Hybrid Rule and Neural Network Based Framework for Ubiquitous Computing
One of most perspective techniques for sensing in ubiquitous computing systems is neural networks. But for a prior knowledge representation it is most appropriate to employ rule based techniques. So usage of hybrid intelligent systems based on combination of neural networks and rule based techniques...
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description | One of most perspective techniques for sensing in ubiquitous computing systems is neural networks. But for a prior knowledge representation it is most appropriate to employ rule based techniques. So usage of hybrid intelligent systems based on combination of neural networks and rule based techniques seems perspective for development of smart environment. In this paper features of hybridization in smart environment are described and usage of technology of hybrid expert systems based on shell ESWin is proposed. |
doi_str_mv | 10.1109/NCM.2008.129 |
format | Conference Proceeding |
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But for a prior knowledge representation it is most appropriate to employ rule based techniques. So usage of hybrid intelligent systems based on combination of neural networks and rule based techniques seems perspective for development of smart environment. 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But for a prior knowledge representation it is most appropriate to employ rule based techniques. So usage of hybrid intelligent systems based on combination of neural networks and rule based techniques seems perspective for development of smart environment. In this paper features of hybridization in smart environment are described and usage of technology of hybrid expert systems based on shell ESWin is proposed.</description><subject>Artificial intelligence</subject><subject>Artificial neural networks</subject><subject>Ferroelectric films</subject><subject>Hybrid Intelligent Systems</subject><subject>Knowledge based Systems</subject><subject>Neural Networks</subject><subject>Nonvolatile memory</subject><subject>Random access memory</subject><subject>Rules</subject><subject>Sensors</subject><subject>Smart Environment</subject><subject>Ubiquitous Computing</subject><isbn>0769533221</isbn><isbn>9780769533223</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjr1OwzAURi2hStDSjY3FL5Dge53YuSNEtEUqRUJ0ruzYQYakKU4i1Ldv-ZmOvjN8OozdgEgBBN1tyucUhShSQLpgU6EV5VIiwoRNfzxhITVdsnnffwghgJQWhFdsuTraGBx_HRvPzd7xjR-jac4Yvrv4yR9M7x1fRNP63113kW9t-BrD0I09L7v2MA5h_37NJrVpej__54xtF49v5SpZvyyfyvt1EhDkkBDKzGItKlWAcrXCSkmqBOlzn9OalEGrrasynZMltFkFIH1us9oZmRuQM3b79xu897tDDK2Jx12mMAMCeQLxdUqZ</recordid><startdate>200809</startdate><enddate>200809</enddate><creator>Gavrilov, A.V.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200809</creationdate><title>Hybrid Rule and Neural Network Based Framework for Ubiquitous Computing</title><author>Gavrilov, A.V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i213t-9234b2f0c6816df62c639c097928d7796a2b7bdc4759b92b4c113e5b4fda35a13</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Artificial intelligence</topic><topic>Artificial neural networks</topic><topic>Ferroelectric films</topic><topic>Hybrid Intelligent Systems</topic><topic>Knowledge based Systems</topic><topic>Neural Networks</topic><topic>Nonvolatile memory</topic><topic>Random access memory</topic><topic>Rules</topic><topic>Sensors</topic><topic>Smart Environment</topic><topic>Ubiquitous Computing</topic><toplevel>online_resources</toplevel><creatorcontrib>Gavrilov, A.V.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gavrilov, A.V.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Hybrid Rule and Neural Network Based Framework for Ubiquitous Computing</atitle><btitle>2008 Fourth International Conference on Networked Computing and Advanced Information Management</btitle><stitle>NCM</stitle><date>2008-09</date><risdate>2008</risdate><volume>2</volume><spage>488</spage><epage>492</epage><pages>488-492</pages><isbn>0769533221</isbn><isbn>9780769533223</isbn><abstract>One of most perspective techniques for sensing in ubiquitous computing systems is neural networks. But for a prior knowledge representation it is most appropriate to employ rule based techniques. So usage of hybrid intelligent systems based on combination of neural networks and rule based techniques seems perspective for development of smart environment. In this paper features of hybridization in smart environment are described and usage of technology of hybrid expert systems based on shell ESWin is proposed.</abstract><pub>IEEE</pub><doi>10.1109/NCM.2008.129</doi><tpages>5</tpages><oa>free_for_read</oa></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Artificial intelligence Artificial neural networks Ferroelectric films Hybrid Intelligent Systems Knowledge based Systems Neural Networks Nonvolatile memory Random access memory Rules Sensors Smart Environment Ubiquitous Computing |
title | Hybrid Rule and Neural Network Based Framework for Ubiquitous Computing |
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