in the paper a model to predict the concentrations of particulate matter pm10, pm2.5, so2, no, co and o3 for a chosen number of hours forward is proposed. the method requires historical data for a large number of points in time, particularly weather forecast data, actual weather data and pollution data. the idea is that by matching forecast data with similar forecast data in the historical data...

The article provides an analysis of the forecast hydrocarbon ratios based on data extracted. Various methods are used in technological processes gas extraction order to build models final gas-condensate yield coefficients. It is important select most accurate and reliable determine recoverable reserves condensate fields operated flood depletion regimes or assess effectiveness geological technic...

Energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. However, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. Accordingly, in this paper a new strategy is proposed for electricity price forecast. The forecast strategy includes Wavelet Transform (WT...

It is well known that coalmine gas concentration forecasting is very significant to ensure the safety of mining. Owing to the high-frequency, non-stationary, fluctuations, and chaotic properties of the gas concentration time series, a gas concentration forecasting model utilizing the original raw data often leads to an inability to provide satisfying forecast results. A hybrid forecasting model...

Public attention on natural gas price, which reflects the demand dynamics, is considered as a new factor to influence the movement of price. So investigate the impact of public attention on natural gas price is an innovative research issue in energy economics. This paper innovatively constructs a measure of public attention and examines its impact on natural gas price. A data set generated from...

the purpose of this research is to investigate the relationship between earnings variabilityand earnings forecast using neural networks in companies listed on tehran stock exchange. theresearch is of the library and analytical-causal study type, and is based on panel data analysis andneural networks. in this research, financial information of 98 companies from 19 industries intehran stock excha...