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  1. International Journal of Machine Learning and Cybernetics
  2. International Journal of Machine Learning and Cybernetics : Volume 6
  3. International Journal of Machine Learning and Cybernetics : Volume 6, Issue 2, April 2015
  4. Parameter optimization of multi-pass turning using chaotic PSO
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International Journal of Machine Learning and Cybernetics : Volume 8
International Journal of Machine Learning and Cybernetics : Volume 7
International Journal of Machine Learning and Cybernetics : Volume 6
International Journal of Machine Learning and Cybernetics : Volume 6, Issue 6, December 2015
International Journal of Machine Learning and Cybernetics : Volume 6, Issue 5, October 2015
International Journal of Machine Learning and Cybernetics : Volume 6, Issue 4, August 2015
International Journal of Machine Learning and Cybernetics : Volume 6, Issue 3, June 2015
International Journal of Machine Learning and Cybernetics : Volume 6, Issue 2, April 2015
A hybrid optimization method with PSO and GA to automatically design Type-1 and Type-2 fuzzy logic controllers
A Chinese expert disambiguation method based on semi-supervised graph clustering
IF-preorder, IF-topology and IF-automata
State estimation for memristor-based neural networks with time-varying delays
Visual reasoning for discoveries
Adaptive exponential synchronization of delayed Cohen–Grossberg neural networks with discontinuous activations
User feedback based metasearching using neural network
Visual music score detection with unsupervised feature learning method based on K-means
Improved stochastic dissipativity of uncertain discrete-time neural networks with multiple delays and impulses
Simultaneous estimation of nonlinear parameters in parabolic partial differential equation using quantum-behaved particle swarm optimization with Gaussian mutation
Parameter optimization of multi-pass turning using chaotic PSO
Evaluation of path stretch in scalable routing system
International Journal of Machine Learning and Cybernetics : Volume 6, Issue 1, February 2015
International Journal of Machine Learning and Cybernetics : Volume 5
International Journal of Machine Learning and Cybernetics : Volume 4
International Journal of Machine Learning and Cybernetics : Volume 3
International Journal of Machine Learning and Cybernetics : Volume 2
International Journal of Machine Learning and Cybernetics : Volume 1

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International journal of machine learning and cybernetics

Article

Parameter optimization of multi-pass turning using chaotic PSO

Content Provider SpringerLink
Author Chauhan, Pinkey Pant, Millie Deep, Kusum
Copyright Year 2014
Abstract Determination of an optimal set of machining parameters is needed to produce an ordered product of considerable quality and minimal manufacturing cost. The nonlinear and highly constrained nature of machining models restricts the application of classical gradient based techniques for handling such problems. The present study focuses on obtaining the optimal machining conditions during multi-pass turning operations. Methodology used is, a chaotic PSO namely Totally Disturbed Particle Swarm Optimization (TDPSO), an enhanced variant of PSO is employed for obtaining the optimal machining conditions during multi-pass turning operations subject to various constraints. In TDPSO, the phenomenon of chaos is embedded at different stages of PSO in order to make the search process more efficient. Results obtained by TDPSO are compared with results available in literature and it is observed that TDPSO is quite efficient for dealing with such problems.
Starting Page 319
Ending Page 337
Page Count 19
File Format PDF
ISSN 18688071
Journal International Journal of Machine Learning and Cybernetics
Volume Number 6
Issue Number 2
e-ISSN 1868808X
Language English
Publisher Springer Berlin Heidelberg
Publisher Date 2014-01-03
Publisher Place Berlin, Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Multi-pass turning Process parameters Constrained optimization Chaotic PSO Computational Intelligence Artificial Intelligence (incl. Robotics) Control, Robotics, Mechatronics Statistical Physics, Dynamical Systems and Complexity Systems Biology Pattern Recognition
Content Type Text
Resource Type Article
Subject Artificial Intelligence Computer Vision and Pattern Recognition Software
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