In this paper, we evaluate the capability to detect traffic anomalieswith Shewhart, CUSUM, andEWMA control charts. In order to cope with seasonal variation and serial correlation, control charts are not applied to traffic measurement time-series directly, but to the prediction errors of exponential smoothing and Holt-Winters forecasting. The evaluation relies on flow data collected in an ISP ba...

Modeling financial volatility is an important part of empirical finance. This paper provides a literature review of the most relevant volatility models, with a particular focus on forecasting models. We firstly discuss the empirical foundations of different kinds of volatility. The paper, then, analyses the non-parametric measure of volatility, named realized variance, and its empirical applica...

This study investigates the algorithm of effective option trading strategy based on the superior volatility forecasts using actual option price data in Taiwan stock market. Forecast evaluation supports the significant incremental explanatory power of investor sentiments on the fitting and forecasting of future volatility to its adversarial multiple-factor model, especially the market turnover a...

Wind power forecasting is recognized as a means to facilitate large scale wind power integration into power systems. Recently, focus has been given on developing dedicated short-term forecasting approaches for the case of large and sharp wind power variations, so-called ramps. Accurate forecasts of specific ramp characteristics (e.g. timing, probability of occurrence, etc) are important since t...

Introduction of ubiquitous technology is changing our daily living environment. Particularly, the new IT services applying the RFID and USN technology are used in wide ranging areas such as the weather, logistics, urban facility management and agriculture. However, information security of such new services closely related to our daily lives is very weak. This paper intends to evaluate the safet...

Energy demand pattern have many variables related to uncertainty behavior. These lead to a higher estimation rate of energy demand forecasting. However, two problems need to be overcome. The first problem is the fitness evaluation in energy demand forecasting model in which more than one variable are included, and the second problem is the local optimality that single algorithm fails to solve. ...

In this paper, we investigate the impact of the non-numerical information on exchange rate changes and that of ensemble multiple classifiers on forecasting exchange rate between U.S. dollar and Japanese yen. We first engage the fuzzy comprehensive evaluation model to quantify the nonnumerical fundamental information. We then design a single classifier, addressing the impact of exchange rate cha...

Precise flood forecasting is desirable so as to have more lead time for taking appropriate prevention measures as well as evacuation actions. Although conceptual prediction models have apparent advantages in assisting physical understandings of the hydrological process, the spatial and temporal variability of characteristics of watershed and the number of variables involved in the modeling of t...

Coastal Ocean Forecasting: system integration and evaluation V.H. Kourafalou, P. De Mey, M. Le Hénaff, G. Charria, C.A. Edwards, R. He, M. Herzfeld, A. Pascual, E.V. Stanev, J. Tintoré, N. Usui, A.J. van der Westhuysen, J. Wilkin & X. Zhu a University of Miami, Rosenstiel School of Marine and Atmospheric Sciences, Miami, FL, USA b LEGOS, Laboratoire d'Etudes en Géophysique et Océanographie Spat...

A reliable multi-step predictor is very useful to a wide array of applications to forecast the behavior of dynamic systems. The objective of this paper is to develop a more robust data-driven predictor for time series forecasting. Based on simulation analysis, it is found that multi-step-ahead forecasting schemes based on step inputs perform better than those based on sequential inputs. It is a...