SCAFE: Automated simultaneous clustering and non-linear feature extraction of building energy profiles
نویسندگان
چکیده
منابع مشابه
on the effect of linear & non-linear texts on students comprehension and recalling
چکیده ندارد.
15 صفحه اولFeature Selection and Non-linear Feature Extraction
Feature extraction and feature selection are two important tasks in pattern recognition. Classiication algorithms like k-nearest neighbors, which are based on the assumption that patterns in the same class are close to each other and those in diierent classes are far apart (locality property), rely heavily on the quality of the features extracted from the input data. In this work, an objective ...
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Mapping techniques have been regularly used for visualization of high-dimensional data sets. In this paper, mapping to d 2 is studied, with the purpose of feature extraction. Two di erent non-linear techniques are studied: self-organizing maps and auto-associative feedforward networks. The non-linear techniques are compared to linear Principal Component Analysis (PCA). A comparison with respect...
متن کاملRadial Projections for Non-Linear Feature Extraction
In this work, two new techniques for non-linear feature extraction are presented. In these techniques, new features are obtained as radial projections of the original measurements. Radial projections are a particular kind of second order transformations that show interesting properties: they capture the local structure of the data and reduce dramatically the number of parameters to estimate fro...
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In this article we use a combination of neural networks with other techniques for the analysis of orthophotos. Our goal is to obtain results that can serve as a useful groundwork for interactive exploration of the terrain in detail. In our approach we split an aerial photo into a regular grid of segments and for each segment we detect a set of features. These features depict the segment from th...
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ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2019
ISSN: 1742-6588,1742-6596
DOI: 10.1088/1742-6596/1343/1/012037