In this paper, based on grey system theory, the general GM(1,1) forecasting model for the growth of Japanese Larch in Liaoning Province was set up and it has been proof-tested in model precision.Verified by use of the dates of the Japanese Larch with age of 21 and 22, it has been proved that the model was effective in practice. The relative error of GM(11) model for mean DBH was 2.4%and 3.69%, ...

In this paper we present an application for the construction of mutual fund portfolios. It is based on a combination of Intelligent Methods, namely an argumentation based decision making framework and a forecasting algorithm combining Genetic Algorithms (GA), MultiModel Partitioning (MMP) theory and Extended Kalman Filters (EKF). The argumentation framework is employed in order to develop mutua...

We explain how the training data can be separated into clean information and unexplainable noise. Analogous to the data, the neural network is separated into a time invariant structure used for forecasting, and a noisy part. We propose a unified theory connecting the optimization algorithms for cleaning and learning together with algorithms that control the data noise and the parameter noise. T...

The basic science of turbulence has been known for many years, yet the knowledge has hardly become a part of operational aviation turbulence forecasting. The history of turbulence forecasting, which has primarily concentrated at elevations above the boundary layer, has been an amalgamation of empirical rules of thumb and forecaster intuition, not of strong theory and conceptual models. Turbulen...

Product technology maturity foresting is vital for any enterprises to hold the chance for innovation and keep competitive for a long term. The Theory of Invention Problem Solving (TRIZ) is acknowledged both as a systematic methodology for innovation and a powerful tool for technology forecasting. Based on TRIZ, the state -of-the-art on the technology maturity of product and the limits of applic...

In this paper, the time series prediction is as a measure. At the same time, the optimal combination forecast using each method can be defined as the actual impact measurement value of true. Effect of its theoretical estimation has error correlation coefficient values. The optimal weighted linear combination is the theoretical prediction which can be proved, also, simple averaging method is lin...

We use game theory and Santa Fe Artificial Stock Market, an agent-based model of an evolving stock market, to study the optimal frequency for traders to revise their market forecasting rules. We discover two things: There is a unique strategic Nash equilibrium in the game of choosing forecast revision rates, and this equilibrium is sub-optimal in the sense that traders’ earnings are not maximiz...

Betting on the most promising new ideas is key to creativity and innovation in organizations, but predicting the success of novel ideas can be difficult. To select the best ideas, creators and managers must excel at creative forecasting, the skill of predicting the outcomes of new ideas. Using both a field study of 339 professionals in the circus arts industry and a lab experiment, I examine th...

Wind speed plays a very important role in the scheduling of power systems and dynamic control of wind turbine. Wind speed forecasting has become one of the most important issue for wind energy conversion recently. Adaptive and reliable methods and techniques for wind speed forecasting are urgently needed in view of its stochastic nature that varies from time to time and from site to site. Back ...

The time evolution of aggregate economic variables, such as stock prices, is affected by market expectations of individual investors. Neo-classical economic theory assumes that individuals form expectations rationally, thus enforcing prices to track economic fundamentals and leading to an efficient allocation of resources. However, laboratory experiments with human subjects have shown that indi...