Clustering and deep learning approaches for modelling and prediction of nonlinear systems

dc.contributor.guide	Srivastava, Smriti
dc.coverage.spatial
dc.creator.researcher	Singh, Saumya
dc.date.accessioned	2025-11-18T11:45:49Z
dc.date.available	2025-11-18T11:45:49Z
dc.date.awarded	2025
dc.date.completed	2025
dc.date.registered	2019
dc.description.abstract	newline
dc.description.note
dc.format.accompanyingmaterial	DVD
dc.format.dimensions	21 cm X 29 cm
dc.format.extent	xvii, 196
dc.identifier.researcherid	0009-0009-2443-3939
dc.identifier.uri	http://hdl.handle.net/10603/674507
dc.language	English
dc.publisher.institution	Instrumentation and Control Engineering
dc.publisher.place	Delhi
dc.publisher.university	Netaji Subhas University of Technology
dc.relation	230
dc.rights	university
dc.source.university	University
dc.subject.keyword	Cluster analysis
dc.subject.keyword	Engineering
dc.subject.keyword	Engineering and Technology
dc.subject.keyword	Engineering Electrical and Electronic
dc.subject.keyword	Nonlinear systems
dc.subject.keyword	Spatial analysis (Statistics)
dc.title	Clustering and deep learning approaches for modelling and prediction of nonlinear systems
dc.title.alternative	Clustering and deep learning approaches for modelling and prediction of non-linear systems
dc.type.degree	Ph.D.