Practical Hydroinformatics Computational Intelligence and Technological Developments in Water Applications /
| Autor Corporativo: | |
|---|---|
| Otros Autores: | , , |
| Formato: | eBook |
| Lenguaje: | English |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2008.
|
| Edición: | 1st ed. 2008. |
| Colección: | Water Science and Technology Library,
68 |
| Materias: | |
| Acceso en línea: | https://doi.org/10.1007/978-3-540-79881-1 |
Tabla de Contenidos:
- Hydroinformatics: Integrating Data and Models
- Some Future Prospects in Hydroinformatics
- Data-Driven Modelling: Concepts, Approaches and Experiences
- Artificial Neural Network Models
- Neural Network Hydroinformatics: Maintaining Scientific Rigour
- Neural Network Solutions to Flood Estimation at Ungauged Sites
- Rainfall-Runoff Modelling: Integrating Available Data and Modern Techniques
- Dynamic Neural Networks for Nonstationary Hydrological Time Series Modeling
- Visualisation of Hidden Neuron Behaviour in a Neural Network Rainfall-Runoff Model
- Correction of Timing Errors of Artificial Neural Network Rainfall-Runoff Models
- Data-Driven Streamflow Simulation: The Influence of Exogenous Variables and Temporal Resolution
- Groundwater Table Estimation Using MODFLOW and Artificial Neural Networks
- Neural Network Estimation of Suspended Sediment: Potential Pitfalls and Future Directions
- Models Based on Fuzzy Logic
- Fuzzy Logic-Based Approaches in Water Resource System Modelling
- Fuzzy Rule-Based Flood Forecasting
- Development of Rainfall–Runoff Models Using Mamdani-Type Fuzzy Inference Systems
- Using an Adaptive Neuro-fuzzy Inference System in the Development of a Real-Time Expert System for Flood Forecasting
- Building Decision Support Systems based on Fuzzy Inference
- Global and Evolutionary Optimization
- Global and Evolutionary Optimization for Water Management Problems
- Conditional Estimation of Distributed Hydraulic Conductivity in Groundwater Inverse Modeling: Indicator-Generalized Parameterization and Natural Neighbors
- Fitting Hydrological Models on Multiple Responses Using the Multiobjective Evolutionary Annealing-Simplex Approach
- Evolutionary-based Meta-modelling: The Relevance of Using Approximate Models in Hydroinformatics
- Hydrologic Model Calibration Using Evolutionary Optimisation
- Randomised Search Optimisation Algorithms and Their Application in the Rehabilitation of Urban Drainage Systems
- Neural Network Hydrological Modelling: An Evolutionary Approach
- Emerging Technologies
- Combining Machine Learning and Domain Knowledge in Modular Modelling
- Precipitation Interception Modelling Using Machine Learning Methods – The Dragonja River Basin Case Study
- Real-Time Flood Stage Forecasting Using Support Vector Regression
- Learning Bayesian Networks from Deterministic Rainfall–Runoff Models and Monte Carlo Simulation
- Toward Bridging the Gap Between Data-Driven and Mechanistic Models: Cluster-Based Neural Networks for Hydrologic Processes
- Applications of Soft Computing to Environmental Hydroinformatics with Emphasis on Ecohydraulics Modelling
- Data-Driven Models for Projecting Ocean Temperature Profile from Sea Surface Temperature
- Model Integration
- Uncertainty Propagation in Ensemble Rainfall Prediction Systems used for Operational Real-Time Flood Forecasting
- OpenMI – Real Progress Towards Integrated Modelling
- Hydroinformatics – The Challenge for Curriculum and Research, and the “Social Calibration” of Models
- A New Systems Approach to Flood Management in the Yangtze River, China
- Open Model Integration in Flood Forecasting.