Design and development of an emulated human cognition using novel 3D neural networks

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dc.contributor.authorZiarati, Martin
dc.contributor.authorZiarati, Reza
dc.contributor.authorAkdemir, Başak
dc.contributor.authorBilgili, Erdem
dc.date.accessioned2015-09-22T15:53:44Z
dc.date.available2015-09-22T15:53:44Z
dc.date.issued2013-09-19
dc.description.abstractThis paper describes the development of an Emulated Human Cognition (EHC) which is designed and based on a replicated human brain with a right- and a left- hand lobe, one a deductive side and the other a generic one. Right-hand lobe consists of a newly designed Artificial Neural Network (ANN) with a multi-hidden layer topology. Left-hand lobe is a newly designed 3-dimensional cellular neural network. The input variables presented to the EHC are immediately analysed for it to decide which lobe should be activated. The EHC, when fully developed, has almost an unlimited memory capacity and is capable of immediate recall of any data in its almost unlimited memory locations. EHC has been used in several applications where neural networks have been used to establish relationship between two or more sets of variables. In this paper the EHC has been used to forecast demand for a given product.en_UK
dc.identifier.citationZiarati M., Akdemir B., Ziarati R. and Bilgili E. (2013). Design and development of an emulated human cognition using novel 3D neural networks. Proceedings of the 11th International Conference on Manufacturing Research (ICMR2013), Cranfield University, UK, 19th – 20th September 2013, pp 145-150en_UK
dc.identifier.isbn9781907413230
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/9453
dc.language.isoenen_UK
dc.publisherCranfield University Pressen_UK
dc.relation.ispartofseriesUncertainty and Modellingen_UK
dc.relation.ispartofseries6en_UK
dc.subjectforecastingen_UK
dc.subject3D neural networksen_UK
dc.subjectartificial neural networksen_UK
dc.subjectcellular neural networken_UK
dc.titleDesign and development of an emulated human cognition using novel 3D neural networksen_UK
dc.typeConference paperen_UK

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International Conference on Manufacturing Research (ICMR 2013)