An Online Diet Recommendation System Based On Artificial Intelligence
D.S. Zingade1 , Umar Shaikh2 , Shreyas Saisekhar3 , Umang Koul4 , Keshav Vaswani5
Section:Review Paper, Product Type: Journal Paper
Volume-7 ,
Issue-4 , Page no. 1126-1130, Apr-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i4.11261130
Online published on Apr 30, 2019
Copyright © D.S. Zingade, Umar Shaikh, Shreyas Saisekhar, Umang Koul, Keshav Vaswani . 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: D.S. Zingade, Umar Shaikh, Shreyas Saisekhar, Umang Koul, Keshav Vaswani, “An Online Diet Recommendation System Based On Artificial Intelligence,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1126-1130, 2019.
MLA Style Citation: D.S. Zingade, Umar Shaikh, Shreyas Saisekhar, Umang Koul, Keshav Vaswani "An Online Diet Recommendation System Based On Artificial Intelligence." International Journal of Computer Sciences and Engineering 7.4 (2019): 1126-1130.
APA Style Citation: D.S. Zingade, Umar Shaikh, Shreyas Saisekhar, Umang Koul, Keshav Vaswani, (2019). An Online Diet Recommendation System Based On Artificial Intelligence. International Journal of Computer Sciences and Engineering, 7(4), 1126-1130.
BibTex Style Citation:
@article{Zingade_2019,
author = {D.S. Zingade, Umar Shaikh, Shreyas Saisekhar, Umang Koul, Keshav Vaswani},
title = {An Online Diet Recommendation System Based On Artificial Intelligence},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {7},
Issue = {4},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {1126-1130},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4176},
doi = {https://doi.org/10.26438/ijcse/v7i4.11261130}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i4.11261130}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4176
TI - An Online Diet Recommendation System Based On Artificial Intelligence
T2 - International Journal of Computer Sciences and Engineering
AU - D.S. Zingade, Umar Shaikh, Shreyas Saisekhar, Umang Koul, Keshav Vaswani
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 1126-1130
IS - 4
VL - 7
SN - 2347-2693
ER -
VIEWS | XML | |
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Abstract
This research paper aims to present the study and implementation of artificial intelligence dietician which can simulate the experience of a human dietician. The main aim is to recommend to the users a perfectly planned diet according to their body parameters and their day to day activities using artificial intelligence. The online artificial dietician is a bot with artificial intelligence about human nourishments. It acts as a diet specialist similar to an actual dietician. We have also taken under consideration the health status of the user. We have used artificial intelligence as the driving technology. To select the diet of user it has to check various parameters and there can be various food items that pass the criteria. So to select the best among all, we take the help of Genetic Algorithm. Genetic Algorithm is our key algorithm, besides the Naïve Bayes algorithm. Genetic algorithm keeps on finding the best option from the pool of options while Naïve Bayes is used for the purpose of classification.
Key-Words / Index Term
Genetic algorithm, Naïve Bayes Classifier, Artificial Intelligence
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