Intelligent techniques for spatio-temporal data analysis in environmental applications

dc.contributor.author	Βασιλάς, Νικόλαος	el
dc.contributor.author	Καλαπανίδας, Ηλίας	el
dc.contributor.author	Αβούρης, Νικόλαος	el
dc.contributor.author	Περαντώνης, Σταύρος	el
dc.date.accessioned	2015-05-11T23:19:02Z
dc.date.available	2015-05-11T23:19:02Z
dc.date.issued	2015-05-12
dc.identifier.uri	http://hdl.handle.net/11400/10181
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://link.springer.com/chapter/10.1007%2F3-540-44673-7_21	en
dc.subject	Ευφυείς τεχνικές
dc.subject	Χωροχρονική ανάλυση δεδομένων
dc.subject	Περιβαλλοντικές Εφαρμογές
dc.subject	Intelligent Techniques
dc.subject	Spatio-Temporal Data Analysis
dc.subject	Environmental Applications
dc.title	Intelligent techniques for spatio-temporal data analysis in environmental applications	en
heal.type	bookChapter
heal.generalDescription	σε έντυπη μορφή στο γραφείο μου	el
heal.classification	Πληροφορική
heal.classification	Μηχανική υπολογιστών
heal.classification	Computer science
heal.classification	Computer engineering
heal.classificationURI	N/A-Πληροφορική
heal.classificationURI	N/A-Μηχανική υπολογιστών
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85029495
heal.identifier.secondary	DOI: 10.1007/3-540-44673-7_21
heal.language	en
heal.access	campus
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Πληροφορικής Τ.Ε.	el
heal.publicationDate	2001-09-20
heal.bibliographicCitation	Vassilas, N., Kalapanidas, E., Avouris, N. and Perantonis, S. (2001) Intelligent Techniques for Spatio-Temporal Data Analysis in Environmental Applications. In: Paliouras, G., Karkaletsis, V. and Spyropoulos, C. (eds). Machine Learning and Its Applications. Springer Berlin Heidelberg.	en
heal.abstract	Environmental applications share common features that make them distinct from typical applications of other areas of applied computer science. This fact has lead during the last years to the development of Environmental Informatics, a novel specialty of Applied Informatics, which studies specific problems related with the application of computer science techniques in environmental problems. In environmental applications often many different, non homogeneous information sources can be found, such as text data e.g. environmental legislation or research projects results, measurement data from monitoring networks, structural data on chemical substances, satellite data etc. In particular, environmental data is often geographically coded, i.e. information is attached to a particular point or region in space. Secondly, some of the data objects are multidimensional and have to be represented by means of complex geometric objects (polygons or curves).	en
heal.publisher	Springer Berlin Heidelberg	en
heal.fullTextAvailability	true
heal.bookName	Machine Learning and Its Applications	en