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Electricity demand forecasting is an important index to make power development plan and dispatch the loading of generating units in order to meet system demand. In order to improve the accuracy of the forecasting, we apply the feedforward neural network for electricity demand forecasting. Inspired by the idea of artificial fish swarm algorithm, in this paper we proposed one hybrid evolutionary algorithm...
Nowadays, owing to the accelerated growth in the development of information technology, the aviation industry plays a prominent role in Chinese economy. Therefore, the accurate prediction for the number of international airlines helps in making major decisions in technological reform. In order to analyze the number of international airlines in China efficiently, in this paper, fuzzy adaptive PSO algorithm...
Short-term electricity demand forecasting for the next hour to several days out is one of the most important tools by which an electric utility plans and dispatches the loading of generating units in order to meet system demand. But there exists chaos in electricity systems to a great extent. Complicated electricity systems are nonlinear systems and the forecasting is very complex in nature and quite...
In this paper, a new approach to ARMA model identification using evolutionary particle swarm optimization (PSO) algorithm has been proposed. ARMA is a popular method to analyze stationary univariate time series data. Stationarity checking, model identification, model estimation and model checking are usually four main stages to build an ARMA model and model identification is the most important stage...
Recently some cities' investments on fix assets increase too fast that lead to a property bubble. In order to prevent the overheating of real estate investment, this paper presents a pre-warning system developed to monitor and provide pre-warning to the governmental decision makers in real estate market. In the overall structure plan, the warning classification system is the most important so that...
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