In financial field, outliers represent volatility of stock market, which plays an important role in management, portfolio selection and derivative pricing. Therefore, forecasting outliers of stock market is of the great importance in theory and application. In this paper, the problem of predicting outliers based on adaptive ensemble models of Extreme Learning Machines (ELMs) is considered. We found out that the proposed model is applicable for outlier forecasting and outperforms the methods based on autoregression (AR) and extreme learning machine (ELM) models.

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BackgrBackgr Backgr Backgr Background: ound: ound: ound: ound: Alzheimer's disease is a form of dementia, mainly strikes people in their 60 and 70s. While no one cause has been determined, researchers have identified certain factors which may put people at a higher risk of developing the disease. Iran's Alzheimer Association has announced that more than 35% of people over 80 years old suffers from this problem across the country. This paper aims to investigate modifiable risk factors of Alzheimer's disease based on Kaplan-Meier estimator and Cox regression analysis (proportional hazard model) and to find out which factors are related to developing of this disease.

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