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Paper Information

Journal:   IRANIAN FOOD SCIENCE AND TECHNOLOGY RESEARCH JOURNAL   SUMMER 2015 , Volume 11 , Number 3; Page(s) 247 To 259.
 
Paper: 

MONITORING THE OSMOTIC DEHYDRATION PROCESS OF QUINCE BY THE NOVEL FUSION MODULAR NEURAL NETWORKS - FUZZY LOGIC (FMNN-FL)

 
 
Author(s):  IRANI M.*, SHAFAFI ZENOOZIAN M., IRANI H.
 
* DEPARTMENT OF FOOD SCIENCE AND TECHNOLOGY, FERDOWSI UNIVERSITY OF MASHHAD INTERNATIONAL CAMPUS, IRAN
 
Abstract: 

This paper presents a novel approach to monitor food process based on Modular Neural Networks (MNNs) and fuzzy inference system. The proposed MNN consists of three separate modules, each using different image features as input including: edge detection, wavelet transform, and Hough transform. The sugeno fuzzy inference system was used to combine the outputs from each of these modules to classify the images of quince during osmotic dehydration process. To test the method, for classification, database was made of 108 quince samples’images (12 classes). In experiments, the developed architecture achieved 91.6% recognition accuracy. Next step, solid gain, water loss and moisture content of quince samples were considered as MNNs outputs, whereas osmotic dehydration time and classified images were MNNs inputs. The minimum %MRE (18.153) with 89% prediction ability for water loss (WL) was obtained when applying two hidden layers with 6 neurons per each two layers. The lowest %MRE (35.5335) with 93% prediction ability for solid gain (SG) was obtained when using 6 and 8 neurons per first and second layer, respectively. And finally %MRE was at least (7.4759) with 96% prediction ability for moisture content (MC) by 6 and 5 neurons per first and second layer, respectively.
The results show that this model could be commendably implemented for quantitative modeling and monitoring of food quality changes during osmotic dehydration process.

 
Keyword(s): MODULAR NEURAL NETWORKS, QUINCE, FUZZY INFERENCE SYSTEM, OSMOTIC DEHYDRATION, NEURAL NETWORKS
 
 
References: 
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Citations: 
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+ Click to Cite.
APA: Copy

IRANI, M., & SHAFAFI ZENOOZIAN, M., & IRANI, H. (2015). MONITORING THE OSMOTIC DEHYDRATION PROCESS OF QUINCE BY THE NOVEL FUSION MODULAR NEURAL NETWORKS - FUZZY LOGIC (FMNN-FL). IRANIAN FOOD SCIENCE AND TECHNOLOGY RESEARCH JOURNAL, 11(3), 247-259. https://www.sid.ir/en/journal/ViewPaper.aspx?id=511560



Vancouver: Copy

IRANI M., SHAFAFI ZENOOZIAN M., IRANI H.. MONITORING THE OSMOTIC DEHYDRATION PROCESS OF QUINCE BY THE NOVEL FUSION MODULAR NEURAL NETWORKS - FUZZY LOGIC (FMNN-FL). IRANIAN FOOD SCIENCE AND TECHNOLOGY RESEARCH JOURNAL. 2015 [cited 2021July26];11(3):247-259. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=511560



IEEE: Copy

IRANI, M., SHAFAFI ZENOOZIAN, M., IRANI, H., 2015. MONITORING THE OSMOTIC DEHYDRATION PROCESS OF QUINCE BY THE NOVEL FUSION MODULAR NEURAL NETWORKS - FUZZY LOGIC (FMNN-FL). IRANIAN FOOD SCIENCE AND TECHNOLOGY RESEARCH JOURNAL, [online] 11(3), pp.247-259. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=511560.



 
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