Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal
This paper presents the capability of simulated neural network (SNN) models for predicting the shelf life of processed cheese stored at ambient temperature 30o C. Processed cheese is a dairy product generally made from medium ripened Cheddar cheese. Elman and Linear Layer(Train) SNN models were deve...
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| Format: | Article |
| Language: | English |
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Universiti Teknologi MARA, Perlis
2012
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| Online Access: | https://ir.uitm.edu.my/id/eprint/34381/1/34381.pdf |
| _version_ | 1825737934530150400 |
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| author | Goyal, Sumit Goyal, Gyanendra Kumar |
| author_facet | Goyal, Sumit Goyal, Gyanendra Kumar |
| author_sort | Goyal, Sumit |
| collection | UITM |
| description | This paper presents the capability of simulated neural network (SNN) models for predicting the shelf life of processed cheese stored at ambient temperature 30o C. Processed cheese is a dairy product generally made from medium ripened Cheddar cheese. Elman and Linear Layer(Train) SNN models were developed. Body & texture, aroma & flavour, moisture, free fatty acids were used as input variables and sensory score as the output. Neurons in each hidden layers varied from 1 to 40. The network was trained with single as well as double hidden layers up to 100 epochs, and transfer function for hidden layer was tangent sigmoid while for the output layer, it was pure linear function. Mean square error, root mean square error, coefficient of determination and nash - sutcliffo coefficient performance measures were used for testing prediction potential of the developed models. Results showed a 4201 topology was able to predict the shelf life of processed cheese exceedingly well with R2 as 0.99992157. The corresponding RMSE for this topology was 0.003615359. From this study it is concluded that SNN models are excellent tool for predicting the shelf life of processed cheese. |
| first_indexed | 2024-03-06T02:25:51Z |
| format | Article |
| id | oai:ir.uitm.edu.my:34381 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T02:25:51Z |
| publishDate | 2012 |
| publisher | Universiti Teknologi MARA, Perlis |
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| spelling | oai:ir.uitm.edu.my:343812020-09-17T03:38:59Z https://ir.uitm.edu.my/id/eprint/34381/ Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal jurnalintelek Goyal, Sumit Goyal, Gyanendra Kumar Neural networks (Computer science) This paper presents the capability of simulated neural network (SNN) models for predicting the shelf life of processed cheese stored at ambient temperature 30o C. Processed cheese is a dairy product generally made from medium ripened Cheddar cheese. Elman and Linear Layer(Train) SNN models were developed. Body & texture, aroma & flavour, moisture, free fatty acids were used as input variables and sensory score as the output. Neurons in each hidden layers varied from 1 to 40. The network was trained with single as well as double hidden layers up to 100 epochs, and transfer function for hidden layer was tangent sigmoid while for the output layer, it was pure linear function. Mean square error, root mean square error, coefficient of determination and nash - sutcliffo coefficient performance measures were used for testing prediction potential of the developed models. Results showed a 4201 topology was able to predict the shelf life of processed cheese exceedingly well with R2 as 0.99992157. The corresponding RMSE for this topology was 0.003615359. From this study it is concluded that SNN models are excellent tool for predicting the shelf life of processed cheese. Universiti Teknologi MARA, Perlis 2012-12 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/34381/1/34381.pdf Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal. (2012) Jurnal Intelek <https://ir.uitm.edu.my/view/publication/Jurnal_Intelek/>, 7 (2). pp. 48-54. ISSN 2682-9223 https://jurnalintelek.uitm.edu.my/index.php/main |
| spellingShingle | Neural networks (Computer science) Goyal, Sumit Goyal, Gyanendra Kumar Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal |
| title | Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal |
| title_full | Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal |
| title_fullStr | Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal |
| title_full_unstemmed | Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal |
| title_short | Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal |
| title_sort | application of simulated neural networks as non linear modular modeling method for predicting shelf life of processed cheese sumit goyal and gyanendra kumar goyal |
| topic | Neural networks (Computer science) |
| url | https://ir.uitm.edu.my/id/eprint/34381/1/34381.pdf |
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