vegetable Price Prediction “ International Conference on pattern Recognition, Informatics and Medical Engineering (PRIME 2013), PP. 424—428 ISBN No:978-1-4673-5843-9.

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Published

2025-11-11

How to Cite

[1]
N. Hemageetha and G. Nasira, “Vegetable Price Prediction using Adaptive Neuro-Fuzzy Inference System”, Int. J. Comp. Sci. Eng., vol. 5, no. 3, pp. 75–79, Nov. 2025.

Issue

Vol. 5 No. 3 (2017): IJCSE March Edition

Section

Research Article

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