Download Computational intelligence in industrial application : by Yanglv Ling PDF

By Yanglv Ling

These court cases of the 2014 Pacific-Asia Workshop on Computational Intelligence in business program (CIIA 2014) comprise eighty one peer-reviewed papers. the subjects coated within the e-book comprise: (1) computing device Intelligence, (2) program of computing device technological know-how and communique, (3) business Engineering, Product layout and production, (4) Automation and keep an eye on, details expertise and MEMS.

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Extra resources for Computational intelligence in industrial application : proceedings of the 2014 Pacific-Asia Workshop on Computer Science in Industrial Application (CIIA, December 8-9, 2014, Singapore)

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The idea and technology of big data give people much more opportunities to get information in many fields and levels than ever. 1 INTRODUCTION Big data, as the hot keywords, have a significant impact on education, just as on all walks of life. We can feel the effect deeply when the flipped classroom and MOOC develop. Big data puts us into an age featured with data, data collection and analysis, and the flipped classroom and MOOC based on big data leads to great change in the educational field. In the age of big data, educational resources become generative, teaching individualized, the role of teachers repositioned.

Hama platform is based on the implementation MapReduce and BSP (Bulk Synchronous Parallel). It uses the transportation of messages in BSP to accelerate the speed of the iterative process, and doesn’t need multiple MapReduce jobs, the cost of HDFS persistence and data serialization stay unchanged. So we, in this paper, design and implement the classical data algorithm K-Means in Hama platform, to pave the way for further complex data mining algorithm. KEYWORDS: Hadoop; MapReduce; BSP; Hama; K-means.

Cozzi, & Y. Zhang (2003). Graphbased ranking algorithms for e-mail expertise analysis. In Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery, pp. 42–48. ACM. Egghe, L. (2006). Theory and practise of the g-index. Scientometrics 69(1), 131–152. Garfield, E. et al. (1972). Citation analysis as a tool in journal evaluation. American Association for the Advancement of Science. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output.

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