Applying Data Mining and HPC for Water Quality Assessment and Prediction

摘要：

Water quality assessment and prediction of Lake Michigan are becoming major challenges in Northwest Indiana. Traditionally, mechanistic simulation models are employed for water quality modeling and prediction. However, given the complicate nature of Lake Michigan in Northwestern Indiana, the detailed simulation model is extremely simple in comparison and, at some point, additional detail exceeds our ability to simulate and predict with reasonable error levels. In this regard, this research applied data mining technologies, as an innovative alternative, to develop an easy and more accurate approach for water quality assessment and prediction. The drawback of the data mining modeling is that the execution takes quite long time, especially when we employ a better accuracy but more time consuming algorithm in clustering. Therefore, we applied the High Performance Computing System of the Northwest Indiana Computational Grid to deal with this problem. The experiments have achieved very promising results. The visualized water quality assessment and prediction obtained from the research are published in an interactive website so that the public and the environmental managers can use the information for their decision making.

关键词： WaterQuality DataMining Clustering Classification Decision Tree High Performance Computing

作者: Ruijian Zhang Hairong Zhao Yong Piao

作者单位: Purdue University Calumet Hammond,IN, USA

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Advanced Computer Control(2011年IEEE第三届高端计算机控制国际会议 ICACC2011)

会议地点: 哈尔滨

会议语种:英文

页码: 487-491

在线出版日期: 2011-01-18（万方平台首次上网日期，不代表论文的发表时间）