Multi performance parameters analysis in a manufacturing system using fuzzy logic and optimal neural network model Online publication date: Wed, 17-Jan-2018
by R. Prasanna Lakshmi; P. Nelson Raja
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 13, No. 4, 2018
Abstract: Support operations enhance machine conditions; additionally involve potential creation time, conceivably postponing the client orders. The target of this paper is to decide execution parameters in every work stations with foresee the cost, dependability and accessibility of the business. This estimate examination considers two sorts of various methodologies, for example, FLP ideal neural system model. At first utilising FLP to foresee the exhibitions parameters and expanding the exactness of examination by means of ANN with motivated enhancement procedure to upgrade the weights in structure. All the ideal results exhibit the way that the accomplished mistake values between the yield of the trial values and the anticipated qualities are firmly equivalent to zero in the planned system. From the outcomes the proposed KHO-based ideal neural system demonstrates the exactness is 98.23% it is contrasted with the Pareto improvement model.
Online publication date: Wed, 17-Jan-2018
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Intelligence and Data Mining (IJBIDM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com