A Neural Network Approach to Solve the Truck Backer-Upper and Iris Flower Problems
نویسنده
چکیده
A neural network approach is proposed to solve the Truck Backer-Upper and Iris Flower Classification problems. Several implementation alternatives with respect to network architecture, number of hidden nodes, step length adjustment method and prevention of overfitting were tested and compared. A performance comparison between our neural network approach and a fuzzy clustering approach was also conducted.
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