Vegetable Price Prediction using Adaptive Neuro-Fuzzy Inference System
N. Hemageetha1 , G.M. Nasira2
Section:Research Paper, Product Type: Journal Paper
Volume-5 ,
Issue-3 , Page no. 75-79, Mar-2017
Online published on Mar 31, 2017
Copyright © N. Hemageetha, G.M. Nasira . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: N. Hemageetha, G.M. Nasira , “Vegetable Price Prediction using Adaptive Neuro-Fuzzy Inference System,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.3, pp.75-79, 2017.
MLA Style Citation: N. Hemageetha, G.M. Nasira "Vegetable Price Prediction using Adaptive Neuro-Fuzzy Inference System." International Journal of Computer Sciences and Engineering 5.3 (2017): 75-79.
APA Style Citation: N. Hemageetha, G.M. Nasira , (2017). Vegetable Price Prediction using Adaptive Neuro-Fuzzy Inference System. International Journal of Computer Sciences and Engineering, 5(3), 75-79.
BibTex Style Citation:
@article{Hemageetha_2017,
author = {N. Hemageetha, G.M. Nasira },
title = {Vegetable Price Prediction using Adaptive Neuro-Fuzzy Inference System},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2017},
volume = {5},
Issue = {3},
month = {3},
year = {2017},
issn = {2347-2693},
pages = {75-79},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1212},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1212
TI - Vegetable Price Prediction using Adaptive Neuro-Fuzzy Inference System
T2 - International Journal of Computer Sciences and Engineering
AU - N. Hemageetha, G.M. Nasira
PY - 2017
DA - 2017/03/31
PB - IJCSE, Indore, INDIA
SP - 75-79
IS - 3
VL - 5
SN - 2347-2693
ER -
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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.
Key-Words / Index Term
Data mining, Back-Propagation neural network (BPNN),Redial basis Function (RBF), ANFIS, Vegetible Price
References
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