Kou-Yuan Huang

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A neural network method is adopted to predict the football game's winning rate of two teams according to their previous stage's official statistical data of 2006 World Cup Football Game. The adopted prediction model is based on multi-layer perceptron (MLP) with back propagation learning rule. The input data are transformed to the relative ratios between two(More)
A well-developed pose estimation scenario suitable for low altitude unmanned aerial vehicle (UAV) is proposed. By employing dual CCD cameras onboard, the instant pose of UAV can be determined without any use of expensive sensor like gyro. The unscented Kalman filter (UKF) is hereafter introduced to resolve the highly nonlinear system dynamics as well as the(More)
Hough transform neural network is adopted to detect line pattern of direct wave and hyperbola pattern of reflection wave in a seismogram. The distance calculation from point to hyperbola is calculated from the time difference. This calculation makes the parameter learning feasible. The neural network can calculate the total error for distance from point to(More)
Simulated annealing algorithm is adopted to detect the parameters of lines, circles, ellipses, and hyperbolic patterns. We define the distance from a point to a pattern such that the detection becomes feasible, especially in hyperbola. The proposed simulated annealing parameter detection system has the capability to find a set of parameter vectors with(More)
We combine neural network and syntactic pattern recognition, and propose a tree automaton system for the recognition of structural seismic patterns in a seismogram. Multilayer perceptron of the neural network is used for the identification of subpatterns, then a tree representation of the structural seismic pattern is constructed. We use three kinds of(More)
Well log data inversion is important for the inversion of true formation. There exists a nonlinear mapping between the measured apparent conductivity (C<sub>a</sub>) and the true formation conductivity (C<sub>t</sub>). We adopt the multilayer perceptron (MLP) to approximate the nonlinear input-output mapping and propose the use of particle swarm(More)