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Traditional time series forecasting models are difficult to capture the nonlinear patterns. Support vector regression (SVR) has been successfully used to solve nonlinear regression and times series problems. However, parameters determination for a SVR model is competent to the forecasting...
Persistent link: https://www.econbiz.de/10014049169
Traditional time series forecasting models are difficult to capture the nonlinear patterns. Support vector regression (SVR) has been successfully used to solve nonlinear regression and times series problems. However, parameters determination for a SVR model is competent to the forecasting...
Persistent link: https://www.econbiz.de/10014049172
will introduce briefly the theory of BSDEs, provide some general background on their studies and review the classical …
Persistent link: https://www.econbiz.de/10013002719
This chapter surveys two methods for the optimization of real-world systems that are modelled through simulation. These methods use either linear regression metamodels, or Kriging (Gaussian processes). The metamodel type guides the design of the experiment; this design fixes the input...
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