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The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incremental learner systems should not only consider the integration of knowledge from new data, but also maintain an optimum set of parameters. In this paper, we propose an approach for performing incremental learning in an adaptive...
Service modeling and composition is a fundamental method for offering advanced functionality by combining a set of primitive services provided by the system. Unlike in the case of web services for which there is an abundance of reliable resources, in sensor networks, the resources are constrained and communication among nodes is error-prone and unreliable. Such a dynamic environment requires a continuous...
To resolve the key issue of uncertainty knowledge representation in the process of establishing threat assessment system, a variable-parameter dynamic Bayesian network for threat assessment is proposed. A self-adaptive assessment system based on variable-parameter dynamic Bayesian network is presented. And a novel threat assessment optimization algorithm based on variable-parameter dynamic Bayesian...
The Vestibulo-Ocular Reflex (VOR) stabilizes the images of the world on the retinae when the head is in motion. Basic daily activities such as walking or driving depend on the proper functioning of this reflex. For several decades, scientists have developed methods to model and identify this system mathematically. However, traditional methods cannot analyze VOR data comprehensively because they disregard...
In this paper, we study how resources within a large high performance computing (HPC) cluster can be dynamically partitioned to optimize client utility for multiple service classes. We model service effectiveness using both perceived service quality and resources required. Using empirical data obtained from A*STAR Computational Resource Center (A*CRC), we analyze how quality metrics and statistical...
To establish suitable models to describe the behavior of biochemistry systems, a new modeling method was introduced, combining multiple objective ant colony optimization(MOACO) with the dynamic Epsilon-SVM. The hyper-parameters of Epsilon-SVM were automatically decided by using multiple objective ant colony optimization(MOACO). Each training sample used different error. The model for penicillin production's...
To solve the problem of process instances adaptation caused by dynamic process changes in workflow systems, a solution of workflow instance migration based on automatic planning mechanism was proposed, in which AI planning methods were used in migrating workflow system. The initial state and the target state of migrating instance were expressed with disjunction of an order prediction, the HTN method...
Currently considerable attention has been given to the effect of data correlation on statistical process control (SPC). Use of traditional SPC methods when observations are correlated often leads to misleading conclusions as to whether or not the process is under control. The objective of this paper is to develop an algorithm to adjust a Dynamic Linear Model, to calculate the run length distribution...
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