Seong-Hoon Kim, Myung-Il Roh, Ki-Su Kim, Min-Jae Oh, “Big Data Platform Based on Hadoop and Application to Weight Estimation of FPSO Topside”, Journal of Advanced Research in Ocean Engineering, Vol. 3, No. 1, pp. 32-40, 2017.03.01
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Abstract | Recently, the amount of data to be processed and the complexity thereof have been increasing due to the development of information and communication technology, and industry’s interest in such big data is increasing day by day. In the shipbuilding and offshore industry also, there is growing interest in the effective utilization of data, since various and vast amounts of data are being generated in the process of design, production, and operation. In order to effectively utilize big data in the shipbuilding and offshore industry, it is necessary to store and process large amounts of data. In this study, it was considered efficient to apply Hadoop and R, which are mostly used in big data related research. Hadoop is a framework for storing and processing big data. It provides the Hadoop Distributed File System (HDFS) for storing big data, and the MapReduce function for processing. Meanwhile, R provides various data analysis techniques through the language and environment for statistical calculation and graphics. While Hadoop makes it is easy to handle big data, it is difficult to finely process data; and although R has advanced analysis capability, it is difficult to use to process large data. This study proposes a big data platform based on Hadoop for applications in the shipbuilding and offshore industry. The proposed platform includes the existing data of the shipyard, and makes it possible to manage and process the data. To check the applicability of the platform, it is applied to estimate the weights of offshore structure topsides. In this study, we store data of existing FPSOs in Hadoop-based Hortonworks Data Platform (HDP), and perform regression analysis using RHadoop. We evaluate the effectiveness of large data processing by RHadoop by comparing the results of regression analysis and the processing time, with the results of using the conventional weight estimation program. |
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Publication Date | 2017-03-01 |
Role | Corresponding Author |
Category | Others |
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Ki-Su Kim, Myung-Il Roh, "A Submarine Arrangement Design Program Based on the Expert System and the Multistage Optimization", Advances In Engineering Software, Vol. 98, No. 97-111, 2016.08.01
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Sol Ha, Seong-Ho Seo, Myung-Il Roh, Hyun-Kyoung Shin, "Simplified Nonlinear Model for the Weight Estimation of FPSO Plant Topside Using the Statistical Method", Ships and Offshore Structures, Vol. 11, No. 6, pp. 603-619, 2016.09.01
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Sol Ha, Tae-Sub Um, Myung-Il Roh, Hyun-Kyoung Shin, “A Structural Weight Estimation Model of FPSO Topsides Using an Improved Genetic Programming Method”, Ships and Offshore Structures, Vol. 12, No. 1, pp. 43-55, 2017.01.01
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Seong-Hoon Kim, Myung-Il Roh, Ki-Su Kim, Min-Jae Oh, “Big Data Platform Based on Hadoop and Application to Weight Estimation of FPSO Topside”, Journal of Advanced Research in Ocean Engineering, Vol. 3, No. 1, pp. 32-40, 2017.03.01
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Sung-Kyoon Kim, Myung-Il Roh, Ki-Su Kim, “Arrangement Method of Offshore Topside Based on an Expert System and Optimization Technique”, Journal of Offshore Mechanics and Arctic Engineering, Vol. 139, No. 2, pp. 1-19, 2017.04.01
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Dong-Hoon Jeong, Myung-Il Roh, Seung-Ho Ham, Chan-Young Lee, “Performance Analyses of Naval Ships Based on Engineering Level of Simulation at the Initial Design Stage”, IJNAOE, Vol. 9, No. 4, pp. 446-459, 2017.07.01
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Dong-Hoon Jeong, Myung-Il Roh, Seung-Ho Ham, “Case Study of Detection and Maneuvering Performance of Naval Ships Using Engagement Simulation of Engineering Level”, Ocean Systems Engineering, Vol. 7, No. 3, pp. 247-273, 2017.09.01