Titlebook: Soft Computing in Data Science; 4th International Co Bee Wah Yap,Azlinah Hj Mohamed,Michael W. Berry Conference proceedings 2019 Springer N

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A Hybrid Singular Spectrum Analysis and Neural Networks for Forecasting Inflow and Outflow Currency is study, i.e. simulation and real data about the monthly inflow and outflow of 12 currency denominations. The forecast accuracy of the proposed method is compared to ARIMAX model. The results of the simulation study showed that the hybrid SSA-NN with aggregate forecasting yielded more accurate fore

FUSE

Simulation Study of Feature Selection on Survival Least Square Support Vector Machines with Applicatis repeated 100 times. The simulation results show that the non-relevant predictors are often included in the model because the effect of confounding. For the application on clinical data (cervical cancer), the feature selection yields nine relevant predictors out of twelve predictors. The three pre

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Feature and Architecture Selection on Deep Feedforward Network for Roll Motion Time Series PredictioFPU). Root mean squared error (RMSE) is used as the model selection criteria. The results show that the ARIMA based 3 hidden layers DNN model with ReLU function outperforms with remarkable prediction accuracy among other models.

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Forecasting Value at Risk of Foreign Exchange Rate by Integrating Geometric Brownian Motionence levels. The GBM model is suitable to forecast the foreign exchange rate accurately using less than one year input data and using the log volatility formula. Lastly, the study verifies the feasibility of the integrated model for a one month holding period using the data shifting technique. In co

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rsprüchen geführt haben. Wir sind deshalb mit Graf der Auffassung, daß „bei wichtigen Arbeiten Anlaß gegeben ist, den Zement durch besondere Versuche auszuwählen“., halten diese Versuche für die Baupraxis aber nur dann für wertvoll, wenn sie unter größtmöglicher Anpassung an die für den Bau gegebene

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