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Based on the annual report data between 1995 and 2005 of all listed companies (LCs), the 25 initial financial indexes, widely used by experts and researchers aboard and at home, was deduced to 14 effective evaluation indicators using factor analysis and principal component analysis (PCA). The 14 evaluation indicators, covering five aspects for comprehensive evaluation of competitiveness of LC, retain...
In this research, the combination of modal data is used to identify the damage of a FEM model using neural networks. The identification ability with different levels of noise and incomplete mode shapes are also investigated. It has been proved that the neural network using combination of modal parameters as input has a excellent identification ability with ideal error tolerance and robustness. Numberical...
The influence of blasting vibration to surroundings around the blasting area can not be ignored, in order to guarantee the safety of surroundings around blasting area, blasting vibration forecasting model based on neural network is established by improved BP neural network in this paper. The inputs of the model are the largest single fire dynamite, height difference and horizontal distance between...
By the intermittent test, we studied the acid fermentation rule after mixing excess sludge and distiller's grains. The results showed that the control sample and by the proportion of 0.2g/gTS, 0.4g/gTS, 0.6g/gTS added distiller's grains to the 4 reactors, the maximums of SCOD reached 775.83mg/L, 1136.92 mg/L, 1427.77mg/L and 2609.48mg/L, the TS loss ratios were 12.00%, 15.69%, 16.92% and 19.25%. With...
In the last decade significant progress in computer vision based control of unmanned ground vehicles (UGV) has been achieved. However, until now textural information has been somewhat less effective than color or laser range information. In this paper we propose a computer vision based cross country segmentation system that is capable of distinguishing cross-country road, grass and trees during day-time...
Fault diagnosis of induction motor is gaining importance in industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. Due to environmental stress and many others reasons different faults occur in induction motor. Many researchers proposed different techniques for fault detection and diagnosis. However, many techniques available presently...
In this paper, a hybrid network consisting of a trigonometric functional link artificial neural network (FLANN) and fuzzy logic system named as functional link neural fuzzy (FLNF) model is used to predict the stock market indices. The proposed model uses a functional link neural network to the consequent part of the fuzzy rules. The consequent part of FLNF model is a non-linear combination of input...
This paper presents the classification of benign and malignant breast tumor based on fine needle aspiration cytology (FNAC) and probabilistic neural network (PNN). Five hundred and sixty nine sets of cell nuclei characteristics obtained by applying image analysis techniques to microscopic slides of FNAC samples of breast biopsy have been used in this study. These data were obtained from the University...
Here an efficient fusion technique for automatic face recognition has been presented. Fusion of visual and thermal images has been done to take the advantages of thermal images as well as visual images. By employing fusion a new image can be obtained, which provides the most detailed, reliable, and discriminating information. In this method fused images are generated using visual and thermal face...
The past few years have seen a lot of applications of Hybrid Soft Computing approaches that seem to have completely replaced the traditional uni-system approaches. The added abilities that come from the hybrid approaches motivate their use in every system. Bio-Medical Engineering is yet another field which has seen a major change in the past few years. We find various new approaches being applied...
Aimed at the intrusion behaviors are characterized with uncertainty, complexity, diversity and dynamic tendency and the advantages of wavelet neural network (WNN), an intrusion detection method based on WNN is presented in this paper. Moreover, we adopt a algorithm of reduce the number of the wavelet basic function by analysis the sparseness property of sample data which can optimize the wavelet network...
This paper introduces a novel algorithm for features selection based on a Support Vector Decision Function (SVDF) and Forward Selection (FS) approach with a fuzzy inferencing model. In the new algorithm, Fuzzy Enhancing Support Vector Decision Function (Fuzzy ESVDF), features are selected stepwise, one at a time, by using SVDF to evaluate the weight value of each specified candidate feature, then...
In construction cost forecasting system, a great many uncertain factors effect the cost decision-making, so it is difficult to do effective forecasting by using traditional methods such as time series approach, regression analysis. In this paper, a nonlinear model based on RBF neural network is presented. There are some ameliorated measures in leaning algorithm of radial basis function (RBF) neural...
An electrical fault-waveform regenerator (EFWG) is proposed in this paper originally, including its hardware structure and software flow chart. And the EFWG is mainly relying on a power amplifier (PA) to regenerate the electrical fault waveforms recorded by fault recorders (FR), so a digital closed-loop modification technique (DCLMT), which is distinct from the predistortion technique (PDT) widely...
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