Abstract
Within a few years, cloud computing emerged as one of the hottest technologies in the IT field. It provides computational resources as general utilities that can be leased and released by users in an on-demand fashion. Cloud computing is rapidly growing interest in many companies around the globe, but adopting cloud computing comes with greater risks, which need to be assessed. In this research, an adaptive neuro-fuzzy inference system (ANFIS) has been applied to assess risk factors in cloud computing. Different membership functions were used for training the data. The model combined the modeling function of fuzzy inference with the learning ability of neural networks. Empirical results illustrate that ANFIS is very effective in modeling cloud-computing risks.
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Acknowledgment
This work was supported by the IT4Innovations Centre of Excellence Project (CZ.1.05/1.1.00/02.0070), funded by the European Regional Development Fund and the national budget of the Czech Republic via the Research and Development for Innovations Operational Programme and by Project SP2015/146 “Parallel Processing of Big Data 2” of the Student Grant System, VŠB-Technical University of Ostrava.
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Ahmed, N., Abraham, A. (2016). Neuro-Fuzzy Model for Assessing Risk in Cloud Computing Environment. In: Abraham, A., Wegrzyn-Wolska, K., Hassanien, A., Snasel, V., Alimi, A. (eds) Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015. Advances in Intelligent Systems and Computing, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-319-29504-6_14
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