Prediction of yarn composition using probabilistic type of artificial neural network.
| dc.contributor.author | Jabwana, David | |
| dc.date.accessioned | 2022-05-13T08:40:50Z | |
| dc.date.available | 2022-05-13T08:40:50Z | |
| dc.date.issued | 2015-06 | |
| dc.description | Dissertation. | en_US |
| dc.description.abstract | The main objective of the was to predict yarn composition by probabilistic neural network. Yarns are produced by a series of processes which include blow room, carding, draw frame, comber for combed yarns, speed frame for ring spun yarns, ring frame and rotor spinning machine. Yarn composition is term used to describe the-percentage of each type of fibers in a yarn. Prediction of yam composition was successful since the performance of the pnn model shows the capability of it predicting composition as shown by; Goodness of fit: SSE: 7.601, R-square: 0.9975, Adjusted R-square: 0.9974, RMSE: 0.521 Matlab programming was also Successful as tool since it was able perform its intended function during the prediction process | en_US |
| dc.description.sponsorship | Dr. Nibikora Ildephonse, Mr. Allan Kasedde, Busitema University. | en_US |
| dc.identifier.citation | Jabwana, David. (2015). Prediction of yarn composition using probabilistic type of artificial neural network. Busitema University. Unpublished dissertation. | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.12283/1119 | |
| dc.language.iso | en | en_US |
| dc.publisher | Busitema University. | en_US |
| dc.subject | Yarn composition | en_US |
| dc.subject | Prediction of yam | en_US |
| dc.subject | Yarn | en_US |
| dc.title | Prediction of yarn composition using probabilistic type of artificial neural network. | en_US |
| dc.type | Thesis | en_US |