The increased need of content based image retrieval technique can be found in a number of different domains such as Data Mining, Education, Medical Imaging, Crime Prevention, Weather forecasting, Remote Sensing etc. An image retrieval system allows us to browse, search and retrieve the images. In early days because of very large image collections the manual annotation approach was more difficul...

Abstract Forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. This paper studies load consumption modeling in Hamedan city province distribution network by applying ESN neural network. Weather forecasting data such as minimum day temperature, average day temp...

Improving time series forecastingaccuracy is an important yet often difficult task.Both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. In this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...

The greenhouse effect and its extension affecting is one of the key issues to governments and academics currently. Study shows, CO2 produced from burning fossil fuels are liable 2/3 of the above-mentioned problems. CO2 emissions in China are mainly concentrated in the power plants. In this paper, Gray Markov method is used for long-term load forecasting, combined with the prediction of power ge...

For meeting the forecasting target of key technology indicators in the flotation process, a BP neural network soft-sensor model based on features extraction of flotation froth images and optimized by shuffled cuckoo search algorithm is proposed. Based on the digital image processing technique, the color features in HSI color space, the visual features based on the gray level cooccurrence matrix...

Energy is essential to the development of an economy and society. In recent years, China's rapid economic has created "China Miracle", but it also led a sharp increase in energy consumption China. To ensure achievement ambitious goal reaching carbon peak by 2030, great significance study total China order promote national conservation emission reduction actions. This paper constructs models GM(...

Abstract Wind power forecasting deals with the prediction of expected generation wind farms in next few minutes, hours, or days. The application machine learning techniques has become great interest due to their superior capability perform regression, classification, and clustering. Support vector regression (SVR) is a powerful suitable tool that been successfully used for forecasting. However,...

computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. nowadays, despite the numerous time series forecasting models propos...