- author = "He Ji and Wang Songlin and Wu Qinglin and Chen Xiaonan",
- title = "Douhe Reservoir Flood Forecasting Model Based on Data Mining Technology",
- journal = "Procedia Environmental Sciences",
- year = "2012",
- volume = "12, Part A",
- pages = "93--98",
- note = "2011 International Conference of Environmental Science and Engineering",
- keywords = "genetic algorithms, genetic programming, ANN, Hydrological Forecasting, Data Mining Technology, Artificial Neural Networks",
- ISSN = "1878-0296",
-
URL = "
http://www.sciencedirect.com/science/article/pii/S1878029612002538",
-
DOI = "
doi:10.1016/j.proenv.2012.01.252",
- abstract = "Calculating flood based on rainfall is an important part of hydrological forecast. However, due to the diversity and complexity of factors affecting the relationship between rainfall and runoffs, using the perspective of mechanism to simulate the forming of flood through rainfall is often difficult. In this paper, flood forecast model is constructed based on Artificial Neural Networks (ANN) and Genetic Programming (GP), using actual data to mine the relationship among rainfall, pre rain and net rain, to avoid the flaws of constructing actual mathematical expression in advance, and automatically search for optimal structure. Practice has approved that applying data mining technique on flood forecasting of Douhe Reservoir is able to achieve outstanding results.",
-
notes = "ICESE2011
North China University of Water Resources and Electric Power, Zhengzhou 450011, China",
