Fuzzy Logic Model to Predict the Color Properties of Pineapple Leaf Fiber Fabric

This study aimed to fabricate a Fuzzy Logic (FL) model based on dye, salt, and alkali concentrations to predict the color properties of pineapple leaf fiber (PALF) fabric dyed with reactive dyes. The nonlinear and interactive nature of these factors makes it challenging to make an exact model using mathematical or statistical methods. Additionally, artificial neural networks and neuro-fuzzy models require extensive trial data for parameter optimization, which is often difficult to obtain from dyeing industries. In this context, FL is an effective modeling tool, capable of handling nonlinear complex domains with minimal trial data. The test data confirmed the model established in this study, showing a mean absolute error (MAE) for all parameters within the acceptable range (<5%) and coefficients of determination (R²) exceeding 0.96. It is concluded that the FL model is efficient in the prediction of color properties of PALF fabric in nonlinear complex dyeing with high accuracy. Journal of Engineering Science 15(2), 2024, 13-27

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Publication Details

Journal
Journal of Engineering Science
Published
2025-06-24
DOI
https://doi.org/10.3329/jes.v15i2.82158
Citations
1
Primary Topic
Leaf Properties and Growth Measurement
Type
article
Field-Weighted Citation Impact
1.75
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article

Fuzzy Logic Model to Predict the Color Properties of Pineapple Leaf Fiber Fabric

Mohammad Abdul Jalil, Ismail Hossain, Joy Sarkar, S. Twareque Ali
1 citations
Journal of Engineering Science
Leaf Properties and Growth Measurement
1.75
article

Fuzzy Logic Model to Predict the Color Properties of Pineapple Leaf Fiber Fabric

Mohammad Abdul Jalil, Ismail Hossain, Joy Sarkar, S. Twareque Ali
article en
1 citations

Abstract

This study aimed to fabricate a Fuzzy Logic (FL) model based on dye, salt, and alkali concentrations to predict the color properties of pineapple leaf fiber (PALF) fabric dyed with reactive dyes. The nonlinear and interactive nature of these factors makes it challenging to make an exact model using mathematical or statistical methods. Additionally, artificial neural networks and neuro-fuzzy models require extensive trial data for parameter optimization, which is often difficult to obtain from dyeing industries. In this context, FL is an effective modeling tool, capable of handling nonlinear complex domains with minimal trial data. The test data confirmed the model established in this study, showing a mean absolute error (MAE) for all parameters within the acceptable range (<5%) and coefficients of determination (R²) exceeding 0.96. It is concluded that the FL model is efficient in the prediction of color properties of PALF fabric in nonlinear complex dyeing with high accuracy. Journal of Engineering Science 15(2), 2024, 13-27

Journal of Engineering ScienceVol. 15(2)
Khulna University of Engineering and Technology (BD)
Openalex Percentile: Top 14%
Leaf Properties and Growth Measurement
1.75
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Fuzzy Logic Model to Predict the Color Properties of Pineapple Leaf Fiber Fabric — Mohammad Abdul Jalil, Ismail Hossain, et al. · Journal of Engineering Science (2025) | TGRS Research Map | TGRS