Bias Correction for Forecasting PM2.5 Concentrations Using Measurement Data from Monitoring Stations by Region
نویسندگان
چکیده
منابع مشابه
A comparative study of quantitative mapping methods for bias correction of ERA5 reanalysis precipitation data
This study evaluates the ability of different quantitative mapping (QM) methods as a bias correction technique for ERA5 reanalysis precipitation data. Climate type and geographical location can affect the performance of the bias correction method due to differences in precipitation characteristics. For this purpose, ERA5 reanalysis precipitation data for the years 1989-2019 for 10 selected syno...
متن کاملMachine Learning Models for Housing Prices Forecasting using Registration Data
This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...
متن کاملAutomated Measurement Stations for River Water Quality Monitoring
The recent technological developments in analysis and sampling systems as well as the need for high resolution datasets for integrated water quality modelling have led to the increased application of Automated Measurement Stations (AMS) in river water quality monitoring projects. However, the investment and maintenance costs of AMS are high and therefore considerable prior research is essential...
متن کاملForecasting Stock Trend by Data Mining Algorithm
Stock trend forecasting is a one of the main factors in choosing the best investment, hence prediction and comparison of different firms’ stock trend is one method for improving investment process. Stockholders need information for forecasting firm’s stock trend in order to make decision about firms’ stock trading. In this study stock trend, forecasting performs by data mining algorithm. It sho...
متن کاملExogenous Measurements from Basic Meteorological Stations for Wind Speed Forecasting
This research presents a comparative analysis of wind speed forecasting methods applied to perform 1 h-ahead forecasting. The main significant development has been the introduction of low-quality measurements as exogenous information to improve these predictions. Eight prediction models have been assessed; three of these models [persistence, autoregressive integrated moving average (ARIMA) and ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Asian Journal of Atmospheric Environment
سال: 2018
ISSN: 1976-6912,2287-1160
DOI: 10.5572/ajae.2018.12.4.338