Biometric authentication techniques are more consistent and efficient than conventional authentication techniques and can be used in monitoring, transaction authentication, information retrieval, access control, forensics, etc. In this paper, we have presented a detailed comparative analysis between Principle Component Analysis (PCA) and Independent Component Analysis (ICA) which are used for f...

abstract cation exchange capacity (cec) is an important characteristic of soil in terms of nutrient and water holding capacities and contamination management. measurement of cec is laborious and time-consuming. therefore, cec estimation through other easily - measured properties is desirable. in this study, ptfs for estimation of cation exchange capacity from basic soil properties such as parti...

It has limitations to apply the traditional mathematical model to assess the risk of the information security for it is characterized by its nonlinearity and uncertainty. The RBF Neural Networks Theory, Particle Swarm Optimization (PSO) Analysis and Fuzzy Evaluation are combined to build a particle swarm optimizing model of Information Security Risk Assessment based on RBF Neural Networks, so a...

Background and Objectives: Gestational Diabetes Mellitus (GDM) is the most common metabolic disorder in pregnancy. In case of early detection, some of its complications can be prevented. The aim of this study was to investigate early prediction of GDM by logistic regression (LR), discriminant analysis (DA), decision tree (DT) and perceptron artificial neural network (ANN) and to compare these m...

This paper presents CONORBIT, a derivative-free algorithm for constrained black-box optimization where the objective and constraint functions are computationally expensive. CONORBIT employs a trust-region framework that uses interpolating radial basis function (RBF) models for the objective and constraint functions and is an extension of the ORBIT algorithm (Wild, Regis, and Shoemaker 2008). It...

This paper presents an approach to model the nonlinear dynamic behaviors of the Automatic Depth Control Electrohydraulic System (ADCES) of a certain mine-sweeping weapon using Radial Basis Function (RBF) neural networks. In order to obtain accurate RBF neural networks efficiently, a hybrid learning algorithm is proposed to train the neural networks, in which centers of neural networks are optim...

Stylized facts are uncovered for a domestic (U.S.) examination of the South African Rand futures contract (ZAR). In this preliminary study, we model complex volatility patterns by a nonparametric artificial neural network (ANN) that incorporates a performance enhancing closed-form regularization technique. The modeling characteristics revealed by the Kajiji-4 radial basis function (RBF) ANN pro...

awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. therefore, the present study two hybrid models, wavelet- adaptive neural fuzzy interference system (wanfis) and wavelet- artificial neural network (wann) are used for flow prediction of gamasyab river (nahavand, hamedan, iran...

Several artificial neural network (ANN) models with a feed-forward, back-propagation network structure and various training algorithms, are developed to forecast daily and monthly river flow discharges in Manwan Reservoir. In order to test the applicability of these models, they are compared with a conventional time series flow prediction model. Results indicate that the ANN models provide bett...