Prediction markets provide an efficient means to assess uncertain quantities from forecasters. Traditional and competitive strictly proper scoring rules have been shown to incentivize players to provide truthful probabilistic forecasts. However, we show that when those players can cooperate, these mechanisms can instead discourage them from reporting what they really believe. When players with ...

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...

introduction: voxel based morphometry is a type of statistical parametric mapping that can be used to investigate the effect of diseases such as epilepsy, alzheimer's disease and parkinson's disease or other agent such as skills on brain structure (white matter, gray matter and cerebrospinal fluid). the aim of this study is evaluate the effectiveness of this method in detection of dif...

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...

Previous machine learning models usually faced the problem of poor performance, especially for aquatic product supply chains. In this study, we proposed a coupling model Shapely value-based to predict CCL demand products (CCLD-AP). We first select key impact indicators through gray correlation degree and finally determine indicator system. Secondly, prediction, principal component regression an...

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...