Selection of browsers for smartphones: a fuzzy hybrid approach and machine learning technique.

The telecommunication segment has grown tremendously over the past few decades. Particularly smartphones have now turned out to be essential and have outperformed many gadgets like computers, cameras, etc. In this current scenario, smartphones become an essential product for all kinds of consumers such as students, teachers, businessmen, etc. And the consumers also like an extensive number of enhanced and better-quality features being embedded into them. Along with this growth, there is a fast growth of mobile application software providers also. Apart from calling, many consumers use smartphones for browsing the internet. Many android developers provide browser application software with several advancements. This puts the consumers into confusion to select a better browser for their smartphone to accomplish their requirements. Hence the consumers need a proven methodology to select a better browser for their smartphones. To select a better browser, in this paper a hybrid multi-criteria decision making model is proposed by integrating grey relational analysis (GRA) and fuzzy analytical hierarchy process (FAHP). The findings are compared and validated through a machine learning approach also. [ABSTRACT FROM AUTHOR]