کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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497511 | 862907 | 2006 | 12 صفحه PDF | دانلود رایگان |
A neuro-fuzzy computing provides the system identification and interpretability of fuzzy models and learning capability of neural networks in a single system. In the last decade, various neuro-fuzzy systems have been developed. Among them, adaptive neuro-fuzzy inference system (ANFIS) provides a systematic and directed approach for model building and gives the best possible design parameters in minimum time. They have got wide acceptance for modelling many real world problems. One such problem frequently encountered is the effects of noise pollution on human work efficiency. From the literature survey, it is observed that the three most important factors influencing human work efficiency are noise level, type of task, and exposure time. The cause effect relationships of these parameters are complex, uncertain, and non-linear in nature. Therefore, it is quite difficult to properly examine it by conventional methods. Hence, an attempt is made in this paper 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. The model is implemented on Fuzzy Logic Toolbox of MATLAB© using ANFIS. The data used in the present study is obtained with the help of the original fuzzy model developed by the authors. Out of the total input/output data sets, 80% was used for training the model and 20% for checking to validate the model.
Journal: Applied Soft Computing - Volume 6, Issue 3, March 2006, Pages 283–294