An Optimized Algorithm for Biological and Environmental Problems

Authors

  • Yasmeen  M.Tech. Scholar, Computer Science & Engineering Ganga Institute of Technology and Management Kablana, Jhajjar, Haryana, India
  • Dr. Neetu Sharma  Associate Professor, Computer Science & Engineering Ganga Institute of Technology and Management Kablana, Jhajjar, Haryana, India

Keywords:

Medical, Data Mining, Environmental, Problems of Data Mining.

Abstract

In the past(Earlier), most of the researchers used data mining techniques in many area. A lot of amounts of data have been collected from various scientific domains such as Geo sciences, Astronomy, Meteorology, Geology and Biological sciences. Data mining techniques and tools used by researchers and scientist in biological and environmental problems also. In biological science data mining used in sequences alignment is based on the fact that all living organisms are related by evolution.ntal science data mining concept used in predicting data such as earthquakes and landslide etc. This Research paper highlights on the wide survey of Protein sequences, (DNA, RNA) sequences, cancer prediction, Relational and semantic data mining for biomedical research area. Health care data, multiagent framework for bio data mining, predicting earthquakes, landslide and spatial data in distributed data mining algorithms and tools.

References

  1. Biological Data Mining edited By Jake Y. Chen and Stefano Lonardi.
  2. Scala For Data Science Leverage the power of scala tool for build to scalable , robust Data Science Applications.
  3. Next Generation Of Data Mining by Rajeev Motvani and Vipin Kumar.
  4. Tutorial points for data mining problems of biological science and environmental science.

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Published

2018-04-30

Issue

Section

Research Articles

How to Cite

[1]
Yasmeen, Dr. Neetu Sharma, " An Optimized Algorithm for Biological and Environmental Problems, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.233-237, March-April-2018.