Abstract: Frequent pattern mining algorithm is an interesting problem and most essential field in data mining, a Navigation pattern defines the user’s behavior towards a particular area, in this paper we propose an algorithm for mining user navigation Patterns using frequent item sets, by using transaction Reduction method. By using Association rule mining we extract the interesting Correlation and relation between the large volumes of Transactions in the databases. In this paper we merge the navigation pattern mining algorithm with the Content based image retrieval application. Thus by merging it we obtain an effective knowledge discovery process by which it overcomes the draw backs of the existing system This work thus used to extract the navigation patterns discovered from the data bases used in the Content Based image retrieval. And also this work is used as the offline Knowledge discovery process in CBIR.

• Publication Date: 12-Mar-2012
• DOI: 10.15224/978-981-07-1847-3-655
• Views: 0
• Downloads: 0

Abstract: Determining of required spinning reserve capacity of system is the most important tasks of system operator for safe and ensure operation of power systems. The spinning reserve is the unused capacity which can be activated on decision of the system operator and which is provided by devices which are synchronized to the network and able to affect the active power [1]. In this paper represented a method to determining the capacity of reserve in deregulated systems with the goal of maximizing public benefits by modeling the consumers. Objective function associated with this method, is minimizing total cost of production and expected cost of outage to consumers. Simplicity of this algorithm is the superiority of this method over other stochastic methods. Finally this algorithm was applied to 14 bus IEEE network and the result was compared with different criteria and has observed that this algorithm can easily prevent the payment of additional costs.

• Publication Date: 12-Mar-2012
• DOI: 10.15224/978-981-07-1847-3-658
• Views: 0
• Downloads: 0