• Corpus ID: 229924149

Unsupervised Real Time Prediction of Faults Using the Support Vector Machine

  title={Unsupervised Real Time Prediction of Faults Using the Support Vector Machine},
  author={Zhiyuan Chen and Dino Isa and Nik Ahmad Akram},
The research and development of Mission Critical System such as national communication system, national grid system and oil and gas pipeline network has been a great concern. Many innovative technologies have provided solutions and applications to the stability and continuous system operation. However a minute of interruption may cost millions of dollars and there were a lot of incident cases, which have brought bad impact to the economy. Therefore the purpose of this project is to design and… 



An Efficient Implementation of an Active Set Method for SVMs

The results show that the proposed active set algorithm to solve the convex quadratic programming (QP) problem has overall better performance on many SVM problems and seems to have a particularly strong advantage on more difficult problems.

Active-Set Methods for Support Vector Machines

This chapter describes an active-set algorithm for the solution of quadratic programming problems in the context of Support Vector Machines, derived for classification and regression problems for both fixed and variable bias term.

Introduction to Support Vector Machines

Support Vector Machines (SVM’s) are intuitive, theoretically wellfounded, and have shown to be practically successful.

Hybrid MPI/OpenMP Parallel Linear Support Vector Machine Training

A parallel implementation of linear Support Vector Machine training has been developed, using a combination of MPI and OpenMP, and it is demonstrated that the hybrid version performs more efficiently than the version using pure MPI.

Support Vector Machines: Theory and Applications

The goal of the chapter is to present an overview of the background theory and current understanding of SVM, and to discuss the papers presented as well as the issues that arose during the workshop.

Computational Intelligence Techniques

The chapter explains the computational intelligence techniques utilized in the algorithms presented in the book. The fuzzy and rough sets, fuzzy-rough sets, genetic algorithm and, feature selection

SOM-based data visualization methods

π-ADL: an Architecture Description Language based on the higher-order typed π-calculus for specifying dynamic and mobile software architectures

π-ADL is described, a novel ADL that has been designed in the ArchWare European Project to address specification of dynamic and mobile architectures and is a formal, well-founded theoretically language based on the higher-order typed π-calculus.

A control architecture for quadruped locomotion over rough terrain

This paper presents a hierarchical control architecture that enables a quadruped, the "LittleDog" robot, to walk over rough terrain, and highlights several elements of the controller that were found to be particularly crucial for robust locomotion, and which are applicable to quadruped robots in general.

Computational Intelligence Techniques", book chapter, Computational Intelligence for Movement Sciences: Neural Networks and other Emerging Techniques, Ed

  • Begg RK & Palaniswami M. IGI Publishing,
  • 2006