Halton iterative partitioning master frames

Author(s):  
Blair Robertson ◽  
Paul van Dam-Bates ◽  
Oliver Gansell
VLSI Design ◽  
2002 ◽  
Vol 15 (2) ◽  
pp. 485-489
Author(s):  
Youssef Saab

Partitioning is a fundamental problem in the design of VLSI circuits. In recent years, ratio-cut partitioning has received attention due to its tendency to partition circuits into their natural clusters. Node contraction has also been shown to enhance the performance of iterative partitioning algorithms. This paper describes a new simple ratio-cut partitioning algorithm using node contraction. This new algorithm combines iterative improvement with progressive cluster formation. Under suitably mild assumptions, the new algorithm runs in linear time. It is also shown that the new algorithm compares favorably with previous approaches.


1983 ◽  
Vol 20 (2) ◽  
pp. 134-148 ◽  
Author(s):  
Girish Punj ◽  
David W. Stewart

Applications of cluster analysis to marketing problems are reviewed. Alternative methods of cluster analysis are presented and evaluated in terms of recent empirical work on their performance characteristics. A two-stage cluster analysis methodology is recommended: preliminary identification of clusters via Ward's minimum variance method or simple average linkage, followed by cluster refinement by an iterative partitioning procedure. Issues and problems related to the use and validation of cluster analytic methods are discussed.


2020 ◽  
Vol 3 (2) ◽  
Author(s):  
Yuliana Yuliana ◽  
Mario Richie ◽  
Halim Agung

CV. Jaya Tunggal Keramik is a company that sale of ceramics. CV. Jaya Tunggal Keramik experienced some problems regarding ceramics and customers such as difficulties in sale ceramics to customers so that some ceramic products accumulate in the warehouse, such as being damaged and ceramic display becomes less good because it is stored too long and difficulty retaining customers because some customers do not want to order ceramic products. Lack of precise decision taken by the management CV. Jaya Tunggal Keramik in determining the strategy to supply ceramic and how to make it CV. Jaya Tunggal Keramik is difficult to estimate the stock of ceramic products to be provided and it is difficult to determine which potential customers can be maintained as a regular customer. This research uses K-Means algorithm. K-Means algorithm is a partitioning clustering method that separates data into different groups with iterative partitioning. By using this application, users can find out the estimated stock and price of ceramics as well as information about potential customers. Testing in this research using data of November 2017 that compared with data of December 2017. Based on ceramic data test results, there are some ceramics that are not in accordance with the predicted results so it can be concluded that the K-Means algorithm on the test inventory data inventory in this study is not fully can provide accurate estimates, this is because the use of the K-Means algorithm is strongly influenced by the cluster center results and the attributes used.


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