title: A stochastic simulation framework for the prediction of strategic noise mapping and occupational noise exposure using the random walk approach.
abstract: Strategic noise mapping provides important information for noise impact assessment and noise abatement. However, producing reliable strategic noise mapping in a dynamic, complex working environment is difficult. This study proposes the implementation of the random walk approach as a new stochastic technique to simulate noise mapping and to predict the noise exposure level in a workplace. A stochastic simulation framework and software, namely RW-eNMS, were developed to facilitate the random walk approach in noise mapping prediction. This framework considers the randomness and complexity of machinery operation and noise emission levels. Also, it assesses the impact of noise on the workers and the surrounding environment. For data validation, three case studies were conducted to check the accuracy of the prediction data and to determine the efficiency and effectiveness of this approach. The results showed high accuracy of prediction results together with a majority of absolute differences of less than 2 dBA; also, the predicted noise doses were mostly in the range of measurement. Therefore, the random walk approach was effective in dealing with environmental noises. It could predict strategic noise mapping to facilitate noise monitoring and noise control in the workplaces.
authors: Faculty of Civil Engineering, Universiti Teknologi Malaysia, Skudai, Malaysia.
authors: Lim Ming
authors: LM
authors: Han
authors: Faculty of Civil Engineering, Universiti Teknologi Malaysia, Skudai, Malaysia.
authors: Zaiton
authors: Z
authors: Haron
authors: Faculty of Civil Engineering, Universiti Teknologi Malaysia, Skudai, Malaysia.
authors: Khairulzan
authors: K
authors: Yahya
authors: Faculty of Civil Engineering, Universiti Teknologi Malaysia, Skudai, Malaysia.
authors: Suhaimi Abu
authors: SA
authors: Bakar
authors: Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai, Malaysia.
authors: Mohamad Ngasri
authors: MN
authors: Dimon
mesh_terms: D004777:Environment; D006801:Humans; D015233:Models, Statistical; D009623:Noise, Occupational; D017132:Workplace