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    Suspended sediment profiles derived from spectral attenuation coefficients measurements using neural network method

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    INCHOE_Proc_2004_2_770.pdf (232.7Kb)
    Date
    2004
    Author
    Varkey, G.
    Suresh, T.
    Matondkar, S.G.P.
    Desa, E.
    Kamath, S.S.
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    Abstract
    Suspended sediment in water plays a major role in the operations of ports and harbor. Here we report a model to be used with an optical instrument that is primarily used for the measurements of inherent optical properties. The AC-9 (WetLabs, USA) is an instrument used for in-situ measurements of the inherent optical properties of the water, absorption and beam attenuation at different wavelengths. The aim is to establish a relationship between the measured profiles of optical properties and the measured total suspended matter values from water samples obtained at discrete depths at the same location. An artificial neural network (ANN) model has been used to derive suspended matter from the spectral values of beam attenuation coefficients measured using the AC-9 instrument. The ANN model has been trained using beam attenuation values obtained from the cruise in the Arabian Sea, SK-149 and the net was tested using the data from the cruise SK-152. The feed forward multi-layer perceptron neural network model was trained using the Levenberg-Marquardt algorithm and has provided us with encouraging results, which are in very close agreements with the measured values. This ANN model with eight input nodes, one hidden layer with five nodes and one output node can now be used to obtain profiles of suspended matter with the measurements of the AC-9 instrument, which will provide variations of concentrations at very fine depth intervals.
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    http://drs.nio.org/drs/handle/2264/1138
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