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Although reputation models are available to encourage good services of sellers as well as punish their bad ones in the C2C ecommerce environment, their anti-fraud ability appears to be weak in general. Based on our TRUST model and the method of combing fraud pattern recognition with Time Window, we propose a Fraud Identification Method which has certain anti-fraud capabilities. Simulation experiments...
There are two principal ideologies in present digital library evaluation model. Divarication between them demonstrates the immaturity of evaluation research to some extent. To resolve such divarication can't only rely on the surface reference and complement from each other, but explore the intrinsic problem of divarication, then we can get ride of constraints and re-building a brand-new evaluation...
In this paper, We briefly present an overview of Markov chain Monte Carlo(MCMC), the MCMC method is studied with LA long beach air pollution PM 2.5 traffic from 2001 to 2007 observations. A linear regression model was built. We carried out statistical and graphical analysis and convergence diagnostics of Monte Carlo sampling output. The conclusion illustrated that the model fitting the datasets very...
As more and more people enter into the virtual world based on the internet, reputation has become the key to punish the bad behaviors of people and encourage the good behaviors of them. How to evaluate effectively the reputation of the participators is the urgent problem which should be solved. The paper provides a combined reputation model TRUST for distributed environment. This model, according...
The generalized autoregressive conditional heteroskedasticity (GARCH) model has become the most popular choice in the analysis of time series datas. In this paper, an autoregressive moving average (ARMA)-GARCH model was built, and it also provided parameter estimation, diagnostic checking procedures to model, and predict Dow and S&P 500 indices data from 1988 to 2008, which extracted from yahoo...
An autoregressive integrated moving average (ARIMA) model was one of the most popular linear models in financial time series forecasting in the past. In this context, a time series analysis of the NASDAQ composite indices is provided study its movement in 1998-2008. This paper proposed a general expression of seasonal ARIMA models with periodicity and provide parameter estimation, diagnostic checking...
The Los Angeles Long Beach area has been the largest air polluter in LA regions. How to decrease the air pollution concentrations becomes a hot topic recently. A vector autoregressive model (VAR) was applied to modeling the time series of monthly maximum particulate matter (PM) 2.5 concentration in Los Angeles Long Beach area. This paper explored the association among the current month PM2.5 concentrations...
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