1. Data-driven modelling: some past experiences and new approaches.
- Author
-
Solomatine, Dimitri P. and Ostfeld, Avi
- Subjects
- *
WATERSHEDS , *WATERSHED management , *MODELS & modelmaking , *HYDRAULIC models , *HYDROLOGIC models , *ENGINEERING models , *SIMULATION methods & models , *COMPUTATIONAL intelligence , *MACHINE learning , *ARTIFICIAL neural networks - Abstract
Physically based (process) models based on mathematical descriptions of water motion are widely used in river basin management. During the last decade the so-called data-driven models are becoming more and more common. These models rely upon the methods of computational intelligence and machine learning, and thus assume the presence of a considerable amount of data describing the modelled system's physics (i.e. hydraulic and/or hydrologic phenomena). This paper is a preface to the special issue on Data Driven Modelling and Evolutionary Optimization for River Basin Management, and presents a brief overview of the most popular techniques and some of the experiences of the authors in data-driven modelling relevant to river basin management. It also identifies the current trends and common pitfalls, provides some examples of successful applications and mentions the research challenges. [ABSTRACT FROM AUTHOR]
- Published
- 2008
- Full Text
- View/download PDF