Papers by Keyword: Water Bloom Prediction

Abstract: An integrated evaluative function and prediction model and prewarning system for water bloom in lakes based on Elman neural network is proposed in this paper, in which main influence factor of outbreak of water bloom is analyzed by rough set theory. The study of the function involves some aspects: algal average activation energy of photosynthesis, integrated nutritional status index, and transparency, which are considered from the microcosmic level, the macroscopic level and the intuitionistic level respectively. The values of the function are classified properly. Combined with the basic features of outbreak of water-bloom, Elman network is studied from the angles of theory and experiment and a water-bloom prewarning system in short term based on Elman network is established. The results of simulation and application show that: Elman neural network improves the algorithm of BP neural network, it has long-term prediction period, strong generalization ability， high prediction accuracy; and needs a small amount of sample and this model provides an efficient new way for short-term water bloom prediction, And approaching ability of Elman network is more superficial than common static networks and its velocity of convergence is faster.

Abstract: According to the urgent requirement of water quality monitoring, water bloom prediction and emergency treatment decision-making, a multi-functional information system based on GIS (Geographic Information System) is designed and developed, which integrates water quality monitoring and analysis, water bloom prediction and emergency treatment decision-making. VS2010 platform and SQL Server 2005 database are used in the system, and the remote data communication is realized by GPRS. The system has functions such as lakes and reservoirs’ water quality real-time monitoring, teletransmission and location, water quality data analysis, water bloom prediction and emergency treatment decision-making. The medium-term prediction of water bloom is realized by wavelet neural network, and the optimal choice of water bloom emergency treatment decision-making projects is realized by multi-attribute decision-making theory. This design offers effective decision-making system for environmental protection departments, which also has significant meaning to the protection and renovation of water environment, and its application and promotion have considerable social and economic benefits.