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Title: Clustering of solar radiation
Authors: Ho, Chung.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2013
Abstract: 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.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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