Many forecasting models based on the concepts of Fuzzy time series have been proposed in the past decades. These models have been widely applied to various problem domains, especially in dealing with forecasting problems in which historical data are linguistic values. In this paper, we present a new fuzzy time series forecasting model, which uses the historical data as the universe of discourse...

The forecasting problem is one of the main environmental problems that need efficient software tools. More concrete, it can mean meteorological/weather forecasting, air/soil/water pollution forecasting, flood forecasting and so on. Several methods based on artificial intelligence were proposed by taken into account that they can offer more informed methods that use domain specific knowledge, an...

Demand Forecasting is an essential process for any firm whether it is a supplier, manufacturer or retailer. A large number of research works about time series forecast techniques exists in the literature, and there are many time series forecasting tools. In many cases, however, selecting the best time series forecasting model for each time series to be dealt with is still a complex problem. In ...

Despite of over a century of scientific effort, the understanding in earthquake forecasting remains immature. Moreover, even the theoretical possibility of earthquake forecasting is debatable. Especially problematic is a possibility of an effective shortand intermediate-term earthquake forecasting. The aim of this paper is to present the new evidence in support of possibility of the shortand in...

Time series forecasting has a long track record in many application areas. In forecasting research, it has been illustrated that finding an individual algorithm that works best for all possible scenarios is hopeless. Therefore, instead of striving to design a single superior algorithm, current research efforts have shifted towards gaining a deeper understanding of the reasons a forecasting meth...

According to Siegfried et al. (1991, 199), most economists agree that the goal of an economics education is to enable students to “think like an economist,” which involves using deductive reasoning, problem-solving skills, and creative thinking in conjunction with simplified models to understand economic events. When economic thinking is applied to the real world, it almost always involves a pr...

Problem statement: Forecasting of electricity load demand is an essential activity and an important function in power system planning and development. It is a prerequisite to power system expansion planning as the world of electricity is dominated by substantial lead times between decision making and its implementation. The importance of demand forecasting needs to be emphasized at all level as...

Enhancing sales and operations planning through forecasting analysis and business intelligence is demanded in many industries and enterprises. Publishing industries usually pick attractive titles and headlines for their stories to increase sales, since popular article titles and headlines can attract readers to buy magazines. In this paper, information retrieval techniques are adopted to extrac...

Clustering is a powerful tool which has been used in several forecasting works, such as time series forecasting, real time storm detection, flood forecasting and so on. In this paper, a generic methodology for weather forecasting is proposed by the help of incremental K-means clustering algorithm. Weather forecasting plays an important role in day to day applications.Weather forecasting of this...