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dc.contributor.authorSingh, Ashutosh Kumar-
dc.date.accessioned2014-12-07T06:43:37Z-
dc.date.available2014-12-07T06:43:37Z-
dc.date.issued2000-
dc.identifierM.Techen_US
dc.identifier.urihttp://hdl.handle.net/123456789/13563-
dc.guideVarma, U. S. P.-
dc.guideGodbole, P. N.-
dc.description.abstractConcrete is most widely used construction material because of its ability to take any shape while wet, and its strength development characteristics when it hardens. Concrete can be classified under two main categories — Normal concrete and High strength concrete. Normal concrete is defined as concrete having strength less than 50 MPa, whereas concrete having strength more than 50 MPa has been classified as High strength concrete. The requirement of high durability in addition to high strength resulted in development of I I igh performance concrete. The proportion of different ingredients of concrete is fixed through a process called Mix design. The mix design is carried out with the help of certain relationship between design parameters, established from past experiences. The IS:10262 provides guidelines for the mix design of concrete. Concrete mix design, on the basis of the recommended guidelines and established relationship, is really a process of making an initial guess at the optimum proportions of different ingredients and final mix proportions are arrived at on the basis of further trial mixes. Hence, the development of concrete mix requires a lot of trial and error, which consumes a lot of time and resources. "lo minimize the trial and error, in order to save the time and resource, artificial neural network can be• very effectively used in concrete mix design. An artificial neural network is a network inspired by neuronal structure and operation of human brain. It consists of many nodes, called as neurons, connected to each other. The connection between the neurons carries numeric data, called weights. These connection weights arc changed when the network is trained for a particular problem. Because of its capability to establish relationship between any input and output patterns, it is a promising tool for those problems where the solution algorithm is unknown or very complex. In present dissertation work, the application of ANN has been studied in area of Concrete Mix Design.en_US
dc.language.isoenen_US
dc.subjectCIVIL ENGINEERINGen_US
dc.subjectARTIFICIAL NEURAL NETWORKSen_US
dc.subjectCONCRETE MIX DESIGNen_US
dc.subjectAPPLICATION CONCRETE MIX DESIGNen_US
dc.titleAPPLICATION OF ARTIFICIAL NEURAL NETWORKS IN CONCRETE MIX DESIGNen_US
dc.typeM.Tech Dessertationen_US
dc.accession.numberG10140en_US
Appears in Collections:MASTERS' THESES (Civil Engg)

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