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In this paper we propose a web log mining-based network user behavior analysis scheme, which plays an important role in network structure optimization and website server configuration. Based on clustering and regression model, we studied the network user's visit model in a university by analyzing a large amount of web log data which is collected from the university campus network. The data analyzing...
Computing Bayesian statistics with traditional techniques is extremely slow, specially when large data has to be exported from a relational DBMS. We propose algorithms for large scale processing of stochastic search variable selection (SSVS) for linear regression that can work entirely inside a DBMS. The traditional SSVS algorithm requires multiple scans of the input data in order to compute a regression...
In order to study the damage on weapon equipment by explosive shock wave, simulation experiments were carried out to research explosive impact damage on stiffened cantilever box girder. Data mining method of PCA was introduced to process the damage data in simulation experiments. Basing on simulation and data mining, it discussed multi-objective optimization of stiffened cantilever box girder about...
C-regression models are known as very useful tools in many fields. Since now, many trials to construct c-regression models for data with uncertainty in independent and dependent variables have been done. However, there are few c-regression models for data with uncertainty in independent variables in comparison with dependent variables now. The reason is as follows. The models are constructed using...
This paper proposes a probability weighted ARX (PrARX) model wherein the multiple ARX models are composed by the probabilistic weighting functions. As the probabilistic weighting function, a `softmax' function is introduced. Then, the parameter estimation problem for the proposed model is formulated as a single optimization problem. Furthermore, the identified PrARX model can be easily transformed...
The two-dimensional magnetotelluric inverse problem is ill-posed and the inverse results are unstable and non-unique. It means that different geo-electrical model could fit the observed data with the same accuracy. A stable solution of the ill-posed inverse problem can be obtained by utilizing the regularization methods in the objective function. Solving large scale linear equation of inverse problem,...
Business process's performance determine the whole enterprise's economic profit, researching work on business process's optimization is very useful and meaningful. This thesis point out that manager must take the dynamic environment and multiple objectives into account while optimizing the enterprise's business process. Based on the theory of multiple objective optimizations, AHP, and simulation technology,...
??Poor?? information systems are found everywhere. The mining technology of data of known information is very important. Method model-based is an important approach. The non-equal-interval optimizing direct Verhulst GM(1, 1) model was built which extended equal interval to non-equal-interval and suited for general data modeling and estimating parameters of direct Verhulst GM (1, 1) by optimizing the...
In this paper, an intelligent model constructed with fuzzy TS dynamic nonlinear autoregressive with exogenous input (NARX) is introduced for process state identification and behavior prediction for complex processes. In the model, fuzzy neural networks (FNNs) are applied as process state classifiers for process state (fault) detection. An optimization schemes are also investigated for model adaptability...
A common assumption in the literature on mixed model assembly line balancing problem is that the task duration is known and deterministic but may differ among various models. In this paper, we present a robust optimization formulation for dealing with task duration uncertainty in a mixed model assembly line balancing problem (RMALB-P) in which task duration can vary in a specific range. RMALB-P is...
The use of PC cluster systems composed of many PCs is largely spread in these days. It is important to improve system usage keeping proper fair-share policy. This optimization problem is difficult to solve. In scheduler software, there are many parameters and the effectiveness of many parameters is related with each other complicatedly. Therefore it is more difficult to find optimal parameter configuration...
This paper is concerned with validating a mathematical model of regulation in the tryptophan operon using global optimization. Although a number of models for this biochemical network are proposed, in many cases only qualitative agreement between the model output and experimental data was demonstrated, since very little information is currently available to guide the selection of parameter values...
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