1 / 18

CLOUD SEEDING

The Use of Neural Network in Determining the Ideality of Day for Cloud Seeding by Cuesta , Yvanne Christine R. Uy, Ma. Ro-anne R. CLOUD SEEDING. A type of weather modification

gary
Download Presentation

CLOUD SEEDING

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The Use of Neural Network in Determining the Ideality of Day for Cloud SeedingbyCuesta, Yvanne Christine R.Uy, Ma. Ro-anne R.

  2. CLOUD SEEDING • A type of weather modification • Treatment used to increase precipitation – to provide water on dams and agricultural fields during drought seasons

  3. CLOUD SEEDING OPERATION

  4. ISSUES • Requires large amount of funds • Doesn’t produce enough rain • Rain do not fall on the right location • Some believe that it does not work successfully at all… In other words… A large amount of money is wasted There is no established quantitative way of pursuing cloud seeding.

  5. Neural Network • information processing model inspired by the human brain • used in classification through pattern based learning

  6. Process Flowchart Acquisition and Compilation of Cloud Seeding Data • Acquisition and Programming of Implementing Software Conversion of data into data input Training of program Testing and Validation of Program

  7. Cloud Seeding Data

  8. Generated Values of Training Phase

  9. Generated Values of Training Phase

  10. Generated Values of Validation Phase

  11. Generated Values of Validation Phase

  12. Generated Values of Testing Phase

  13. Generated Values of Testing Phase

  14. Summary

  15. t-Test

  16. Conclusion • The ranges in which cloud seeding operations are likely to be successful • It is possible to establish a more accurate and precise way of predicting the ideality of Day for cloud seeding.

  17. Recommendations • Wide range of cloud seeding data wherein taking into consideration other factors besides from the given factors • Usage of BackpropagationNeural Network

  18. Bibliography • American Friends of Tel Aviv University (2010, November 1). 'Cloud seeding' not effective at producing rain as once thought, new research shows. ScienceDaily. Retrieved December 10, 2010, from http://www.sciencedaily.com­ /releases/2010/11/101101125949.htm • Hagan, M.T. (1996). Neural Network Design. Boston, MA: PWS Publishing. • Macfarlane, M. (2009, February 3). Major study proves cloud seeding effective.Cosmomagazine. Retrieved July 21, 2010 from http://www.cosmosmagazine.com/news/2514/major- study-proves-cloud-seeding-effective. • Matthew, J. (2000). An Introduction to Neural Networks. Retrieved July 21, 2010 from http://www.generation5.org/content/2000/nnintro.asp. • Moseman, A. (2009, February 19). Does cloud seeding work?. Scientific American. Retrieved August 11, 2010 from http://www.scientificamerican.com/article.cfm?id=cloud-seeding-china- snow • Shoukat, U. & Zakia, H. (2005). Improve an efficiency of feedforward multilayer perceptrons by Serial training. Journal of Theoretical and Applied Information Technology, 6(1), 017 – 020. Retrieved August 11, 2010 from http://www.jatit.org/volumes/research- papers/Vol6No1/2Vol6No1.pdf. • XLMiner (n.d.). Online Help. Retrieved January 22, 2011 from http://www.resample.com/xlminer/help/Index.htm

More Related