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Monitoring crop areas is a key issue in remote sensing studies. A Crop Proportion Phenology Index (CPPI) model has previously been developed for estimation of winter wheat areas. Here we test the CPPI model in different areas using remote sensing data for varied kernel functions, including linear regression (LR), Artificial Neural Network (ANN), and Support Vector Regression (SVR). The differences...
The general focus of this study is to design a multilevel deep learning model that provides big data analytics and emergency management knowledge. A big data covariance analysis approach has been used to find multilevel representations of data based on prior knowledge from large scale power systems. For purpose of meeting requirements of incremental knowledge discovery, an adaptive regression algorithm...
This paper presents a deep data fusion model for risk perception and coordinated control in a regional power system control center. A knowledge learning data fusion approach has been used to find an efficient state representation based on prior knowledge from cross-domain energy management systems. In particular, a kernel principal components analysis technique is presented for nonlinear dimensionality...
Tongue line refers to the surface of the tongue covered with fissures or lines in deep or shallow shape and is one type of important features in clinical practice of Traditional Chinese Tongue Diagnosis (TCTD). However, it is hard to extract tongue lines completely due to the large variation of the widths of tongue lines and the strong noise caused by the rough surface of tongue and uneven illumination...
Using support vector machine (SVM) function approximation, in this paper, we present the quantitative structure-activity relationship (QSAR) among the known aldose reductase inhibitors (ARIs). The two physical descriptors of a molecule, namely the electronegativity and the molar volume are evaluated by SVM. SVM is found to work better than multi-layer perceptron (MLP).
Performance, reliability and scalability in data access are key issues in the context of Grid computing and High Energy Physics (HEP) data analysis. We present the technical details and the results of a large scale validation and performance measurement achieved at the INFN Tier1, the central computing facility of the Italian National Institute for Nuclear Research (INFN). The aim of this work is...
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