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- W1570606770 abstract "This paper presents a performance comparison of a variety of data preprocessing algorithms in a geoscience application. The selected algorithms are principal component analysis (PCA) and three different independent component analyses (FLEXICA, JADE and SOBI). These algorithms are applied to a set of electrical and radioactive signals obtained from a drilled well in Indonesia. Standard backpropagation neural networks are used to perform pattern (flow unit) classification from raw or preprocessed data. The results show that use of the preprocessed data gives more confident results than those obtained from the raw data. Among the preprocessing algorithms, FLEXICA seems to slightly outperform the others. The study also present a technological framework for combining results from different techniques and it shows that further improvement was achieved." @default.
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- W1570606770 date "2001-01-01" @default.
- W1570606770 modified "2023-09-27" @default.
- W1570606770 title "A COMPARISION OF PCA/ICA FOR DATA PREPROCESSING IN A GEOSCIENCE APPLICATION" @default.
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