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Surrogate model methods are usually used as a time-saving approach to reduce the computational burden of expensive computer simulations, while the appropriate surrogate model for an unknown problem is often difficult to choose. In this paper, a SCG (Ensemble of surrogate models using Sign based Cross validation error with Global correction) ensemble modeling method based on pointwise local measures...
Surface roughness has a great influence on the product properties. Predicting the surface roughness is an important work for modern manufacturing industry. In this paper, a novel prediction method called Free Pattern Search (FPS) is proposed to explicitly construct the surface roughness prediction model. FPS takes the advantage of the expression tree in gene expression programming (GEP) to encode...
Because of accurate forecasting of tourist arrivals is very important for tourism industry, various tourist arrivals forecasting models have been developed. The aim of this paper is to introduce the basic theoretical principles of electromagnetism-like mechanism (EM) algorithm and design a new neural network model for tourism forecasting which uses the EM algorithm as the learning rule (EMNN). The...
In order to predict the performance of a manufacturing process or system, proper mathematical models are needed. This research investigates the use of two competitive unsupervised data mining methods - regression and neural networks - in developing an empirical model for two electronics fabrication processes/systems. A case study from experimental data of electronics fabrication is used to demonstrate...
The characteristics of the chaos theory are analyzed in this paper. The urban daily water demand short-term forecasts model, which is for the scientific forecast of the urban daily water demand, is built based on the chaos theory. The time-series of urban daily water demand is analyzed on the basis of phase space reconstruction and the historical data of water demand is used. The saturated embedding...
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