Techniques to develop forecasting model on low cost housing in urban area
The number of people who will live in urban areas is expected to double to more than five billion between 1990 to 2025. Therefore, accurate predictions of the level of aggregate demand for housing are very important. Various forecasting techniques have been developed using probabilistic, statistics,...
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| Format: | Article |
| Language: | English |
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Faculty of Civil Engineering
2002
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| Online Access: | http://eprints.utm.my/2063/ http://eprints.utm.my/2063/1/NoorYasminZainun2002_TechniquesToDevelopForecastingModel.pdf |
| _version_ | 1848890277714984960 |
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| author | Zainun, Noor Yasmin Abd. Majid, Muhd. Zaimi |
| author_facet | Zainun, Noor Yasmin Abd. Majid, Muhd. Zaimi |
| author_sort | Zainun, Noor Yasmin |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | The number of people who will live in urban areas is expected to double to more than five billion between 1990 to 2025. Therefore, accurate predictions of the level of aggregate demand for housing are very important. Various forecasting techniques have been developed using probabilistic, statistics, simulation or artificial intelligent. Hence, there is a need to identify different techniques, in terms of accuracy, in the prediction of needs for facilities. This paper discusses the Artificial Neural Networks (ANN) technique and compaes it with other techniques in forecasting needs of housing in urban area. Investigation on previous research and literature materials will be derived and compared in terms of errors in the accuracy of the technique. The findings of this study indicates that the ANN model performs best overall |
| first_indexed | 2025-11-15T20:39:31Z |
| format | Article |
| id | utm-2063 |
| institution | Universiti Teknologi Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:39:31Z |
| publishDate | 2002 |
| publisher | Faculty of Civil Engineering |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utm-20632010-09-28T02:33:54Z http://eprints.utm.my/2063/ Techniques to develop forecasting model on low cost housing in urban area Zainun, Noor Yasmin Abd. Majid, Muhd. Zaimi TA Engineering (General). Civil engineering (General) The number of people who will live in urban areas is expected to double to more than five billion between 1990 to 2025. Therefore, accurate predictions of the level of aggregate demand for housing are very important. Various forecasting techniques have been developed using probabilistic, statistics, simulation or artificial intelligent. Hence, there is a need to identify different techniques, in terms of accuracy, in the prediction of needs for facilities. This paper discusses the Artificial Neural Networks (ANN) technique and compaes it with other techniques in forecasting needs of housing in urban area. Investigation on previous research and literature materials will be derived and compared in terms of errors in the accuracy of the technique. The findings of this study indicates that the ANN model performs best overall Faculty of Civil Engineering 2002 Article PeerReviewed application/pdf en http://eprints.utm.my/2063/1/NoorYasminZainun2002_TechniquesToDevelopForecastingModel.pdf Zainun, Noor Yasmin and Abd. Majid, Muhd. Zaimi (2002) Techniques to develop forecasting model on low cost housing in urban area. Jurnal Kejuruteraan Awam, 14 (1). pp. 36-46. ISSN 0128-0147 http://web.utm.my/ipasa/index.php?option=content&task=view&id=771&Itemid= |
| spellingShingle | TA Engineering (General). Civil engineering (General) Zainun, Noor Yasmin Abd. Majid, Muhd. Zaimi Techniques to develop forecasting model on low cost housing in urban area |
| title | Techniques to develop forecasting model on low cost housing in urban area |
| title_full | Techniques to develop forecasting model on low cost housing in urban area |
| title_fullStr | Techniques to develop forecasting model on low cost housing in urban area |
| title_full_unstemmed | Techniques to develop forecasting model on low cost housing in urban area |
| title_short | Techniques to develop forecasting model on low cost housing in urban area |
| title_sort | techniques to develop forecasting model on low cost housing in urban area |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://eprints.utm.my/2063/ http://eprints.utm.my/2063/ http://eprints.utm.my/2063/1/NoorYasminZainun2002_TechniquesToDevelopForecastingModel.pdf |