1.1 Research Problem and the Objectives
In this research work, an attempt has been made to propose the appropriate soft computing
systems for predicting opencast mining machinery noise. Due to increasing mechanization
of mining operations, the noise level in mines have increased over years. To
maintain a good working environment, it is important to predict appropriate noise status
of machineries in mines. However, the available conventional noise prediction models
are mathematically complex and difficult to use. Soft computing based noise prediction
models were developed for prediction of the noise of machineries in different opencast
mines.
1.1.1 The Objectives of the Research Work
• To conduct noise survey in opencast mines to find the noise status of various heavy
earth moving machineries.
• To develop both non-frequency and frequency based statistical noise prediction
models for prediction of the noise of machineries in different opencast mines.
• To develop noise prediction models using different soft computing techniques viz.
Fuzzy Inference Systems (Mamdani, Takagi-Sugeno-Kang Fuzzy Inference System)
ii) Multi-layer Perceptron (MLP), iii) Radial Basis Function Network (RBFN) and
iv) Adaptive Network based Fuzzy Inference System (ANFIS)etc.
• To develop Fuzzy logic system based noise induced hearing loss prediction models.
• To select and recommend best soft-computing model for noise prediction in opencast
mines.
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