Clustering of solar radiation
For the past years, the clustering and predication of solar radiation has been an interesting research field in time series analysis. In today technologies, the use of solar energy is commonly found in many applications and it will be easy to improve the efficiency of the applications with an accura...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2013
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| Online Access: | http://hdl.handle.net/10356/52999 |
| _version_ | 1826116901552521216 |
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| author | Ho, Chung. |
| author2 | Chan Chee Keong |
| author_facet | Chan Chee Keong Ho, Chung. |
| author_sort | Ho, Chung. |
| collection | NTU |
| description | For the past years, the clustering and predication of solar radiation has been an interesting research field in time series analysis. In today technologies, the use of solar energy is commonly found in many applications and it will be easy to improve the efficiency of the applications with an accurate solar clustering and prediction input model. As such, to have an accurate prediction model, it is very important to have a good cluster and segmentation pattern as the initial requirement. With this objective set, I will be implementing a new approach using a combination model consists of K-means clustering method and Genetic Algorithm (GA) to obtain a good cluster and segmentation pattern for the prediction of solar radiation time series. A series of simulation results were obtained using various GA options setting. The best cluster size and segmentation pattern were obtained using the new approach. Best result obtained from the new approach has a good validity index and will improve the prediction outcome in the subsequence project. |
| first_indexed | 2024-10-01T04:19:01Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/52999 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:19:01Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/529992023-07-07T17:12:17Z Clustering of solar radiation Ho, Chung. Chan Chee Keong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence For the past years, the clustering and predication of solar radiation has been an interesting research field in time series analysis. In today technologies, the use of solar energy is commonly found in many applications and it will be easy to improve the efficiency of the applications with an accurate solar clustering and prediction input model. As such, to have an accurate prediction model, it is very important to have a good cluster and segmentation pattern as the initial requirement. With this objective set, I will be implementing a new approach using a combination model consists of K-means clustering method and Genetic Algorithm (GA) to obtain a good cluster and segmentation pattern for the prediction of solar radiation time series. A series of simulation results were obtained using various GA options setting. The best cluster size and segmentation pattern were obtained using the new approach. Best result obtained from the new approach has a good validity index and will improve the prediction outcome in the subsequence project. Bachelor of Engineering 2013-05-29T07:08:01Z 2013-05-29T07:08:01Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/52999 en Nanyang Technological University 51 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Ho, Chung. Clustering of solar radiation |
| title | Clustering of solar radiation |
| title_full | Clustering of solar radiation |
| title_fullStr | Clustering of solar radiation |
| title_full_unstemmed | Clustering of solar radiation |
| title_short | Clustering of solar radiation |
| title_sort | clustering of solar radiation |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
| url | http://hdl.handle.net/10356/52999 |
| work_keys_str_mv | AT hochung clusteringofsolarradiation |