نتایج جستجو برای: forecasting error
تعداد نتایج: 292207 فیلتر نتایج به سال:
The aim of the short term load forecasting is to forecast the electric power load for unit commitment, evaluating the reliability of the system, economic dispatch, and so on. Short term load forecasting obviously plays an important role in traditional non-cooperative power systems. Moreover, in a restructured power system a generator company (GENCO) should predict the system demand and its corr...
Forecasting is a systematic attempt to examine the future by inference from known facts. Sales forecasting is an ballpark figure of sales during a specified future period. Formerly, it was a manual process using the mathematical formulas. Due to the advent of computer the process of sale forecasting is fast and accurate. Machine learning, a subfield of Artificial Intelligence, has many algorith...
This research conducts an error analysis between the forecasting value and the actual value of steel demand of 2010 in China, which is based on the analysis of forecasting methods and their results of Chinese steel demand in the existing studies, and then forecasts China’s steel demand in 2015 by making use of a combined forecasting method. The combined forecasting method includes two stages. I...
Accurate forecasting of annual gas consumption of the country plays an important role in energy supply strategies and policy making in this area. Markov chain grey regression model is considered to be a superior model for analyzing and forecasting annual gas consumption. This model Markov is a combination of the Markov chain and grey regression models. According to this model, the residual er...
In order to improve the accuracy of grain production forecasting, this study proposed a new combination forecasting model, the model combined stepwise regression method with RBF neural network by assigning proper weights using inverse variance method. By comparing different criteria, the result indicates that the combination forecasting model is superior to other models. The performance of the ...
The problem of fuzzy time series forecasting plays an important role in many scientific areas such as statistics and neural networks. While forecasting fuzzy time series, most of forecasting applications use the same length of intervals. The determination of length of intervals is significant and critical in fuzzy time series forecasting. The usage of convenient performance measure may also hav...
The accurate forecasting of carbon dioxide (CO2) emissions from fossil fuel energy consumption is a key requirement for making energy policy and environmental strategy. In this paper, a novel quantum harmony search (QHS) algorithm-based discounted mean square forecast error (DMSFE) combination model is proposed. In the DMSFE combination forecasting model, almost all investigations assign the di...
Accurate electricity price forecasting plays an important role in the profits of electricity market participants and the healthy development of electricity market. However, the electricity price time series hold the characteristics of volatility and randomness, which make it quite hard to forecast electricity price accurately. In this paper, a novel hybrid model for electricity price forecastin...
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