Electricity cannot be stored and needs huge amount of capital so producers and consumers pay special attention to predict electricity consumption. Besides, time-series data of the electricity market are chaotic and complicated. Nonlinear methods such as Neural Networks have shown better performance for predicting such kind of data. We also need to analyze other variables affecting electricity c...

The performance of the Autoregressive Integrated Moving Average )ARIMA) model and Double and Holt-winters exponential smoothing techniques for forecasting the consumption of particleboard in Iran are compared. Annual time series data from 1978 to 2009 in the modeling process, and observations from 2010 to 2012 were used to check the accuracy of the models’ forecasting performance. Also, the mod...

This research work has addressed demand side flexibility in a smart grid oriented building. The principal purpose has been to build a short term forecasting model that will predict the next hour consumption. Three advanced methods of forecasting have been investigated for this purpose, the ARIMA (Autoregressive Integrated Moving Average) model, Artificial Neural Networks (ANN) and Support Vecto...

Artificial Neural Network (ANN) has been used in nonlinear systems modeling and simulation. One of the most useful and interesting factors of ANNs is forecasting. This paper discusses the application of ANNs to predict the long range energy consumption for a country. In this study the long-term energy consumption for the years ahead is predicted, exploiting ANN computational speed, ability to h...

A kind of power forecast model combined cellular genetic algorithm with BP neural network was established in this article. Mid-long term power demand in urban areas was done load forecasting and analysis based on material object of the actual power consumption in urban areas of Nanchang. The results show that this method has the characteristic of the minimum training times, the shortest consump...

Since the Brazilian inclusion in the global market, search for productivity and product quality improvement became essential for the companies to survive. However, due to energy costs rise, national steel industries are investing in electrical power generation in partnership with energy supply companies aiming at overall cost reduction. Therefore, actions that search for energy consumption redu...

Feature selection has as principal goal to find a representative space of minimal size from original set of larger size. Several research works have been developed on this problem. This paper presents Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Genetic Algorithms (GA), and Differential Evolution (DE) algorithms for feature selection from a database of an Electric Arc Furnace...

This paper investigates the relationship between cigarette consumption per capita net disposable income, cigarette price index, and per capita expenditure for education. In this empirical analysis the Johansen cointegration test is applied in conjunction with the vector error correction model. Finally, the forecasting technique of cigarettes consumption in Greece using cointegration models is p...

Roller is a key component of milling machine in iron and steel industry, with the development of industrial wireless technology. The online predictive maintenance of the roller plays an important role in effective production. But the harsh working environment – spray of cooling liquid, moving, high temperature and heavy shelter – cause low quality of wireless communication and need high reliabi...