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Use of the artificial neural network and meteorological data for predicting daily global solar radiation in Djelfa, Algeria

date accessioned2020-03-12T19:58:38Z
date available2020-03-12T19:58:38Z
date issued2014
identifier other6843807.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/997273?show=full
formatgeneral
languageEnglish
publisherIEEE
titleUse of the artificial neural network and meteorological data for predicting daily global solar radiation in Djelfa, Algeria
typeConference Paper
contenttypeMetadata Only
identifier padid8117188
subject keywordsBayes methods
subject keywordscomputer network security
subject keywordsdecision trees
subject keywordslearning (artificial intelligence)
subject keywordspattern classification
subject keywordspublic domain software
subject keywordsBro open-source system
subject keywordsCART decision tree classifier
subject keywordsCorsaro open-source system
subject keywordsDDoS attacks
subject keywordsIP addresses
subject keywordsNIDS
subject keywordsNaive Bayes machine learning classifier
subject keywordsbackscatter darknet traffic
subject keywordsnetwork intrusion detection systems
subject keywordssupervised learning techniques
subject keywordsBackscatter
subject keywordsComputer crime
subject keywordsDecision trees
subject keywordsIP networks
subject keywordsPorts (Computers)
subject keywordsProtocols
subject keywordsTraining
subject keywordsBack
identifier doi10.1109/CICYBS.2014.7013367
journal titleomposite Materials & Renewable Energy Applications (ICCMREA), 2014 International Conference
filesize815072
citations0
contributor rawauthorAssas, O. , Bouzgou, H. , Fetah, S. , Salmi, M. , Boursas, A.


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