Title :
A Method of Weather Cases Generation Based on Similarity Rough Set
Author :
Ji, Sai ; Yuan, Shenfang ; Yue, Jian
Author_Institution :
Dept. of Comput. Sci. & Technol., Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
Abstract :
Case selection from weather database is a key step in disaster weather forecasts based on CBR. The selection of representative weather cases without noise and reduces time and space complexity is its essential target. This paper proposes the SRS algorithm based on similarity-based rough set theory. By reducing undirected graph, it can select a reasonable number of the typical cases from a large data set for future case-based reasoning tasks. It also can handle noise and inconsistent data. Experimental result has confirmed the algorithm feasibility and the validity.
Keywords :
case-based reasoning; rough set theory; weather forecasting; CBR; SRS algorithm; case-based reasoning; disaster weather forecasts; similarity rough set; undirected graph; weather cases generation; weather database; Computer science; Information retrieval; Information science; Information systems; Materials science and technology; Noise reduction; Rough sets; Set theory; Space technology; Weather forecasting;
Conference_Titel :
Management and Service Science, 2009. MASS '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4638-4
Electronic_ISBN :
978-1-4244-4639-1
DOI :
10.1109/ICMSS.2009.5302086
