Solution of Inverse Problems in Laser Spectroscopy of Water Media with the Help of Neural Networks

S. A. Dolenko, I. V. Boychuk, I. V. Churina, T. A. Dolenko, V. V. Fadeev, and I. G. Persiantsev, Moscow State University, Russia; B. Carse, University of the West, England

Two methodological approaches to inverse problems solution with the help of neural networks are considered: "experiment-based" and "model-based". Their merits, drawbacks, and characteristics of their use are discussed. Successful application of neural networks for solution of three inverse problems in laser spectroscopy of water media is reported: (1) simultaneous determination of sea water temperature and salinity from Raman spectra, (2) determination of contributions for components of an organic compounds mixture in water from their fluorescence spectra, and (3) determination of molecular parameters of organic compounds from fluorescence saturation curves. Keywords: inverse problems, applications, laser spectroscopy, water media


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