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From the perspective of cognitive informatics, cognition can be viewed as the acquisition of knowledge. In real-world applications, information systems usually contain some degree of noisy data. A new model proposed to deal with the hybrid-feature selection problem combines the neighbourhood approximation and variable precision rough set models. Then rule(More)
From the point of the process of distribution service, a Markov chain based method is proposed for analyzing the reliability of supply chain. This paper presents an analytic method for determining the reliability of supply chains for logistics systems. By introducing the model of k -out-of- n :G system in reliability into the studies of supply chain, an(More)
The complexity of knowledge plays an important role in the success of any types of knowledge acquisition algorithms performing on large-scale database. LERS (learning from examples based on rough sets) system is a rule based knowledge acquisition system that is characterized by excellent accuracy, but the complexity of generated rule set is not taken into(More)
In this article, a delay dependent memory robust model predictive control (RMPC) algorithm was proposed for uncertain polytopic state delay systems with input constraints. The state delay is time-varying with an upper and lower bound. We minimize a cost function by minimizing its upper bound for the proposed RMPC algorithm. A new sufficient condition, in(More)
In this paper , a network devices fault diagnosis system based on Rough Set theory is introduced. It describe the design of fault diagnosis system from theory background , system architecture , function module and presents the basic principle , specific algorithm and steps to set up model which forms the fault diagnosis system by MIB data . It is proved(More)
To realize the information integration of CAD/CAPP/CAM, it’s important to apply the feature recognition method to the transfer and share of part information, but it’s still very difficult to apply the feature recognition method to handle the complicated box part. This paper presents a new method to extract the box part information, called as(More)