This paper presents an efficient method for updating the structural finite element model. Model updating is performed through minimizing the difference of recorded acceleration of real damaged structure and hypothetical damaged structure, by updating physical parameters in each phase using iterative process of Levenberg-Marquardt algorithm. This algorithm is based on sensitivity analysis and pr...

web usage mining (wum) is the automatic discovering of hidden informationof user access pattern from the web log data. frequent pattern discovery is one ofthe main techniques in wum that can be used to implement recommender systems,forecast user`s navigational behaviour, and personalize web sites. many algorithmshave been suggested on obtaining frequent user navigation patterns. this paperprese...

—Process mining is a relatively new and emerging research area dealing with the process modeling and process analysis by studying on the event logs. By mining these logs, one can understand what is actually happening in the organization, which will bring quite different results than what people think. That is the reason why big organizations start using process mining to x-ray their organizatio...

In order to survive in the increasingly customer-oriented marketplace, continuous quality improvement marks the fastest growing quality organization’s success. In recent years, attention has been focused on intelligent systems which have shown great promise in supporting quality control. However, only a small number of the currently used systems are reported to be operating effectively because ...

Data mining is a complex process that aims to derive an accurate predictive model starting from a collection of data. Traditional approaches assume that data are given in advance and their quality, size and structure are independent parameters. In this paper we argue that an extended vision of data mining should include the step of data acquisition as part of the overall process. Moreover the s...

Databases for machine learning and data mining often have missing values. How to develop effective method for missing values imputation is an important problem in the field of machine learning and data mining. In this paper, several methods for dealing with missing values in incomplete data are reviewed, and a new method for missing values imputation based on iterative learning is proposed. The...

Motion estimation and compensation is an essential part of existing video coding systems. The mesh-based motion estimation (MME) produces smoother motion field, better subjective quality (free from blocking artifacts), and higher peak signal-to-noise ratio (PSNR) in many cases, especially at low bitrate video communications, compared to the conventional block matching algorithm (BMA). Howev...

In this paper, we introduce a new iterative algorithm for approximating a common solution of certain class of multiple-sets split variational inequality problems. The sequence of the proposed iterative algorithm is proved to converge strongly in Hilbert spaces. As application, we obtain some strong convergence results for some classes of multiple-sets split convex minimization problems.

basically, medical diagnosis problems are the most effective component of treatment policies. recently, significant advances have been formed in medical diagnosis fields using data mining techniques. data mining or knowledge discovery is searching large databases to discover patterns and evaluate the probability of next occurrences. in this paper, bayesian classifier is used as a non-linear dat...

The only way to test the ability of concrete plants to produce high quality concrete is to test their final products. Also, the process of testing and controlling concrete quality is time consuming and expensive. In this regard, having a quick, cheap and efficient way to predict the readiness of concrete plants to produce high quality concrete is very valuable. In this paper, a probabilistic mu...