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Functional network analysis based on matrix decomposition/factorization methods including ICA and dictionary learning models have become a popular approach in fMRI study. Yet it is still a challenging issue in interpreting the result networks because of the inter-subject variability and image noises, thus in many cases, manual inspection on the obtained networks is needed. Aiming to provide a fast...
For the high-temperature structure, there exists correlation between the thermal stress and thermal intensity in most cases because of the two-sided effects of temperature. This paper proposes a time-varying response surface method considering correlation between the structural response value and structural response threshold based on Copula models. Firstly, the time-varying model of structural response...
Parallel query processing over data streams in cloud computing environments has attracted considerable attention recently in various fields, due to the huge potential value of analyzing massive data or big data in a large number of streaming applications. Nevertheless, existing studies on queries primarily focus on the algorithms for the specific query types with the lack of the general framework...
The authors conducted a meta-analysis about the relationship between Information Technology (IT) capability and business performance which aggregates empirical findings from the information technology literature. This paper confirms that IT capability has significant impact on business performance. Our research also finds that different types of IT capability measurement, different types of performance...
In this paper, a non-stationary Kalman filter parametrization of subspace identification models is adopted to deal with finite data windows. We show that the non-stationary Kalman filter parametrization is the solution to the least squares estimation of the Markov parameters from high-order ARX models. A recursive conversion between observer Markov parameters and system Markov parameters is developed...
A fractional order model method based on Mittag-Leffler Functions for education evaluation is proposed in this paper. Course evaluation is necessary means to ensure the improvement of course construction level. Firstly, analytical solution of linear fractional-order systems is promoted. Secondly, fractional order model of course evaluation is proposed. And fractional evaluation model is composed of...
Industrial model predictive control (MPC) usually assumes a step-like disturbance model, which is insufficient when there is model mismatch in the plant or high order disturbances. In this paper, we demonstrate that a disturbance model identified from close-loop data is desirable for dynamic matrix control (DMC). We introduce a subspace based method to obtain such a model. The method estimates Markov...
The load identification of the shield machine is presented in this paper by introducing the mechanical analysis of shield excavating into the nonlinear multiple regression of on-site data. The analysis on mechanical characteristics of shield-soil system can decouple the nonlinear multi-parameter problem of load, so it is great helpful for the regression process to establish a load model. Then a load...
Combat mission of battle plane is usually executed by plane fleet as a unit. Plane fleet can be divided into several team formations. Battle planes in different formations have different flight profiles, and cooperate with each other. The load conditions varied under different flight profiles. According to the influence of load conditions on battle plane's reliability, the flight profile conversion...
This paper is concerned with the identification of multiple model process with transition using the output error (OE) method. Local multiple linear models with output error model structure are identified at fixed operating points first and then a global nonlinear model is approximated by interpolating the multiple linear models with exponential weighting functions. With all the obtained initial values...
Traditional subspace identification (SID) framework uses Kalman filter or predictor to interpret the SID models. To achieve this the horizons f, p have to approach infinity to be consistent. In practice, however, the horizons f, p are finite. We argue that for finite f and p the Kalman filter framework does not apply. In this paper, we introduce a progressive parametrization framework to interpret...
To overcome the disadvantage of conventional fusion forecasting models, two main research ways are attempted. Firstly, the idea of the comprehensive evaluation is adopted to evaluate the forecasting models which needed to be selected by the multi-attribute comprehensive evaluation model. Secondly, the forecast precision of each forecasting model influenced by the time is compared in rationally way...
All the major citrus producing areas in China are facing the intensive competition from international market. The problem of how to find an efficient path to decrease citrus production cost by analyzing production cost of citrus and how to promote effective cooperation between regions to deal with the pressure of international market through integrating resources of the regions, has become an important...
According to the characteristics and requests of data analysis of traffic information, data mining techniques are put forward to apply to the management and decision-making of traffic information. Based on this foundation, an integrated model of the traffic information intelligent analysis and decision support is further given. This model has data mining techniques and data warehouse at its core,...
Taking the monthly data from July, 2005 to April 2008 as a specimen period, this paper uses panel data model to analyze the influences of RMB revaluation on import value of agricultural products of China's different import subjects. Demonstration result indicates that the economic growth of China stimulates the increasing of agricultural imports of the main import subjects; appreciation of real effective...
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