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Effectiveness of FPA in Sparse Data Modelling and Optimization

  • R. S. Umamaheswara Raju
  • V. Ramachandra Raju
  • R. Ramesh
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 5)

Abstract

The work is to develop an intelligent model to predict the surface roughness and increase the productivity, as surface roughness estimation is a complex task and cannot be easily done for a given cutting parameters due to the complexity of the machining. In order to predict the surface roughness from cutting parameters, a forward mapping predicted model using flower pollination algorithm (FPA) is developed. While predicting surface roughness the FPA model showed a better performance than the existing regression technique, SVM with competitively a minimum percentile of error.

Keywords

Cutting parameters Surface roughness FPA 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • R. S. Umamaheswara Raju
    • 1
  • V. Ramachandra Raju
    • 2
  • R. Ramesh
    • 1
  1. 1.Department of Mechanical EngineeringMVGRCEVizianagaramIndia
  2. 2.RGUKT (IIIT)APIndia

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