Thesis Open Access

Neural Network predictive process modeling: Application to food processing

Mesfin Agide


JSON-LD (schema.org) Export

{
  "description": "<p>Currently, food processing industry is driven by several requirements. This<br>\nrequirement includes ensuring safety, meeting quality standard and customer<br>\nexpectation and reducing production cost to be competent in market. To achieve<br>\nthis requirement they have to operate at optimum process conditions all the time.<br>\nIn food processing, due to the nature of the process, it is difficult to find and<br>\noperate at the best conditions solely by experience.<br>\nThe Ethiopia food industry is no coping up with such requirement due cost<br>\nof optimization and low level of education of works operating in the production<br>\nsystem. Thus, it is necessary modeling of the process or part of the process to<br>\ncapture the relation of between important process parameters and use the model to<br>\ncontrol and improve the process better. In addition, it is found necessary to make<br>\nthe model accessible for the operators working in Ethiopian industry. Using<br>\nartificial neural network method is found to be very good modeling to tool to solve<br>\nfood engineering problems</p>", 
  "license": "http://www.opendefinition.org/licenses/cc-by", 
  "creator": [
    {
      "@type": "Person", 
      "name": "Mesfin Agide"
    }
  ], 
  "headline": "Neural Network predictive process modeling: Application to food processing", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2009-03-01", 
  "url": "https://nadre.ethernet.edu.et/record/4930", 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.20372/nadre:4930", 
  "@id": "https://doi.org/10.20372/nadre:4930", 
  "@type": "ScholarlyArticle", 
  "name": "Neural Network predictive process modeling: Application to food processing"
}
0
0
views
downloads
All versions This version
Views 00
Downloads 00
Data volume 0 Bytes0 Bytes
Unique views 00
Unique downloads 00

Share

Cite as