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DC Field | Value | Language |
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dc.contributor.author | Bobade P. | |
dc.contributor.author | Kumar P. | |
dc.contributor.author | Chandrasekaran K. | |
dc.contributor.author | Usha D. | |
dc.date.accessioned | 2021-05-05T10:16:08Z | - |
dc.date.available | 2021-05-05T10:16:08Z | - |
dc.date.issued | 2020 | |
dc.identifier.citation | 2020 IEEE International Conference on Computing, Power and Communication Technologies, GUCON 2020 , Vol. , , p. 639 - 643 | en_US |
dc.identifier.uri | https://doi.org/10.1109/GUCON48875.2020.9231213 | |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/14985 | - |
dc.description.abstract | Cholesterol, hypertension and diabetes are the three major chronic diseases from which most of the people suffers and these peoples often use search engines to acquire related information about these problems. But, almost every information related to diet on the internet isn't suitable for people to gather information about the diet suggestions. A system for diet suggestion which can advocate a prudent diet for such peoples is suggested in this paper. We designed a system that recommends a proper diet which has the adequate knowledge of three above mentioned highly chronic diseases. We propose a solution to the menu recommending problem using the optimization algorithm known as unbounded knapsack. We designed a model which satisfies the nutritional requirements of individuals while imposing the 'Laws of Nutrition', a set of hypothesis used by almost all Latin America's nutrition scientists. This prototype corresponds to a numerical optimization problem with constraints. We design a menu items generator application model to set up a convenient menu for a user with different properties. © 2020 IEEE. | en_US |
dc.title | Optimized diet plan using unbounded knapsack Algorithm | en_US |
dc.type | Conference Paper | en_US |
Appears in Collections: | 2. Conference Papers |
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