METODE HYBRID PARTICLE SWARM OPTIMIZATION - NEURAL NETWORK BACKPROPAGATION UNTUK PREDIKSI HASIL PERTANDINGAN SEPAK BOLA
Description
Hybrid is using two methods to a problem with the aim to improve their approach towards the specified target data. Hybrid PSO-ANN one optimal algorithm to solve such predictions in football matches. The process begins with determining the outcome of test dataset with the neural network architecture, specify the input parameters, the value of weight up to the value of hidden layer and output layer. Then the optimization of the results of the first test on a training dataset optimized by Particle Swarm Optimization. Testing will continue over using back propagation neural network until the maximum iteration and the results of the initial approach the target value. Furthermore, from the output obtained to search the value of the average error.
Files
7. METODE HYBRID PARTICLE SWARM OPTIMIZATION NEURAL NETWORK BACKPROPAGATION UNTUK PREDIKSI HASIL PERTANDINGAN SEPAK BOLA.pdf
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