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- W2022234741 endingPage "225" @default.
- W2022234741 startingPage "215" @default.
- W2022234741 abstract "Recent developments in curve fitting, multivariate calibration, and pattern recognition in chemometrics, and their application to x-ray spectrometry, are reviewed. Relatively innovated algorithms, namely genetic algorithms, neural networks and support vector machines, are discussed. Together with the three algorithms, the performances of different algorithms are compared briefly, which mainly includes principal component analysis, partial least-squares regression, factor analysis, cluster analysis, nearest neighbor methods, linear discriminant analysis, linear learning machine, and soft independent modeling of class analogy. In general, the chemometrics methods are superior to the conventional methods, such as Fourier transform and Marquardt–Levenberg algorithms, to a certain extent. Copyright © 2006 John Wiley & Sons, Ltd." @default.
- W2022234741 created "2016-06-24" @default.
- W2022234741 creator A5026251379 @default.
- W2022234741 date "2006-01-01" @default.
- W2022234741 modified "2023-10-14" @default.
- W2022234741 title "Chemometrics and its applications to x-ray spectrometry" @default.
- W2022234741 cites W1489571934 @default.
- W2022234741 cites W1579093114 @default.
- W2022234741 cites W172786307 @default.
- W2022234741 cites W1965431799 @default.
- W2022234741 cites W1966413464 @default.
- W2022234741 cites W1967708203 @default.
- W2022234741 cites W1972043864 @default.
- W2022234741 cites W1972187954 @default.
- W2022234741 cites W1975267178 @default.
- W2022234741 cites W1976998719 @default.
- W2022234741 cites W1978508948 @default.
- W2022234741 cites W1978996791 @default.
- W2022234741 cites W1979162621 @default.
- W2022234741 cites W1979704339 @default.
- W2022234741 cites W1981976602 @default.
- W2022234741 cites W1982293999 @default.
- W2022234741 cites W1982385140 @default.
- W2022234741 cites W1983082592 @default.
- W2022234741 cites W1985085054 @default.
- W2022234741 cites W1985147596 @default.
- W2022234741 cites W1987843319 @default.
- W2022234741 cites W1988358336 @default.
- W2022234741 cites W1988461998 @default.
- W2022234741 cites W1988883468 @default.
- W2022234741 cites W1990917197 @default.
- W2022234741 cites W1991428022 @default.
- W2022234741 cites W1991733646 @default.
- W2022234741 cites W1992346433 @default.
- W2022234741 cites W1992382570 @default.
- W2022234741 cites W1992649245 @default.
- W2022234741 cites W1993896525 @default.
- W2022234741 cites W1999212763 @default.
- W2022234741 cites W2003524940 @default.
- W2022234741 cites W2004523502 @default.
- W2022234741 cites W2008273110 @default.
- W2022234741 cites W2009866811 @default.
- W2022234741 cites W2012008625 @default.
- W2022234741 cites W2013213973 @default.
- W2022234741 cites W2016229600 @default.
- W2022234741 cites W2018200093 @default.
- W2022234741 cites W2018473466 @default.
- W2022234741 cites W2021039490 @default.
- W2022234741 cites W2021651928 @default.
- W2022234741 cites W2023244747 @default.
- W2022234741 cites W2023552815 @default.
- W2022234741 cites W2025053504 @default.
- W2022234741 cites W2026414205 @default.
- W2022234741 cites W2027727008 @default.
- W2022234741 cites W2027961622 @default.
- W2022234741 cites W2028070629 @default.
- W2022234741 cites W2028430123 @default.
- W2022234741 cites W2029372760 @default.
- W2022234741 cites W2031741416 @default.
- W2022234741 cites W2032437475 @default.
- W2022234741 cites W2034825096 @default.
- W2022234741 cites W2034849348 @default.
- W2022234741 cites W2036112399 @default.
- W2022234741 cites W2037173921 @default.
- W2022234741 cites W2037761739 @default.
- W2022234741 cites W2038193856 @default.
- W2022234741 cites W2040199820 @default.
- W2022234741 cites W2046310843 @default.
- W2022234741 cites W2046518304 @default.
- W2022234741 cites W2046855103 @default.
- W2022234741 cites W2046898986 @default.
- W2022234741 cites W2050297731 @default.
- W2022234741 cites W2054595653 @default.
- W2022234741 cites W2054945951 @default.
- W2022234741 cites W2056217049 @default.
- W2022234741 cites W2057394498 @default.
- W2022234741 cites W2058782629 @default.
- W2022234741 cites W2059020380 @default.
- W2022234741 cites W2061088453 @default.
- W2022234741 cites W2061322644 @default.
- W2022234741 cites W2061350602 @default.
- W2022234741 cites W2062786850 @default.
- W2022234741 cites W2063095872 @default.
- W2022234741 cites W2063883976 @default.
- W2022234741 cites W2064201024 @default.
- W2022234741 cites W2065581058 @default.
- W2022234741 cites W2069291673 @default.
- W2022234741 cites W2070028025 @default.
- W2022234741 cites W2070439790 @default.
- W2022234741 cites W2071300311 @default.
- W2022234741 cites W2071843477 @default.
- W2022234741 cites W2073706516 @default.
- W2022234741 cites W2074724805 @default.
- W2022234741 cites W2074761581 @default.
- W2022234741 cites W2075432049 @default.
- W2022234741 cites W2078778515 @default.
- W2022234741 cites W2079810797 @default.
- W2022234741 cites W2081574488 @default.