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This paper investigates the use of machine learning to predict a sensitive gait parameter based on acceleration information from previous gait cycles. We investigate a k-step look-ahead prediction which attempts to predict gait variable values based on acceleration information in the current gait cycle. The variable is the minimum toe clearance which has been demonstrated to be a sensitive falls risk...
In the analysis of predicting financial distress based on support vector regression (SVR), irrelevant or correlated features in the samples could spoil the performance of the SVR classifier, leading to decrease of prediction accuracy. In order to solve the problems mentioned above, this paper used rough sets as a preprocessor of SVR to select a subset of input variables and employed the immune clone...
In this paper, we proposed a novel house prediction model that integrated hybrid genetic-based support vector regression (HGA-SVR) model and feng shui theories for developing a high accuracy appraising real estate price system in Taiwan. In Taiwan, feng shui theory applies in choosing good days, divination and house selection. From the past researches, many factors might affect the real estate price...
It is important to choose good parameters in support vector regression (SVR) modeling. Choosing different parameters will influence the accuracy of SVR models. This paper proposes a parameter choosing method of SVR models for time series prediction. In the light of data features of time series, the paper improves the traditional cross-validation method, and combines the improved cross-validation with...
An approach of a mean hourly wind speed conformal prediction in wind farm is proposed. Conformal prediction is a new prediction methodology. It can be used not just to make predictions but also to estimate the confidence under the usual independent and identically distributed assumption. Based on support vector regression, wind speed regions are predicted by inductive confidence machine. Wind speed...
One of the challenging problems in grid environment is the choice of destination nodes where the tasks of the application are to be executed. Therefore, resource prediction is a crucial direction for job scheduling system and grid users. In this paper, Nu-support vector regression (v-SVR) is applied to solve resource prediction problem. The method of parallel multidimensional step search is also introduced...
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