Predicting Cotton Fibre Maturity by Using Artificial Neural Network

Autor: Farooq Assad, Sarwar Muhammad Ilyas, Ashraf Muhammad Azeem, Iqbal Danish, Hussain Azmat, Malik Samander
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: AUTEX Research Journal, Vol 18, Iss 4, Pp 429-433 (2018)
Druh dokumentu: article
ISSN: 2300-0929
DOI: 10.1515/aut-2018-0024
Popis: Cotton fibre maturity is the measure of cotton’s secondary cell wall thickness. Both immature and over-mature fibres are undesirable in textile industry due to the various problems caused during different manufacturing processes. The determination of cotton fibre maturity is of vital importance and various methods and techniques have been devised to measure or calculate it. Artificial neural networks have the power to model the complex relationships between the input and output variables. Therefore, a model was developed for the prediction of cotton fibre maturity using the fibre characteristics. The results of predictive modelling showed that mean absolute error of 0.0491 was observed between the actual and predicted values, which show a high degree of accuracy for neural network modelling. Moreover, the importance of input variables was also defined.
Databáze: Directory of Open Access Journals