NDLI: Redundancy reduction in environmental data set by means of an unsupervised neural networks

Content Provider	IEEE Xplore Digital Library
Author	Chiarantoni, E. Fornarelli, G. Vergura, S.
Copyright Year	2002
Description	Author affiliation: Dipt. di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy (Chiarantoni, E.; Fornarelli, G.; Vergura, S.)
Abstract	The acquisition of environmental data, like pollution and/or meteorological data requires the processing of a huge amount of heterogeneous data from external fields. As the number of monitoring points grows, we need a strategy to validate the acquired data and to efficiently utilize the transmission resources. An efficient way to obtain the validation-compression of the data sets is the adoption of a restricted set of samples (templates) that describe, with an assigned accuracy the whole data set. The aim of the work is to propose a validation-compression technique based on features, extracted by means of an unsupervised neural network. The paper reports the results obtained utilizing the above procedure to a real data set of a chemical pollutant. It is shown that the validation process allows a correct identification of corrupted and/or anomalous data, comparable with the human validation. Moreover the process allows a considerable reduction of transmitted data as the compression process profits the local processing of redundant data.
Sponsorship	IEEE IEEE Neural Networks Soc. (NNS) Int. Neural Network Soc
Starting Page	412
Ending Page	416
File Size	345672
Page Count	5
File Format	PDF
ISBN	0780372786
ISSN	10987576
DOI	10.1109/IJCNN.2002.1005507
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-05-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent networks Neural networks Pollution Feature extraction Humans Meteorology Data mining Chemicals Monitoring Rain
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
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
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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