â  abstract: in this paper, artificial neural network (ann) was used for modeling the nonlinear structure of a debutanizer column in a refinery gas process plant. the actual input-output data of the system were measured in order to be used for system identification based on root mean square error (rmse) minimization approach. it was shown that the designed recurrent neural network is able to pr...

Nonlinear principal component analysis is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA, like PCA, is used to identify and remove correlations among problem variables as an aid to dimensionality reduction, visualization, and exploratory data analysis. While PCA identifies only linear correlations between variables, NLPC...

the instrumental use of social networks has become a central tenet of international health policy and advocacy since the millennium project. in asking, ‘how to facilitate social contagion?’, karl blanchet of the london school of hygiene and tropical medicine therefore reflects not only on the recent success, but also hints to growing challenges; the tactics of partnerships, alliances and platfo...

A feedback Group Method of Data Handling (GMDH)-type neural network algorithm is proposed, and is applied to nonlinear system identification and medical image analysis of liver cancer. In this feedback GMDH-type neural network algorithm, the optimum neural network architecture is automatically selected from three types of neural network architectures, such as sigmoid function neural network, ra...

the proposal lateral load pattern for pushover analysis is given in two forms for symmetric concrete buildings: 1-(x/h)0.5 for low-rise and mid-rise buildings, 2- sin(πx/h) for high-rise buildings. these two forms give more realistic results as compared to conventional load patterns such as triangular and uniform load patterns. the assumed buildings of 4, 8, 12, 16, 20 and 30 story concrete bui...

the nonlinear static pushover analysis technique is mostly used in the performance-based design of structures and it is favored over nonlinear response history analysis. however, the pushover analysis with fema load distributions losses its accuracy in estimating seismic responses of long period structures when higher mode effects are important. some procedures have been offered to consider thi...

analyzing the nonlinear vibration of beams is one of the important issues in structural engineering. according to this, an impressive analytical method which is called modified iteration perturbation method (mipm) is used to obtain the behavior and frequency of a cantilever beam with geometric nonlinear. this new method is combined by the mickens and iteration methods. moreover, this method don...

In this chapter, a nonlinear extension to independent component analysis is developed. The nonlinear mapping from source signals to observations is modelled by a multi-layer perceptron network and the distributions of source signals are modelled by mixture-of-Gaussians. The observations are assumed to be corrupted by Gaussian noise and therefore the method is more adequately described as nonlin...

The widely used principal component analysis (PCA) is implemented in nonlinear by an auto-associative neural network. Compared to other nonlinear versions, such as kernel PCA, such a nonlinear PCA has explicit encoding and decoding processes, and the data can be transformed back to the original space. Its data compression performance is similar to that of PCA, but data analysis performance such...