Application of Big Data on Facility Interoperability using Python

Vikram Kumar¹, Su-Ling Fan², Sidagam Eswar³

¹PG Student, Tamkang University, Taiwan
²Director of Research & Development Center for Construction Law and Associate Professor, Tamkang University Taiwan
³UG Student, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India

Abstract

The Purpose of this study on Facility Interoperability is mostly to reduce the Injury and deaths happened by the Instruments and System in the Hospital. The preliminary study in this paper is to investigate the damages happen due to the Facility interoperability. This paper describes techniques from computer science, such as Python, decision tree induction and Association Mining Rules Pattern that are not normally applied to find the way to stop injury and deaths in the Hospital buildings and as an example applies them to a complex set of data from climate-responsive spaces in India. The findings illustrate the power of these techniques for using simplified measures as proxies to extract more sophisticated information about building operation, and for quickly identifying patterns in how different design and operational characteristics affected. By using PrefixSpan Algorithm, I am finding the relationship between two or more system. PrefixSpan (i.e., Prefix-projected Sequential pattern mining), which explores prefix projection in sequential pattern mining. PrefixSpan mines the complete set of patterns but greatly reduces the efforts of candidate subsequence generation. Moreover, prefix-projection substantially reduces the size of projected databases and leads to efficient processing. Our performance study shows that PrefixSpan outperforms both the Apriori-based GSP algorithm and another recently proposed method, FreeSpan, in mining large sequence databases.

Keywords

• Python, Interoperability, Algorithm

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Cite this Article as Follows

Vikram Kumar, Su-Ling Fan, Sidagam Eswar. Application of Big Data on Facility Interoperability using Python. International Conference on Global Environmental Changes and Sustainable Development (2018): 02. Print.