NDLI: Pulp digester level prediction using multiresolution networks of locally active units

Content Provider	IEEE Xplore Digital Library
Author	Fern, A. Miranda, J. Musavi, M.T. Coughlin, D.R.
Copyright Year	1997
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Maine Univ., Orono, ME, USA (Fern, A.)
Abstract	Complex processes such as those found in some manufacturing plants have many dynamically related variables which interact to produce a system response. The goal of system identification is to construct a model of a complex process, based on observations, in order to predict future system responses and help improve its control. In this research, neural networks constructed with multiresolution locally active units are used to model the content level of a paper plant pulp digester. This problem represents a real world multidimensional dynamic system for which a predictive model does not yet exist. Two local networks are considered which use radial basis functions (RBF) and utilize the concept of multiresolution analysis (MRA). The networks differ in the way each generates an MRA candidate node set from which the most important nodes are selected for the approximation using a fast orthogonal search (FOS) algorithm. The MRA networks are compared to each other and are also shown to produce approximations using fewer nodes than those obtained using a standard RBF architecture. This report demonstrates that locally active MRA networks produce promising results for the system identification task of digester level prediction.
Starting Page	633
Ending Page	638
File Size	492841
Page Count	6
File Format	PDF
ISBN	0780341228
DOI	10.1109/ICNN.1997.616095
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-06-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Function approximation System identification Predictive models Artificial neural networks Computer aided manufacturing Neural networks Testing Intelligent manufacturing systems Laboratories Manufacturing processes
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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