Steel consumption is a critical factor affecting pricing decisions and a key element to achieve sustainable industrial development. Forecasting future trends of steel consumption based on analysis of nonlinear patterns using artificial intelligence (AI) techniques is the main purpose of this paper. Because there are several features affecting target variable which make the analysis of relations...

Abstract—We regard forecasting of energy consumption by private production areas of a large industrial facility as well as by the facility itself. As for production areas, the forecast is made based on empirical dependencies of the specific energy consumption and the production output. As for the facility itself, implementation of the task to minimize the energy consumption forecasting error is...

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...

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...

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...

Accurate prediction of the future electricity consumption is crucial for production electricity management. Since the storage of electrical energy is very difficult, reliable and accurate prediction of power consumption is important. Different approaches for this purpose were used. In this paper, Grey model (1,1) based on grey system theory has been used for forecasting results. Annual electric...

Forecasting the life of concrete infrastructures in corrosive environments presents a long-standing and socially relevant challenge in science and engineering. Chloride-induced corrosion of reinforcing steel in concrete is the main cause for premature degradation of concrete infrastructures worldwide. Since the middle of the past century, this challenge has been tackled by using a conceptual ap...

This work develops Artificial Neural Networks (ANN) models applied to predict the consumption forecasting considering climatic factors. It is intended to verify the influence of climatic factors on the electricity consumption forecasting through the ANN. The case study is applied in the Campinas city, Brazil. This work used Perceptron and Backpropagation ANN models. The specific goal is compari...