By Topic

Neuro-fuzzy approaches to collaborative scientific computing

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Ramakrishnan, N. ; Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA ; Joshi, A. ; Houstis, E.N. ; Rice, J.R.

Rapid advances in high performance computing (HPC) and the Internet are heralding a paradigm shift to network-based scientific software servers, libraries, repositories and problem solving environments. According to this new paradigm, vital pieces of software and information required for a computation are distributed across a network and need to be identified and `linked' together at run time; this implies a `net-centric' and collaborative scenario for scientific computing. This scenario requires the application to dynamically choose the best among several competing resources that can solve a given problem. For these systems to become ubiquitous, efficient mechanisms for collaboration and automatic inference of the abilities of multiple `compute servers' need to be established. The authors demonstrate a methodology to facilitate collaborative scientific computing. Their idea is comprised of (i) a concept of `reasonableness' to automatically generate exemplars for learning the mapping from problems to `servers' and (ii) a neuro-fuzzy technique developed earlier by the authors that conducts supervised classification on the exemplars generated. The techniques work in an on-line manner and cater to mutually non-exclusive classes which are critical in the collaborative networked computing landscape

Published in:

Neural Networks,1997., International Conference on  (Volume:1 )

Date of Conference:

9-12 Jun 1997