Modelling and Predicting the Breaking Strength and  Mass Irregularity of Cotton Rotor-Spun Yarns Containing  Cotton Fiber Recovered from Ginning Process by Using  Artificial Neural Network Algorithm

<table class="table-group" id="tab9"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td align="left">Excluded input  parameter</td><td align="center">MSE</td><td align="center">Increase in  mean square error (%)</td><td align="center">Ranking</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td align="left">Rotor speed</td><td align="center">0.442</td><td align="center">216.285</td><td align="center">1</td></tr><tr><td align="left">Rotor diameter</td><td align="center">0.289</td><td align="center">106.714</td><td align="center">3</td></tr><tr><td align="left">Opener roller speed</td><td align="center">0.153</td><td align="center">9.928</td><td align="center">6</td></tr><tr><td align="left">Navel type</td><td align="center">0.254</td><td align="center">81.926</td><td align="center">4</td></tr><tr><td align="left">Waste percentage</td><td align="center">0.428</td><td align="center">206.214</td><td align="center">2</td></tr><tr><td align="left">Yarn count</td><td align="center">0.249</td><td align="center">78.285</td><td align="center">5</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Effectiveness of input parameters on breaking strength.

Modelling and Simulation in Engineering

tab9

Table 9

Table 9: Modelling and Predicting the Breaking Strength and  Mass Irregularity of Cotton Rotor-Spun Yarns Containing  Cotton Fiber Recovered from Ginning Process by Using  Artificial Neural Network Algorithm 

Table 9 | Modelling and Predicting the Breaking Strength and  Mass Irregularity of Cotton Rotor-Spun Yarns Containing  Cotton Fiber Recovered from Ginning Process by Using  Artificial Neural Network Algorithm 