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Autoregression (AR) is a tool commonly used to understand and predict time series data. Traditionally the excitation noise is modelled as a Gaussian. However, real-world data may not be Gaussian in nature, and it is known that Gaussian models are adversely affected by the presence of outliers. We introduce a Bayesian AR model in which the excitation noise is assumed to be Student-t distributed. Variational...
Networks are very important in many fields of machine learning research. Within networks research, inferring the structure of unknown networks is often a key problem; e.g. of genetic regulatory networks. However, there are very few well-known biological networks, and good simulation is essential for validating and evaluating novel structural inference techniques. Further, the importance of large,...
IDS (Intrusion Detection system) is an active and driving defense technology. This paper mainly focuses on intrusion detection based on data mining. The aim is to improve the detection rate and decrease the false alarm rate, and the main research method is clustering analysis. The algorithm and model of ID are proposed and corresponding simulation experiments are presented. Firstly, a method to reduce...
This paper presents a modelling method for noisy response data of a closed loop with a PI controller. A general pre-£ltering procedure is not required in this method. A three-step procedure for estimating Laplace transfer function of a process is proposed. The true closed loop response is estimated from noisy response data, exploiting orthonormal properties of Laguerre functions. Then the closed loop...
This paper describes a modeling of movement object. A auto driving of the car is studied to reduce traffic accidents and traffic jam in late years. The experiment tries there control with the radio controlled car which did movement same as a car. The control of the radio controlled car controls the steering voltage on speed uniformity this time. The control method usually uses model predictive control...
This paper describes dynamics analysis of a small training ship and a possibility of ship pitching stabilization by adjusting engine speed. First, statistical analysis through multi-variate auto regressive(MAR) model is carried out. After upgrading the navigational system of an actual small training ship, in order to identify the model of the ship, the real data collected by sea trials on the ship...
A two-step identification method for nonlinear polynomial model using Evolutionary Algorithm (EA) is proposed in this paper, and the method has the ability to select a parsimonious structure from a very large pool of model terms. In a nonlinear polynomial model, the number of candidate monomial terms increases drastically as the order of polynomial model increases, and it is impossible to obtain the...
Several activities of Web-based architectures are managed by algorithms that take runtime decisions on the basis of continuous information about the state of the internal system resources. The problem is that in this extremely dynamic context the observed data points are characterized by high variability, dispersion and noise at different time scales to the extent that existing models cannot guarantee...
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