A great challenge for today’s companies is not only how to adapt to the changing business environment but also how to gain a competitive advantage from the way in which they choose to do so. As a basis for achieving such advantages, companies have started to seek to improve the performance of various operations. Forecasting is one of them; it is important to firms because it can help ensure tha...

Uncertainty represented in visualizations is often ignored or misunderstood by the non-expert user. The National Hurricane Center displays hurricane forecasts using a track forecast cone, depicting the expected track of the storm and the uncertainty in the forecast. Our goal was to test whether different graphical displays of a hurricane forecast containing uncertainty would influence a decisio...

Abstract: 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 mod...

High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper propo...

The accuracy of forecasting of electrical load for the electricity industry has a vital significance in the renewal of economic structure as well as various equations including: purchasing and producing energy, load fluctuation, and the development of infrastructures. Its short-term forecasting has a significant role in designing and utilizing power systems and in the distribution systems and h...

Accurate air-conditioning load forecasting is the precondition for the optimal control and energy saving operation of central air-conditioning system. However, the single forecasting method, such as autoregressive integrated moving average (ARIMA), grey model (GM), multiple linear regression (MLR) and artificial neural network (ANN), has not enough accuracy. In order to improve the accuracy of ...

Electricity demand forecasting can provide the scientific basis for the country to formulate the power industry development strategy and the power-generating target, which further promotes the sustainable, healthy and rapid development of the national economy. In this paper, a new mathematical hybrid method is proposed to forecast electricity demand. In line with electricity demand feature, the...

Wind forecasting is critical in the wind power industry, yet forecasting errors often exist. In order to effectively correct the forecasting error, this study develops a weather adapted bias correction scheme on the basis of an average bias-correction method, which considers the deviation of estimated biases associated with the difference in weather type within each unit of the statistical samp...

in recent years, use of fuzzy collection theories for modeling of hydrological phenomenon's that is including complexity and uncertainly is considered scholars. so in this research, adaptive neuro-fuzzy inference system (anfis) is used for performance of river flow forecasting process. in this research, three parameters such as raining, temperature and daily discharge of lighvanchai basin ...

the emphasis of this paper is the role of volatility indices on improvement artificial neural networks (anns) forecasting models for the daily usd/eur and usd/gbp exchange rates two volatility indices are used. first; the realized volatility, which is based on intra-daily data, and second the garch volatility. they are applied into the model in two ways. firstly, the lagged volatility index is ...