An integrated data preparation scheme for neural network data analysis

2006 ◽  
Vol 18 (2) ◽  
pp. 217-230 ◽  
Author(s):  
Lean Yu ◽  
Shouyang Wang ◽  
K.K. Lai
Keyword(s):  
Neural Network ◽  
Data Analysis ◽  
Network Data ◽  
Data Preparation

Influence of the GMDH Neural Network Data Preparation Method on UTC(PL) Correction Prediction Results

2012 ◽  
Vol 19 (1) ◽  
Author(s):  
Wiesław Miczulski ◽  
Łukasz Sobolewski
Keyword(s):  
Neural Network ◽  
Preparation Method ◽  
Network Data ◽  
Data Preparation

scholarly journals Development of a condition monitoring system for compressor equipment with neural network data analysis

2019 ◽  
Vol 1399 ◽  
pp. 022058
Author(s):  
D K Zyryanov ◽  
V V Bukhtoyarov ◽  
N A Bukhtoyarova ◽  
V V Kukartsev ◽  
V S Tynchenko ◽  
...  
Keyword(s):  
Neural Network ◽  
Data Analysis ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Network Data ◽  
Condition Monitoring System ◽  
Compressor Equipment

scholarly journals Penerapan Algoritma Backpropagation dalam Memprediksi Persentase Penduduk Buta Huruf di Indonesia

2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Imelda Asih Rohani Simbolon ◽  
Fikri Yatussa’ada ◽  
Anjar Wanto
Keyword(s):  
Neural Network ◽  
Data Analysis ◽  
Network Architecture ◽  
Mean Squared Error ◽  
Central Bureau ◽  
Network Data ◽  
Backpropagation Neural Network ◽  
Matlab Software ◽  
Squared Error

Illiteracy is one of the most serious issues in Indonesia. The government's ignorance of illiterate people makes the illiteracy rate quite high. It should be one of the government's targets for reducing illiteracy in order to reduce the number of illiterate people. Illiteracy rate in Indonesia itself has reached 34.55% in Papua province. One way to suppress illiteracy rate in Indonesia is by predicting illiterate figures for subsequent years. The data to be predicted is the data of illiterate figures of each province in Indonesia which is sourced from the Indonesian Central Bureau of Statistics from 2011 to 2017. The method used in the prediction is Backpropagation Neural Network. Data analysis was done with the help of matlab software R2011b (7.13). This study uses 5 architectures, 4-5-1, 4-6-1, 4-9-1, 4-14-1 and 4-18-1. From these 5 models the best network architecture is 4-14-1 with 91% accuracy and Mean Squared Error 0,00274166.

scholarly journals Neural network data analysis for laser-induced thermal acoustics

2000 ◽  
Vol 11 (6) ◽  
pp. 784-794 ◽  
Author(s):  
Stefan Schlamp ◽  
Hans G Hornung ◽  
Eric B Cummings
Keyword(s):  
Neural Network ◽  
Data Analysis ◽  
Network Data

Neural network data analysis for intracavity laser spectroscopy

2003 ◽  
Author(s):  
Petr V. Nazarov ◽  
Vladimir V. Apanasovich ◽  
Katsiaryana U. Lutkovskaya ◽  
Vladimir M. Lutkovski ◽  
Pulat Y. Misakov
Keyword(s):  
Neural Network ◽  
Data Analysis ◽  
Laser Spectroscopy ◽  
Network Data ◽  
Intracavity Laser Spectroscopy ◽  
Intracavity Laser

Neural Network Data Analysis Using Simulnet™

1998 ◽  
Author(s):  
Edward J. Rzempoluck
Keyword(s):  
Neural Network ◽  
Data Analysis ◽  
Network Data

scholarly journals Comparison between two PCR-based bacterial identification methods through artificial neural network data analysis

2008 ◽  
Vol 22 (1) ◽  
pp. 14-20 ◽  
Author(s):  
Jie Wen ◽  
Xiaohui Zhang ◽  
Peng Gao ◽  
Qiuhong Jiang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Data Analysis ◽  
Network Data ◽  
Bacterial Identification ◽  
Identification Methods ◽  
Artificial Neural
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