Prediction of rainfall intensity using artificial intelligence (AI) techniques in Singapore
This paper will be covering the usage of artificial intelligence techniques, mainly using non-linear autoregressive with external(exogenous) input (NARX) to predict rainfall intensity in Singapore some 5, 15 and 30 minutes intervals ahead. The time-series data will be analysed by using data mining t...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2019
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| Online Access: | http://hdl.handle.net/10356/78012 |
| _version_ | 1811683469631160320 |
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| author | Toh, Jia Yee |
| author2 | Chan Chee Keong |
| author_facet | Chan Chee Keong Toh, Jia Yee |
| author_sort | Toh, Jia Yee |
| collection | NTU |
| description | This paper will be covering the usage of artificial intelligence techniques, mainly using non-linear autoregressive with external(exogenous) input (NARX) to predict rainfall intensity in Singapore some 5, 15 and 30 minutes intervals ahead. The time-series data will be analysed by using data mining techniques. Then, it will be grouped into four different on and off monsoon seasons, which are later used as training data for different artificial neural networks. Different scenarios of neural network will be explored using MATLAB NARX to find the best accuracy for predicting the intensity of the rainfall events. |
| first_indexed | 2024-10-01T04:13:14Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/78012 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:13:14Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | ntu-10356/780122023-07-07T17:17:01Z Prediction of rainfall intensity using artificial intelligence (AI) techniques in Singapore Toh, Jia Yee Chan Chee Keong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering This paper will be covering the usage of artificial intelligence techniques, mainly using non-linear autoregressive with external(exogenous) input (NARX) to predict rainfall intensity in Singapore some 5, 15 and 30 minutes intervals ahead. The time-series data will be analysed by using data mining techniques. Then, it will be grouped into four different on and off monsoon seasons, which are later used as training data for different artificial neural networks. Different scenarios of neural network will be explored using MATLAB NARX to find the best accuracy for predicting the intensity of the rainfall events. Bachelor of Engineering (Electrical and Electronic Engineering) 2019-06-11T03:05:12Z 2019-06-11T03:05:12Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/78012 en Nanyang Technological University 54 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Toh, Jia Yee Prediction of rainfall intensity using artificial intelligence (AI) techniques in Singapore |
| title | Prediction of rainfall intensity using artificial intelligence (AI) techniques in Singapore |
| title_full | Prediction of rainfall intensity using artificial intelligence (AI) techniques in Singapore |
| title_fullStr | Prediction of rainfall intensity using artificial intelligence (AI) techniques in Singapore |
| title_full_unstemmed | Prediction of rainfall intensity using artificial intelligence (AI) techniques in Singapore |
| title_short | Prediction of rainfall intensity using artificial intelligence (AI) techniques in Singapore |
| title_sort | prediction of rainfall intensity using artificial intelligence ai techniques in singapore |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | http://hdl.handle.net/10356/78012 |
| work_keys_str_mv | AT tohjiayee predictionofrainfallintensityusingartificialintelligenceaitechniquesinsingapore |