Data-driven modelling: some past experiences and new approaches
IHE Delft Institute for Water Education · Technion – Israel Institute of Technology
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…
Citation impact
- FWCI
- 13.91
- Percentile
- 100%
- References
- 108
Authors
2Topics & keywords
- Process (computing)
- Computer science
- Data science
- Management science
- Hydrological modelling
- Current (fluid)
- Data management
- Structural basin
- Clean water and sanitation