every country actively and initiatively takes all kinds of policy steps to improve the international competitiveness of its industries and therefore improve national integrated competitiveness for the purpose of gaining economic benefits under the context of economic globalization. therefore, studies of moreover, projects launched by the cluster had to be endorsed by the growers and one criteri...

abstract the objective of the present study is to assess the performance of 18 irrigation districts from ten countries in the world using the benchmarking method and data mining analysis (cluster analysis). irrigation networks of dez, sefidrood, tajan and voshmgir from iran have been compared with 14 irrigation districts from nine other countries. the k- means algorithm was used to analyze the ...

performance   evaluation in regular periods is one of the ways in which organizations can   evaluate their performance as well as weak and strong points unifiedly and   precisely. these days, mathematical models are also used to evaluate the   efficiency and productivity of various units. these units are a collection of   education, research and service activities as input and output factors an...

Some indexes are necessary for performance evaluation of a management system. Balanced scorecard (BSC) is used in order to extraction of these indexes for evaluating the necessary performances in the evaluation process. Utilization of BSC causes to prevent in increasing information and data. Furthermore, all of the important indexes are considered in evaluation performance.Data envelopment anal...

There are two primary types of graph-based data miners: frequent subgraph and compression-based miners. With frequent subgraph miners, the most interesting substructure is the largest one (or ones) that meet the minimum support. Whereas, compression-based graph miners discover those subgraphs that maximize the amount of compression that a particular substructure provides a graph. The algorithms...

This paper evaluates the performance of ten significance measures applied to the problem of determining an appropriate network structure, for data modelling with neurofuzzy systems. The advantages of Neurofuzzy systems are demonstrated with application to both real and synthetic data interpretation problems.