Comparison of Forcasting Ability between Backpropagation Network and ARIMA in the Prediction of Bitcoin Price

Author(s):  
Chung-Chieh Chen ◽  
Jung-Hsin Chang ◽  
Fang -Cih Lin ◽  
Jui-Cheng Hung ◽  
Cheng-Shian Lin ◽  
...  
CAUCHY ◽  
2012 ◽  
Vol 2 (3) ◽  
pp. 154
Author(s):  
Shofwan Ali Fauzi

<div class="standard"><a id="magicparlabel-1110">Artificial Neural Network (ANN) is beginning little by little to replace the task of an expert, even with the ANN can be a tool to replace a doctor. One of kind of ANN is Backpropagation networks, this network can be used to training programs in order to be able to recognize whether it is pig or cow wave spectra. To determine the output in Backpropagation training required suitable activation functions. Therefore, in this research will be compared to some of the activation function that can be used in training. Activation functions will be tested with the ratio test to determine the interval convergence. After tested with the ratio test it was found that the activation function was the best activation function to use the Backpropagation network training, because it has a weight range that can meet the methods used in the determination of weights. When tested with the data, the activation function is able to recognize correctly all trial datas. Expected in future research to examine the weight that makes the interval training to achieve fast convergence and the error bit.</a></div>


1991 ◽  
Vol 3 (1) ◽  
pp. 88-97 ◽  
Author(s):  
Dean A. Pomerleau

The ALVINN (Autonomous Land Vehicle In a Neural Network) project addresses the problem of training artificial neural networks in real time to perform difficult perception tasks. ALVINN is a backpropagation network designed to drive the CMU Navlab, a modified Chevy van. This paper describes the training techniques that allow ALVINN to learn in under 5 minutes to autonomously control the Navlab by watching the reactions of a human driver. Using these techniques, ALVINN has been trained to drive in a variety of circumstances including single-lane paved and unpaved roads, and multilane lined and unlined roads, at speeds of up to 20 miles per hour.


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