exploiting multimodal information like acceleration and heart rate is a promising method to achieve human action recognition. a semi-supervised action recognition approach aucc (action understanding with combinational classifier) using the diversity of base classifiers to create a high-quality ensemble for multimodal human action recognition is proposed in this paper. furthermore, both labeled ...

A major requirement for credit scoring models is to provide a maximally accurate risk prediction. Additionally, regulators demand these be transparent and auditable. Thus, in scoring, very simple predictive such as logistic regression or decision trees are still widely used the superior power of modern machine learning algorithms cannot fully leveraged. Significant potential therefore missed, l...

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evaporation is a fundamental parameter in the hydrological cycle. this study examines the performance of m5model tree and artificial neural network (ann) models in estimating potential evapotranspiration calculated bypenman- monteith and hargreaves- samani equations. daily weather data from two meteorological stations in asemi-arid climate of iran, namely kerman and zahedan, were collected duri...

The field of optimization and machine learning are increasingly interplayed and optimization in different problems leads to the use of machine learning approaches‎. ‎Machine learning algorithms work in reasonable computational time for specific classes of problems and have important role in extracting knowledge from large amount of data‎. ‎In this paper‎, ‎a methodology has been employed to opt...

Common industry practice means that geological or stratigraphic boundaries are estimated from exploration drill holes. While holes provide opportunities for accurate data at a high resolution down the hole, their acquisition is cost-intensive, which can result in number of drilled being reduced. In contrast, sampling with ground-penetrating radar (GPR) cost-effective, non-destructive, and compa...

in this work, several machine learning techniques are presented for nanofiltration modeling. according to the results, specific errors are defined. the rejection due to nanofiltration increases with pressure but decreases with increasing the concentration of chloride ion. methods of machine learning represent the rejection of nanofiltration as a function of concentration, ph, pressure and also ...