Abstract
In this paper, an attempt has been made to develop a neuro-fuzzy model for predicting the effects of noise pollution on human work efficiency as a function of noise level, type of task, and exposure time. Originally, the model was developed using fuzzy logic based on literature survey. So, the data used in the present study has been synthetically generated from the previous fuzzy model. The model is implemented on Fuzzy Logic Toolbox of MATLAB© using adaptive neuro-fuzzy inference system (ANFIS). ANFIS discussed in this paper is functionally equivalent to Sugeno fuzzy model. Out of the total input/output data sets, 80% was used for training the model and 20% for checking purpose to validate the model.
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Zaheeruddin, Garima (2004). A Neuro-fuzzy Approach for Predicting the Effects of Noise Pollution on Human Work Efficiency. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_146
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