K. P. Holz - Academia.edu (original) (raw)

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Papers by K. P. Holz

Research paper thumbnail of A high-order time integration scheme for open channel flow

Research paper thumbnail of Computer language for hybrid river models

Research paper thumbnail of Finite element formulations for tidal wave analysis

Research paper thumbnail of Short-term water level prediction using neural networks and neuro-fuzzy approach

Neurocomputing, 2003

A comparative study on a short-term water level prediction using artiÿcial neural networks (ANN) ... more A comparative study on a short-term water level prediction using artiÿcial neural networks (ANN) and neuro-fuzzy system is addressed in this paper. The performance of the traditional approaches applied for such a hydrological task can often be constrained by data availability and simplifying assumptions in the processes description. In this paper, the ANN and neuro-fuzzy approaches are used for handling the situations with scarce data, where the predictions are based on the upstream hydrological conditions only. The models have been tested on two di erent river reaches in Germany. Moreover, the obtained results are compared to those of linear statistical models. Both ANN and neuro-fuzzy systems have performed comparably well and accurate for the purpose, explicitly outperforming the linear statistical models for a longer prediction horizon. The trained neural networks are partly implemented on-line, as a prototype of a web-based water level predictor.

Research paper thumbnail of Book Reviews

Journal of Hydraulic Research, 1983

Research paper thumbnail of Hybrid Neural Network—Finite Element River Flow Model

Journal of Hydraulic Engineering-asce, 2005

ABSTRACT

Research paper thumbnail of Numerical movable-bed models for practical engineering

Applied Mathematical Modelling, 1984

Research paper thumbnail of Tidal wave analysis for estuaries with intertidal flats

Advances in Water Resources, 1982

Research paper thumbnail of Rainfall-runoff modelling using adaptive neuro-fuzzy systems

Two important applications of rainfall-runoff models are forecasting and simulation. At present, ... more Two important applications of rainfall-runoff models are forecasting and simulation. At present, rainfall-runoff models based on artificial intelligence methods are built basically for short-term forecasting purposes and these models are not very effective for simulation purposes. This study explores the applicability and effectiveness of adaptive neuro-fuzzy-system-based rainfall-runoff models for both forecasting and simulation. For this purpose, an adaptive neuro-fuzzy system with autoregressive exogenous input (ARX) structure is proposed and an application is presented for the modelling of rainfall-runoff processes in the Sieve basin in Italy.

Research paper thumbnail of A high-order time integration scheme for open channel flow

Research paper thumbnail of Computer language for hybrid river models

Research paper thumbnail of Finite element formulations for tidal wave analysis

Research paper thumbnail of Short-term water level prediction using neural networks and neuro-fuzzy approach

Neurocomputing, 2003

A comparative study on a short-term water level prediction using artiÿcial neural networks (ANN) ... more A comparative study on a short-term water level prediction using artiÿcial neural networks (ANN) and neuro-fuzzy system is addressed in this paper. The performance of the traditional approaches applied for such a hydrological task can often be constrained by data availability and simplifying assumptions in the processes description. In this paper, the ANN and neuro-fuzzy approaches are used for handling the situations with scarce data, where the predictions are based on the upstream hydrological conditions only. The models have been tested on two di erent river reaches in Germany. Moreover, the obtained results are compared to those of linear statistical models. Both ANN and neuro-fuzzy systems have performed comparably well and accurate for the purpose, explicitly outperforming the linear statistical models for a longer prediction horizon. The trained neural networks are partly implemented on-line, as a prototype of a web-based water level predictor.

Research paper thumbnail of Book Reviews

Journal of Hydraulic Research, 1983

Research paper thumbnail of Hybrid Neural Network—Finite Element River Flow Model

Journal of Hydraulic Engineering-asce, 2005

ABSTRACT

Research paper thumbnail of Numerical movable-bed models for practical engineering

Applied Mathematical Modelling, 1984

Research paper thumbnail of Tidal wave analysis for estuaries with intertidal flats

Advances in Water Resources, 1982

Research paper thumbnail of Rainfall-runoff modelling using adaptive neuro-fuzzy systems

Two important applications of rainfall-runoff models are forecasting and simulation. At present, ... more Two important applications of rainfall-runoff models are forecasting and simulation. At present, rainfall-runoff models based on artificial intelligence methods are built basically for short-term forecasting purposes and these models are not very effective for simulation purposes. This study explores the applicability and effectiveness of adaptive neuro-fuzzy-system-based rainfall-runoff models for both forecasting and simulation. For this purpose, an adaptive neuro-fuzzy system with autoregressive exogenous input (ARX) structure is proposed and an application is presented for the modelling of rainfall-runoff processes in the Sieve basin in Italy.

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