Wullapa Wongsinlatam An IMCOH Algorithm Neural Network Optimization with Cuckoo Search Algorithm for Time Series Samples
53 - 58
2019
13
3
International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering http://waset.org/publications/10010106
http://waset.org/publications/147
World Academy of Science, Engineering and Technology
Back propagation algorithm (BP) is a widely used
technique in artificial neural network and has been used as a tool
for solving the time series problems, such as decreasing training
time, maximizing the ability to fall into local minima, and optimizing
sensitivity of the initial weights and bias. This paper proposes an
improvement of a BP technique which is called IMCOH algorithm
(IMCOH). By combining IMCOH algorithm with cuckoo search
algorithm (CS), the result is cuckoo search improved control output
hidden layer algorithm (CSIMCOH). This new algorithm has a
better ability in optimizing sensitivity of the initial weights and bias
than the original BP algorithm. In this research, the algorithm of
CSIMCOH is compared with the original BP, the IMCOH, and the
original BP with CS (CSBP). Furthermore, the selected benchmarks,
four time series samples, are shown in this research for illustration.
The research shows that the CSIMCOH algorithm give the best
forecasting results compared with the selected samples.
International Science Index 147, 2019