This chapter covers different approaches that may be taken when building an ensemble method, through studying specific examples of each approach from research conductded by the author. A method called Negative Correlation Learning illustrates a decision level combination approach with individual calssifiers trained co-operatively. The Model level combination paradigm is illustrated via a tree c...

The paper introduces a modified version of the classical Coupon Collector’s Problem entailing exchanges and cooperation between multiple players. Results of the development show that, within a proper Markov framework, the complexity of the Cooperative Multiplayer Coupon Collectors’ Problem can be attacked with an eye to the modeling of social strategies and community behaviors. The cost of coop...

In recent years, authors have focused on modeling and forecasting volatility in financial series it is crucial for the characterization of markets, portfolio optimization and asset valuation. One of the most used methods to forecast market volatility is the linear regression. Nonetheless, the errors in prediction using this approach are often quite high. Hence, continued research is conducted t...

in this paper semi-markov models are used to forecast the triple dimensions of next earthquake occurrences. each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. semi-markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. in semi-markov models each zone can be considered as a state...

Stock trend forecasting is a one of the main factors in choosing the best investment, hence prediction and comparison of different firms’ stock trend is one method for improving investment process. Stockholders need information for forecasting firm’s stock trend in order to make decision about firms’ stock trading. In this study stock trend, forecasting performs by data mining algorithm. It sho...

in recent years, various time series models have been proposed for financial markets forecasting. in each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. many researchers have compared different time series models together in order to determine more efficient ...

This paper presents a new combined forecasting method that is guided by the soft set theory (CFBSS) to predict business failures with different sample sizes. The proposed method combines both qualitative analysis and quantitative analysis to improve forecasting performance. We considered an expert system (ES), logistic regression (LR), and support vector machine (SVM) as forecasting components ...

Through a series of studies, involving over 400 companies over 20 years, the University of Tennessee Sales Forecasting Research Team has developed a vision of world-class forecasting. This presentation will articulate that vision, and participants will leave with a framework for benchmarking their own forecasting processes. Specifically, attendees will learn: • What forecasting excellence consi...