A new method of ozone forecasting using fuzzy expert and neural network systems
A new method of ozone forecasting using fuzzy expert and neural network systems
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DOI：
10.1016/j.scitotenv.2003.11.009
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发表时间：
2004-06-05
影响因子：
9.8
通讯作者：
Kim, DS
中科院分区：
文献类型：
--
作者：
Heo, JS;Kim, DS
本研究描述了在韩国首尔四个监测点预测每日最大臭氧浓度的方法。开发的预测工具有模糊专家系统和神经网络系统。本文分析了1989-1999年汉城市地面和高海拔（500 hPa）站每小时的大气污染物和气象变量资料。开发了两种预报模型。第一个模型，第一部分，使用一个模糊专家系统，预测第二天出现高臭氧水平（等于或高于80 ppb）的可能性。第二个模型，即第二部分，使用神经网络系统预测第二天的日最大臭氧浓度。预报系统包括一个校正功能，以便在出现新的臭氧事件时更新现有模式。通过验证和增强，预测系统的准确性不断提高。(C) 2003 Elsevier B.V.版权所有
This study describes the method of forecasting daily maximum ozone concentrations at four monitoring sites in Seoul, Korea. The forecasting tools developed are fuzzy expert and neural network systems. The hourly data for air pollutants and meteorological variables, obtained both at the surface and at the high elevation (500 hPa) stations of Seoul City for the period of 1989-1999, were analyzed. Two types of forecast models are developed. The first model, Part I, uses a fuzzy expert system and forecasts the possibility of high ozone levels (equal to or above 80 ppb) occurring on the next day. The second model, Part II, uses a neural network system to forecast the daily maximum concentration of ozone on the following day. The forecasting system includes a correction function so that the existing model can be updated whenever a new ozone episode appears. The accuracy of the forecasting system has been improved continuously through verification and augmentation. (C) 2003 Elsevier B.V. All rights reserved.