报告人：Alistair G.L. Borthwick  (The University of Edinburgh)

时  间：2019-05-31  10:00- 11:30

地  点：环境大楼B112

Abstract:  Data analytics aims to address challenges posed by large sets of (observed and simulated) unstructured data.  So-called ‘big data’ describes data of large Volume, Velocity, Variety, Veracity, Value, Volatility and Validity. In practice, such data are growing at a rate of about 40% per annum. Data analytics implies processes of pattern extraction used to formulate predictive relationships.  Approaches include machine learning techniques, data reduction, model emulation, and traditional statistical models.  The application of data analytics can enhance water resources analysis techniques (using cloud computing), lead to more efficient water-use and wastewater treatment, better forecasting of natural and human impacts, improve water security, and assist disaster management.  Potential drawbacks may arise from the amount of data where noise exceeds value, the creation of inaccurate information, lack of understanding by users, complexity, and violation of data privacy and security.  Environmental engineering is on the cusp of a digital revolution, led by data analytics and artificial intelligence.