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{ "item_title" : "Identification of flow pattern in microchannel using ANN", "item_author" : [" Seim Timung", "Tapas K. Mandal "], "item_description" : "This book is based on my M. Tech work on prediction of flow patterns of gas-liquid flow in microchannel using probabilistic neural network (PNN). It also contains a brief description on PNN and steps to develop a PNN in MATLAB R2008a. The analytical models present in literature, to predict the gas-liquid flow patterns employs different physics involved. So, for each flow pattern there are separate models being developed. This present work is aim to develop a single PNN model for predicting the flow patterns. The advantage of using a PNN is the ability to predict without any detail knowledge and understanding of the physics involved.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/65/939/774/3659397741_b.jpg", "price_data" : { "retail_price" : "43.09", "online_price" : "43.09", "our_price" : "43.09", "club_price" : "43.09", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Identification of flow pattern in microchannel using ANN|Seim Timung

Identification of flow pattern in microchannel using ANN

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Overview

This book is based on my M. Tech work on prediction of flow patterns of gas-liquid flow in microchannel using probabilistic neural network (PNN). It also contains a brief description on PNN and steps to develop a PNN in MATLAB R2008a. The analytical models present in literature, to predict the gas-liquid flow patterns employs different physics involved. So, for each flow pattern there are separate models being developed. This present work is aim to develop a single PNN model for predicting the flow patterns. The advantage of using a PNN is the ability to predict without any detail knowledge and understanding of the physics involved.

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Details

  • ISBN-13: 9783659397745
  • ISBN-10: 3659397741
  • Publisher: LAP Lambert Academic Publishing
  • Publish Date: May 2013
  • Dimensions: 9 x 6 x 0.18 inches
  • Shipping Weight: 0.27 pounds
  • Page Count: 76

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