Abstract: “Mathematical Optimization refers to finding the minimum or maximum value from a desired set of outcomes. This paper discusses about optimization in two levels. Levenberg- Marquardt is used for back propagation to minimize non-linear least square error using curve fitting. This minimization involves functional optimization to reduce error in neural network (NN) classification. The second level of optimization is on improving the performance of Levenberg-Marquardt algorithm (LMA) by using divide and conquer methods to parallelize computation”

Keywords: Levenberg-Marquardt; Back Propagation; Neural Networks; Optimization, Fitting, Parallelization; Fork/Join; Divide and Conquer; Java