Tool wear monitoring and prognostics challenges: a comparison of connectionist methods toward an adaptive ensemble model

This publication has 40 references indexed in Scilit:

• The evolutionary development of roughness prediction models
  Applied Soft Computing, 2013
• Ensemble of data-driven prognostic algorithms for robust prediction of remaining useful life
  Reliability Engineering & System Safety, 2012
• Prognostic modelling options for remaining useful life estimation by industry
  Mechanical Systems and Signal Processing, 2011
• Extreme learning machines: a survey
  International Journal of Machine Learning and Cybernetics, 2011
• Tool wear monitoring and selection of optimum cutting conditions with progressive tool wear effect and input uncertainties
  Journal of Intelligent Manufacturing, 2009
• Enhanced random search based incremental extreme learning machine
  Neurocomputing, 2008
• Prediction of Melting Points of Organic Compounds Using Extreme Learning Machines
  Industrial & Engineering Chemistry Research, 2008
• Convex incremental extreme learning machine
  Neurocomputing, 2007
• Universal Approximation using Incremental Constructive Feedforward Networks with Random Hidden Nodes
  IEEE Transactions on Neural Networks, 2006
• On-line wear estimation using neural networks
  Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 1998