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Work Efficiency Prediction of Persons Working in Traffic Noise Environment Using Adaptive Neuro Fuzzy Inference System (ANFIS) Models

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Yadav M. , Tandel B.

Archives of Acoustics

2021

tom Vol. 46, No. 4

677--683

A study was carried to assess the effect of traffic noise pollution on the work efficiency of shopkeepers in Indian urban areas. For this, an extensive literature survey was done on previous research done on similar topics. It was found that personal characteristics, noise levels in an area, working conditions of shopkeepers, type of task they are performing are the most significant factors to study effects on work efficiency. Noise monitoring, as well as a questionnaire survey, was done in Surat city to collect desired data. A total of 17 parameters were considered for assessing work efficiency under the influence of traffic noise. It is recommended that not more than 6 parameters should be considered for ANFIS modeling hence, before opting for the ANFIS modeling, most affecting parameters to work efficiency under the influence of traffic noise, was chosen by Structural Equation Model (SEM). As a result of the SEM model, two ANFIS prediction models were developed to predict the effect on work efficiency under the influence of traffic noise. R squared for model 1, for training data was 0.829 and for testing data, it was 0.727 and R squared for model 2 for training data was 0.828 and for testing data, it was 0.728. These two models can be used satisfactorily for predicting work efficiency under traffic noise environment for open shutter shopkeepers in tier II Indian cities.

Structural Equation Model-Based Selection and Strength Co-Relation of Variables for Work Performance Efficiency Under Traffic Noise Exposure

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Yadav M. , Tandel B.

Archives of Acoustics

2021

tom Vol. 46, No. 1

155--166

In this work, we integrated exploratory factor analysis (EFA) followed by structural equation modeling (SEM) to assess the work performance efficiency under the traffic noise environment for open shutter shopkeepers in the Indian urban context. 706 valid questionnaire responses by personal interviews in local language were collected from open shutter shopkeepers exposed to noise level (Leq) of 77 dBA for 12 to 14 hours daily. The questionnaire was prepared based on demographics, environmental conditions, and primary effects of noise pollution. Among which four common latent factors which summaries 17 questionnaire response items were obtained by exploratory factor analysis, which are “Impacts of noise” (IM), “Environmental conditions” (EC), “Personal characteristics” (PC) and “Work efficiency” (WE). The associations between the individual latent factors were studied by the structural equation model method in AMOS software. Validation of the constructed model was carried out by testing the proposed hypothesis as well as goodness-of-fit indices like Absolute fit, Incremental fit, and Parsimonious fit indices. The effect of specific latent factors derived on the work efficiency of shopkeepers in the noisy area was characterized by the path coefficients estimated in the SEM model. It was found that work performance efficiency (WE) was greatly influenced by the primary impacts of noise pollution like annoyance, stress, interference in spoken communication, which was associated with the latent factor “Impacts of noise” (IM) with a path coefficient of 0.931. The second latent factor “Environmental conditions” (EC), which was associated with parameters like ambient temperature and humidity, showed less path coefficient of 0.153. And lastly, a latent factor called “Personal characteristics” (PC) associated with age, experience, education, showed the least path coefficient of 0.05. The work efficiency of open shutter shopkeepers working in a highly noisy commercial area is profoundly affected by the prominent effects of noise pollution and least affected by ambient environmental conditions as well as their personal characteristics. The developed model clarified some casual relationships among complex systems in the study of noise exposure on individuals n tier 2 cities in the Indian context and may help other researchers to study of tier I and tier III cities.