Feed-Forward Neural Network Architectures Based on Extreme Learning Machine for Parkinson’s Disease Diagnosis

2014 ◽  
pp. 746-749
Author(s):  
P. J. García-Laencina ◽  
G. Rodríguez-Bermúdez ◽  
J. Roca-Dorda
Keyword(s):  
Neural Network ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Extreme Learning Machine ◽  
Disease Diagnosis ◽  
Network Architectures ◽  
Feed Forward Neural Network ◽  
Feed Forward ◽  
Neural Network Architectures ◽  
Learning Machine

scholarly journals PREDIKSI HARGA EMAS MENGGUNAKAN FEED FORWARD NEURAL NETWORK DENGAN METODE EXTREME LEARNING MACHINE

2019 ◽  
Vol 8 (2) ◽  
pp. 171-183
Author(s):  
Nisa Afida Izati ◽  
Budi Warsito ◽  
Tatik Widiharih
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Extreme Learning Machine ◽  
Gold Price ◽  
Good Prediction ◽  
Feed Forward Neural Network ◽  
Feed Forward ◽  
Artificial Neural ◽  
Learning Machine

The prediction of gold price aims to find out the gold price in the future on the basis of historical data on gold prices in the past, so it can be used as a consideration by gold investors to investing in gold. Prediction methods that do not require assumptions, one of which is Artificial Neural Networks. In this study, using Artificial Neural Networks, Feed Forward Neural Network with Extreme Learning Machine (ELM). ELM is a non-iterative algorithm so ELM has advantages in process speed. The input weight and bias for this method are determined randomly. After that, to find the final weight using the Moore-Penrose Generalized Inverse calculation on the hidden layer output matrix. The best model selection criteria uses the Mean Absolute Percentage Error (MAPE). This study shows that the results of the training and testing process from the model 1 input neuron and 7 hidden neurons are very good, because it produces MAPE training = 0.6752% and MAPE testing = 0.8065%. Also gives a very good prediction result because it has MAPE = 0.5499% Keywords: gold price, Extreme Learning Machine, MAPE

A Hybrid Extreme Learning Machine Approach for Early Diagnosis of Parkinson’s Disease

2014 ◽  
pp. 342-349
Author(s):  
Yao-Wei Fu ◽  
Hui-Ling Chen ◽  
Su-Jie Chen ◽  
Li-Juan Li ◽  
Shan-Shan Huang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Diagnosis ◽  
Extreme Learning Machine ◽  
Learning Machine
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