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Nature essentially consists of complex systems. The paper presents a conceptual framework to understand how complex systems interact with each other in nature. All natural systems are thermodynamicall...
We review recent progress made in analyzing the spread of viruses and bugs in the internet. We describe how the use of a model that takes into account the complex inhomogeneity of the internet and its...
Distributed watershed models constitute a key component in flood forecasting systems. It is widely recognized that models because of their structural differences have varying capabilities of capturing...
Urban transportation is a complex phenomenon. Since many agents are constantly interacting in parallel, it is difficult to predict the future state of a transportation system. Because of this, optimiz...
Distributed watershed models constitute a key component in flood forecasting systems. It is widely recognized that models because of their structural differences have varying capabilities of capturing...
The use of unsupervised artificial neural network techniques like the self-organizing map (SOM) algorithm has proven to be a useful tool in exploratory data analysis and clustering of multivariate dat...
The reduction of information contained in model time series through the use of aggregating statistical performance measures is very high compared to the amount of information that one would like to dr...
Hydrological model evaluation and identification essentially involves extracting and processing information from model time series. However, the type of information extracted by statistical measures h...
Several methodological Problems of experimental systems analysis can be overcome by means of parametric and nonparametric selection procedures. Together with theselection of models with optimal comple...

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