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Neural network deals with matter of developing programs that enhance their performance at some task through experience. Many have proven that the Neural Network has great practical value in many domains of application. One useful use of Neural Network is for complex problem domains where a little knowledge exists for humans to develop effective algorithms and also in domains where programs must adjust to changing conditions. Software Engineering can be a perfect field where many software development task and maintenance task could be constructed as problems to be learned and approaches in terms of optimizing the software performance. In this research, two different versions of neural network structure called Multilayer Perceptron (MLP) is used to compare the performance of the software which is a car navigation simulator in terms of finding the solution for its problem. The performance of the software is strictly compared using parameters from the algorithm used which is Genetic Algorithm (GA) and also parameters from the car navigation simulator. From this research, the MLP structure does shows different performance value of the software when finding the solution for its problem. This research also shows that the software optimization technique using neural network may improve the software engineering field in terms of performance optimization of the developed software.
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