EN 
IN
Journal article
Optimized Back propagation Learning in Neural Networks with Bacterial Foraging Optimization to Predict Forex Gold Index (XAUUSD)
I Made Bayu Permana Putra RUKMI SARI HARTATI I Ketut Gede Darma Putra NI KADEK AYU WIRDIANI
Volume : 8 Nomor : 38 Published : 2014, December
Applied Mathematical Sciences
Abstrak
This paper aims to build systems that can predict the gold price index with the back propagation method so that the back propagation method can run faster and get more accurate results. Back propagation method optimized in weight and bias with bacterial foraging optimization. Proven by adding bacterial foraging optimization method, it involve the back propagation method can run 50% faster and accuracy increased 2% average. System performance testing was conducted 1000 times using many different data. Sample data and test data normalization is immersely affect the system performance.