Many factors impact a city’s water consumption, including population distribution, average household income, water prices, water conservation programs, and climate. Of these, however, meteorological effects are considered to be the primary determinants of water consumption. In this study, the effects of climate on residential water consumption in Las Vegas, Nevada, were examined during the peri...

Environmental degradation and Economic growth are two important proofs in sustainable development which are followed by steel industry. In this case, energy and environmental damages as sustainability patterns of environment have been investigated in three different dust collectors to select the most environmentally suitable dust collector for electric furnace. In this article, the consumption ...

Steel industry is one of the leading industries in the world. Today it is also one of the fundamental and strategic industries of the world. Per capita production and consumption amount of steel are used as a criterion for evaluation of country development. Furthermore, attention to technological innovations is assumed so much crucial to access the international markets of steel industrie...

This paper applies artificial neural networks to forecast gasoline consumption. The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. To forecast gasoline consumption (GC), the ANN uses previous ...

Lettau and Ludvigson (2001a) show that the consumption-wealth ratio—the error term from the cointegration relation among consumption, net worth, and labor income—forecasts stock market returns out of sample. In this paper, we reexamine their evidence using real-time data. Consistent with the early authors, we find that consumption and labor income data are subject to substantial revisions, whic...

Prediction of residential natural gas consumption in 20 next years was performed in this paper. Artificial neural network (ANN) was used to predict the natural gas in the Kerman, the biggest province in the Iran. The Kerman is included with ten important cities where gas consumption was estimated in each city. The minimum temperature in each year, population growth rate and number of each year ...

Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is eas...