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Dauphin is a new statistical signal processing language designed for easier formulation of detection, classification and estimation algorithms. This paper demonstrates the ease of developing signal processing algorithms in Dauphin. We illustrate this by providing exemplar code for two classifiers: Bayesian and \km, and for an estimator: the Kalman filter. In all cases, and especially the last named,...
This paper presents, a simple and robust Adaptive Neuro-Fuzzy Inference System (ANFIS) for vibration control of a Vehicle Active Suspension System (VASS) and compares with conventional Proportional, Integral and Derivative (PID) controller and an Artificial Neural Network (ANN) controller which is trained with conventional control data. The main objective is to enhance the travelling comfort to the...
Based on ergonomics, fuzzy theory and BP neural network, weighted integrated comfort index WICI is proposed in the paper. WICI is calculated as the weighted sum of integrated comfort indices which gained by the data recorded in different periods of wheelchair assessment experiments. The integrated comfort index ICI is the output of a trained BP neural network. The inputs of the network are the main...
In this paper, the rolling bearing is detected by the PLC-based remote fault diagnosis system. This system carries out remote system bearing fault diagnosis and maintenance through the combination of expert system and BP Neural Network. Since the advantages of rapid exchange of diagnostic information, accelerating the fault diagnosis rate, and reducing negative effects of failure on production process,...
Evaluating road safety is essential in identifying the potential road safety hazard which could result in casualties and property losses. in this paper, a BP neural network was built by using neural network toolkit in "Matlab", Two similar roadways are used in calibrating and validating the network. The high level of predictability provided that the application of BP neural network model...
In order to reflect the quality of construction projects, this paper constructed the evaluation index system of construction quality and designed BP network model based on neural network theory. Then in the MATLAB environment, an instance of the model was simulated, the results are consistent with the results of expert evaluation, and show that the method can make the quality evaluation of construction...
Customer is one of the most important resources of an enterprise. Customer value analysis is the basis of customer relationship management and customer classification is an important item of customer value analysis. Aiming at the characteristics of customer in the mobile telecommunication industry, the thesis designed the BP neural network model, and presented the doable evaluating programs using...
This paper presents a customer segmentation model in coal enterprises based on SOM neural network. The index system in this model is designed into seven indexes according to the customer lifetime value and behavior character. Then it is divided into six sections to calculate much data in database of information system based on the SOM neural network. After completing the quantification and standardization...
In this paper, the authors established an evaluation model of university teaching quality based on back-propagation neural networks. Quantified indices of teaching quality were inputs of the model, while teaching effect was output. The empirical research by MATLAB showed that this evaluation approach was suitable for the university teaching quality assessment tasks, which not only overcomes subjective...
This paper expound concept of credit evaluation of enterprise. Establish system of enterprise with the chosen 12 single financial ratio indexes which was divided into four groups and a model of three layers of BP NEURAL NETWORKS which can use theory and method of ANN forecast the credit of enterprise. In the end, use the indexes of an enterprise and MATLAB to forecast the credit.
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