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Artificial Neural Network For Optimization In Food Engineering Applications

Amar, Harish S and Lionel, Texeira and Dushyant, Mullur and Raghu, G Iyer (2004) Artificial Neural Network For Optimization In Food Engineering Applications. [Student Project Report]

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Abstract

This Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page.

Item Type: Student Project Report
Additional Information: <p align='justify'>An Artificial Neural Network (ANN) has a massively parallel structure which is composed of many processing elements connected to each other through weights. An ANN performs well while solving optimization problems dealing with a large number of variables.When an input is provided to the network it computes the output using the similarities of all learned patterns. A back propagation model is used here which is a supervised learning paradigm.Here we use an Object Oriented Programming (OOP) approach using C++ instead of the usually used traditional procedural programming. A general purpose ANN has been developed which is consequently used for optimizing a highly complicated food processing operation, such as frying. The input variables are moisture and frying time, and the output parameters involve fat content, failure force, deflection at failure and expansion of the fried product.</p>
Uncontrolled Keywords: Artificial Neural Network Food Engineering Neural Networks Object Oriented Programming
Subjects: 600 Technology > 08 Food technology > 07 Food Engineering
000 Computer science, information and general works > 02 Computer Science
Divisions: Food Engineering
Depositing User: Food Sci. & Technol. Information Services
Date Deposited: 19 Sep 2005
Last Modified: 28 Dec 2011 09:25
URI: http://ir.cftri.com/id/eprint/153

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