Evaluating the Smoothness of the Washed Fabric after Laundry with the Washing Machine Based on a New Type-2 Fuzzy Neural Network
Clothes laundering are necessary during their cycle life, and the mechanical forces exposed to fabrics during laundering were caused to wrinkle. Therefore, in this paper, the wrinkle of the cotton fabric after home laundering was evaluated based on their characteristic. The washing process was done...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/2401736 |
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| author | Mir Saeid Hesarian Jafar Tavoosi |
| author_facet | Mir Saeid Hesarian Jafar Tavoosi |
| author_sort | Mir Saeid Hesarian |
| collection | DOAJ |
| description | Clothes laundering are necessary during their cycle life, and the mechanical forces exposed to fabrics during laundering were caused to wrinkle. Therefore, in this paper, the wrinkle of the cotton fabric after home laundering was evaluated based on their characteristic. The washing process was done without any softener as toxic material. For this purpose, experimental and theoretical evaluations were conducted. In experiments, the cotton fabrics in various characteristics were washed by washing machine without any softener in special adjustments. The wrinkle of the samples was rated based on the light line method. Theoretical evaluations were studied by the development of a new type-2 fuzzy neural network. In this model the thickness, weight, warp and weft density per inch, warp and weft Tex as linear density, and cover factor of the fabric in warp and weft directions were considered as input parameters and the wrinkle grade of the washed fabric was output. Analysis of the modeling and experimental results illustrates that when eight mentioned parameters were selected as inputs, the mean square error, root mean square error, and mean absolute error of the model were decreased in comparison of the models with two, four, and six inputs. According to this fact, all of the input parameters have an effect on the wrinkle of the cotton fabric after the washing process. |
| format | Article |
| id | doaj-art-bf5bf150b6aa4f4aa85bbb92bad80d54 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-bf5bf150b6aa4f4aa85bbb92bad80d542025-02-03T01:19:58ZengWileyComplexity1099-05262022-01-01202210.1155/2022/2401736Evaluating the Smoothness of the Washed Fabric after Laundry with the Washing Machine Based on a New Type-2 Fuzzy Neural NetworkMir Saeid Hesarian0Jafar Tavoosi1Faculty of Textile EngineeringDepartment of Electrical EngineeringClothes laundering are necessary during their cycle life, and the mechanical forces exposed to fabrics during laundering were caused to wrinkle. Therefore, in this paper, the wrinkle of the cotton fabric after home laundering was evaluated based on their characteristic. The washing process was done without any softener as toxic material. For this purpose, experimental and theoretical evaluations were conducted. In experiments, the cotton fabrics in various characteristics were washed by washing machine without any softener in special adjustments. The wrinkle of the samples was rated based on the light line method. Theoretical evaluations were studied by the development of a new type-2 fuzzy neural network. In this model the thickness, weight, warp and weft density per inch, warp and weft Tex as linear density, and cover factor of the fabric in warp and weft directions were considered as input parameters and the wrinkle grade of the washed fabric was output. Analysis of the modeling and experimental results illustrates that when eight mentioned parameters were selected as inputs, the mean square error, root mean square error, and mean absolute error of the model were decreased in comparison of the models with two, four, and six inputs. According to this fact, all of the input parameters have an effect on the wrinkle of the cotton fabric after the washing process.http://dx.doi.org/10.1155/2022/2401736 |
| spellingShingle | Mir Saeid Hesarian Jafar Tavoosi Evaluating the Smoothness of the Washed Fabric after Laundry with the Washing Machine Based on a New Type-2 Fuzzy Neural Network Complexity |
| title | Evaluating the Smoothness of the Washed Fabric after Laundry with the Washing Machine Based on a New Type-2 Fuzzy Neural Network |
| title_full | Evaluating the Smoothness of the Washed Fabric after Laundry with the Washing Machine Based on a New Type-2 Fuzzy Neural Network |
| title_fullStr | Evaluating the Smoothness of the Washed Fabric after Laundry with the Washing Machine Based on a New Type-2 Fuzzy Neural Network |
| title_full_unstemmed | Evaluating the Smoothness of the Washed Fabric after Laundry with the Washing Machine Based on a New Type-2 Fuzzy Neural Network |
| title_short | Evaluating the Smoothness of the Washed Fabric after Laundry with the Washing Machine Based on a New Type-2 Fuzzy Neural Network |
| title_sort | evaluating the smoothness of the washed fabric after laundry with the washing machine based on a new type 2 fuzzy neural network |
| url | http://dx.doi.org/10.1155/2022/2401736 |
| work_keys_str_mv | AT mirsaeidhesarian evaluatingthesmoothnessofthewashedfabricafterlaundrywiththewashingmachinebasedonanewtype2fuzzyneuralnetwork AT jafartavoosi evaluatingthesmoothnessofthewashedfabricafterlaundrywiththewashingmachinebasedonanewtype2fuzzyneuralnetwork |