Prophecy Oxygen Levels at High Altitudes Using Fuzzy C-means Clustering
 
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Publication date: 2019-04-24
 
Eurasian J Anal Chem 2018;13(Engineering and Science SP):emEJAC181264
 
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ABSTRACT
Data Analysis is an efficient technique to implement the analysis on an immense data, which can be structured, semi-structured or even unstructured. Various advanced data analysis techniques from statistics, artificial intelligence and others can be used for analyzing data in the areas of medical diagnosis, user pattern extraction, image extraction, market research, cell segmentation and spatial data extraction. Predictive analysis is one of the methods in data analysis used to identify the predictions on future happenings which are not known in advance exactly. The key benefits of predictive analysis are preventing risks, managing resources, and strategic decision making. This paper focuses on the benefit of preventing risks factors by analyzing environment at high altitude areas through predicting the oxygen levels using Fuzzy C Means algorithm. The percentage of oxygen level is not same at sea level as it is in hilly areas which have high altitudes. Less oxygen in atmosphere may lead to short of breath causes chronic illness to people in all age groups. This study focuses on the collection and processing of data, identifying the prediction model, the results and the improvisation in the future work.
eISSN:1306-3057