Flow conditions (flow discharge, flow depth, and velocity) in natural streams are mainly determined via the resistance formula such as Manning’s equation. Evaluating accurate roughness coefficient (n), especially rivers with bed form during floods, to obtain more reliable results has always been of interest scholars. The interaction between is very complex since control forms, vice versa. main ...

Selection procedure • The initial state form n inputs only, there are no neurons. • If there are k neurons already, the probability of a selection from inputs and from neurons is given by constant probability p0 that one of the network inputs will be selected. • Otherwise an already existing neuron is selected randomly with probability proportional to fitness. • After the new neuron is formed a...

Medical applications are often characterized by a large number of disease markers and a relatively small number of data records. We demonstrate that complete feature ranking followed by selection can lead to appreciable reductions in data dimensionality, with significant improvements in the implementation and performance of classifiers for medical diagnosis. We describe a novel approach for ran...

Objective: In general, financial time series such as stock indexes have nonlinear, mutable and noisy behavior. Structural and statistical models and machine learning-based models are often unable to accurately predict series with such a behavior. Accordingly, the aim of the present study is to present a new hybrid model using the advantages of the GMDH method and Non-dominated Sorting Genetic A...

in the present study, computational fluid dynamics (cfd) techniques and artificial neural networks (ann) are used to predict the pressure drop value (δp ) of al2o3-water nanofluid in flat tubes. δp  is predicted taking into account five input variables: tube flattening (h), inlet volumetric flow rate (qi  ), wall heat flux (qnw  ), nanoparticle volume fraction (φ) and nanoparticle diameter (dp ...