Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/69250
Title: การพัฒนาระบบพยากรณ์การเคลื่อนที่ของเมฆโดยใช้ภาพถ่ายผ่านดาวเทียมและเซนเซอร์ทางกายภาพ
Other Titles: Development of Cloud Movement Prediction Using Satellite Image and Physical Sensor
Authors: อาจารย์ ดร.ภาสกร แช่มประเสริฐ
จตุรัฐ คำขาว
Issue Date: Apr-2016
Publisher: เชียงใหม่ : บัณฑิตวิทยาลัย มหาวิทยาลัยเชียงใหม่
Abstract: This independent study is to develop and test a cloud movement prediction model applying an artificial neural network using data from satellite images and physical sensors. The predicted cloud images in Muang, Chiang Mai area for the next hour and three hours are generated from the proposed prediction methods. There are two prediction methods, which are 1) absolute pixel image input, and 2) relative pixel image input. Each method conducts with four scenarios, according to physical sensors and prediction periods. Four scenarios are 1) scenario-1: the prediction with data from satellite images and physical sensors for next hour, 2) scenario-2: the prediction with only data from satellite images for next hour, 3) scenario-3: the prediction with data from satellite images and physical sensors for next three hours, and 4) scenario-4: the prediction with only data from satellite images for next three hours. The results show that the prediction using absolute pixel image is more accurate than using relative pixel image but the absolute pixel image method is much slower than the other for training network and testing. Scenario-1 is the most accurate prediction, the average mean squared error (MSE) is 0.0096. The comparison between next hour and three hours prediction found an hour is more accurate than three hours, the average MSE is 0.0132. Using physical sensors data is more accurate than not using, the average MSE is 0.0180.
URI: http://cmuir.cmu.ac.th/jspui/handle/6653943832/69250
Appears in Collections:ENG: Independent Study (IS)

Files in This Item:
File Description SizeFormat 
Full.pdf4 MBAdobe PDFView/Open    Request a copy


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.