Publication:
An Application of artificial neural networks for rainfall forecasting. December 1998.
An Application of artificial neural networks for rainfall forecasting. December 1998.
dc.contributor.author | Luk, K. C. | en_US |
dc.contributor.author | Ball, J. E. | en_US |
dc.contributor.author | Sharma, A. | en_US |
dc.date.accessioned | 2021-11-25T12:40:50Z | |
dc.date.available | 2021-11-25T12:40:50Z | |
dc.date.issued | 1998 | en_US |
dc.description.abstract | Development of artificial neural networks (ANN) for rainfall forecasting. A four stage network development procedure is adopted which involves identifying appropriate networks, determinig network complexity, estimating parameters and evaluating performance. Particular emphasis is made on the generalization issue of complex networks with large parameters. The upper Parramatta River catchment is used as a test case to compare the three alternative ANN, namely multi-layer feedforward network (MLFN), partial recurrent neural network (PRNN) and time delay neural network (TDNN). It was found that with careful development, the three alternative types of network could produce reasonable predictions of the rainfall depth one time-step (15 min) in advance. In addition, various ways to improve the accuracy of forecasts were attempted. By integrating an ANN with a spatial model developed within a Geographical Information System environment, the rainfall forecasting model was able to forecast the spatially distributed rainfall patterns one time-step ahead for the study catchment. | en_US |
dc.identifier.isbn | 0959240319 | en_US |
dc.identifier.uri | http://hdl.handle.net/1959.4/36222 | |
dc.language | English | |
dc.language.iso | EN | en_US |
dc.publisher | University of New South Wales - Water Research Laboratory | en_US |
dc.rights | CC BY-NC-ND 3.0 | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/au/ | en_US |
dc.source | Legacy MARC | en_US |
dc.source | WRL Digitisation | |
dc.subject.other | neural networks | en_US |
dc.subject.other | rainfall | en_US |
dc.subject.other | forecasting | en_US |
dc.subject.other | spatial distribution | en_US |
dc.subject.other | Parramatta River | en_US |
dc.subject.other | Australian research Council ARC | en_US |
dc.title | An Application of artificial neural networks for rainfall forecasting. December 1998. | en_US |
dc.type | Report | en |
dcterms.accessRights | open access | |
dspace.entity.type | Publication | en_US |
unsw.accessRights.uri | https://purl.org/coar/access_right/c_abf2 | |
unsw.description.notePublic | Number of pages: 171pp | en_US |
unsw.identifier.doi | https://doi.org/10.4225/53/57a4181590631 | en_US |
unsw.publisher.place | Sydney | en_US |
unsw.relation.faculty | Engineering | |
unsw.relation.ispartofreportnumber | UNSW Water Research Laboratory Report No. 194 | en_US |
unsw.relation.originalPublicationAffiliation | Luk, K. C., Water Research Laboratory, UNSW | en_US |
unsw.relation.originalPublicationAffiliation | Ball, J. E., Water Research Laboratory, UNSW | en_US |
unsw.relation.originalPublicationAffiliation | Sharma, A., Water Research Laboratory, UNSW | en_US |
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