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Geochemical characterization of oceanic basalts using Artificial Neural Network

DOI: 10.1186/1467-4866-10-13

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Abstract:

We have applied Artificial Neural Network (ANN) technique as a supervised Learning Vector Quantisation (LVQ) to identify the inherent geochemical signatures present in the Central Indian Ocean Basin (CIOB) basalts. A range of N-MORB, E-MORB and OIB dataset was used for training and testing of the network. Although the identification of the characters as N-MORB, E-MORB and OIB is completely dependent upon the training data set for the LVQ, but to a significant extent this method is found to be successful in identifying the characters within the CIOB basalts. The study helped to geochemically delineate the CIOB basalts as N-MORB with perceptible imprints of E-MORB and OIB characteristics in the form of moderately enriched rare earth and incompatible elements. Apart from the fact that the magmatic processes are difficult to be deciphered, the architecture performs satisfactorily.Several discrimination diagrams have been proposed to classify the ocean floor basalts (OFB) into ocean island basalts (OIB), mid-oceanic ridge basalts (MORB), and island arc basalts (IAB) that are recovered from different tectonic settings. These diagrams are constructed by considering a variety of oxides and/or their ratios, for instance the triangular diagrams of Ti/100 - Zr - Y.3 by Pearce & Cann [1], Hf/3 - Th - Ta by Wood et al. [2], TiO2 - MnO - P2O5 × 100 by Mullen [3] and 2Nb -Zr/4 -Y by Meschede [4]. The model based geochemical studies classify the MORB into three types such as normal - , enriched or plume - and transitional MORB (i.e., N- MORB, E or P-MORB and T-MORB, respectively) or as OIB [5-7]. The discrimination diagrams provide a broad picture of the type of basalts but it is difficult to determine the basic characters that are involved in the geochemical classification of OFB based solely on the above mentioned elements and oxides. Recently, Sheth [8] considered several log-ratio and discriminant-analysis based diagrams to evaluate and classify the basalts into OIB, island arc

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