机械化露天煤矿噪声建模与噪声制图——以实例为例

Q4 Environmental Science

Pollution Research Pub Date : 2022-09-30 DOI:10.53550/pr.2022.v41i03.040

D. P. Tripathy, G. Parmar

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引用次数: 0

摘要

机械化程度的提高给露天矿带来了噪声和振动问题。噪音是由矿井里的每一项活动或机械产生的。将人工神经网络(ANN)和基于自适应网络的模糊推理系统(ANFIS)应用于某矿机械化露天矿机械噪声预测。为了寻找露天矿的实际噪声状况，将基于神经网络和基于神经网络的软计算模型(-Ã)与现有统计模型(ENM)的预测能力进行了比较。从本研究中可以看出，ANFIS的预测效果优于人工神经网络(MLPand BP)方法。本文还介绍了利用Kriging和IDW两种方法和ArcGIS编制露天矿噪声图的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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NOISE MODELLING AND NOISE MAPPING IN MECHANIZED OPENCAST COAL MINE - A CASE STUDY

Increased mechanization has generated noise and vibration problems in opencast mines. Noise isgenerated by every activity or machinery present in the mines. Artificial Neural Network (ANN)and Adaptive Network-based Fuzzy Inference System (ANFIS) was applied to predictmachinerynoise in a mechanized opencast coal mine. This paper dealt with comparison of theprediction capabilities of ANN and ANFIS based soft computing models vis-Ã -vis existingstatistical model (ENM) in order to find the actual noise status in an opencast coal mine. From thepresent study, it could be concluded that ANFIS gave better prediction results than the ANN (MLPand BP) methods. This paper also includes the preparation of a noise map in the opencast mine usingtwo methods (Kriging and IDW) and ArcGIS.

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来源期刊

Pollution Research Environmental Science-Water Science and Technology

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期刊介绍： POLLUTION RESEARCH is one of the leading enviromental journals in world and is widely subscribed in India and abroad by Institutions and Individuals in Industry, Research and Govt. Departments.