the discharge or runoff which ousts from a watershed is important. because its deficiency leads to financial losses and its excesses cause damage in lives and property as flood. in this research using artificial neural network multi-layer perceptron (mlp (and adaptive neuro-fuzzy interface system (anfis) and multiple regression method simulated rainfall- runoff process on daily basis in the kho...

The paper proposes empirical Bayes (EB) estimators for simultaneous estimation of means in the natural exponential family (NEF) with quadratic variance functions (QVF) models. Morris (1982, 1983a) characterized the NEF-QVF distributions which include among others the binomial, Poisson and normal distributions. In addition to the EB estimators, we provide approximations to the MSE’s of t...

unknown noise and artifacts present in medical signals with  non-linear fuzzy filter will be estimate and then removed. an adaptive neuro-fuzzy interference system which has a nonlinear  structure presented  for the noise function prediction by before samples. this paper is about a neuro-fuzzy method to estimate unknown noise of electrocardiogram (ecg) signal. adaptive neural combined with fuzz...

-Target tracking is one of the major aspects often used in sonar applications, surveillance systems, communication systems, embedded applications etc. To obtain kinematic components of a moving target such as position, velocity, and acceleration, one of the most used approaches in target tracking is stochastic estimation approach. Movement of the target is described by state space dynamic syste...

infiltration plays an important role in surface and subsurface hydrology and it is a key factor in the rainfall and runoff equations. the use of new approaches that have no limitations of common theoretical and empirical methods to determine infiltration relationships, will minimize the necessity of time consuming and costly experiments to determine permeability values and will make it possible...

In this paper, M-estimators, where M stands for maximum likelihood, used in robust regression theory for linear parametric regression problems will be generalized to nonparametric maximum likelihood fuzzy neural networks (MFNNs) for nonlinear regression problems. Emphasis is put particularly on the robustness against outliers. This provides alternative learning machines when faced with general ...

Many variables of interest in business and agricultural surveys have skewed distributions. An example from the National Agricultural Statistics Service is the acres harvested for a particular crop. We investigate small area estimation methods for skewed data under the assumption that a lognormal model is a reasonable approximation for the distribution of the response given covariates. Empirical...