Combining Exploratory Projection Pursuit and Projection Pursuit Regression with Application to Neural Networks

1993 ◽  
Vol 5 (3) ◽  
pp. 443-455 ◽  
Author(s):  
Nathan Intrator

We present a novel classification and regression method that combines exploratory projection pursuit (unsupervised training) with projection pursuit regression (supervised training), to yield a new family of cost/complexity penalty terms. Some improved generalization properties are demonstrated on real-world problems.

2005 ◽  
Vol 48 (1) ◽  
pp. 47-55
Author(s):  
Li Jianlong ◽  
QI Jiaguo ◽  
Zhao Dehua ◽  
Jiang Ping ◽  
Xu Sheng

2012 ◽  
Vol 485 ◽  
pp. 310-313
Author(s):  
Yu Cai Dong ◽  
Ge Hua Fan ◽  
Liang Hai Yi ◽  
Ling Zhang ◽  
Min Lin

The hydraulic motor of amphibious assault vehicle is one of the important output executive components of the hydraulic system whose performance has an important influence for the whole system. According to the high failure rate, fault detection and location problems of hydraulic system, this paper explore the relationship between the leakage of amphibious assault vehicle and each influential factor, establish the leakage predication model by projection pursuit regression method and get a better predicated effect. It has great significance for the fault diagnosis of hydraulic motor of amphibious assault vehicle.


2014 ◽  
Vol 881-883 ◽  
pp. 1747-1753
Author(s):  
Wei Dong Nie ◽  
Xiao Ming Wang ◽  
Zhao Na Li ◽  
Xin Geng Li

A Projection Pursuit Regression method by using Hermite Polynomial is put forward to make modeling and forcasting of corrosion data, because of small sample of acumulation data of metal material corrosion in atmosphere, Multi-dimensional Properties and Non-orthogonality of influence factors. Analyses and prediction of atmospheric corrosion data of a metal are made by using this method. Compared with PCA+SVM method, this method improves significantly the accuration of prediction and correctness of corrosion vehavior trend. The result proves that the Hermite Polynomial Projection Pursuit Regression method has great huge advantage in data analysis of steel corrosion in atmosphere.


2014 ◽  
Vol 551 ◽  
pp. 365-369
Author(s):  
Jia Xing Du ◽  
Ping Chen ◽  
Ling Zhang ◽  
Juan Min Xiang ◽  
Hui Zhen Li

Through the relations among the torpedo velocity at tube outlet, cylinder volume, cylinder pressure and emission valve size, we adopt the projection pursuit regression method and establish the model to predict the torpedo velocity at tube outlet. Through the comparison of experiment data and model prediction, fitting accuracy of this relation model is stronger and the projection pursuit regression is an efficient method which can research the initial ballistic trajectory of ship-launched torpedoes.


2016 ◽  
Vol 25 (43) ◽  
pp. 73-82
Author(s):  
Álvaro David Orjuela-Cañón ◽  
Hugo Fernando Posada-Quintero

This study analyzes acoustic lung signals with different abnormalities, using Mel Frequency Cepstral Coefficients (MFCC), Self-Organizing Maps (SOM), and K-means clustering algorithm. SOM models are known as artificial neural networks than can be trained in an unsupervised or supervised manner. Both approaches were used in this work to compare the utility of this tool in lung signals studies. Results showed that with a supervised training, the classification reached rates of 85 % in accuracy. Unsupervised training was used for clustering tasks, and three clusters was the most adequate number for both supervised and unsupervised training. In general, SOM models can be used in lung signals as a strategy to diagnose systems, finding number of clusters in data, and making classifications for computer-aided decision making systems.


2014 ◽  
Vol 533 ◽  
pp. 44-47
Author(s):  
Ling Zhang ◽  
Yu Cai Dong ◽  
Bao Hong Lu ◽  
Ge Hua Fan

Through the relation among the pressure of the torpedo launch tube, cylinder volume, cylinder pressure and emission valve size, we adopt the projection pursuit regression method and establish the model to predict the pressure of the torpedo launch tube. Through the comparison of experiment data and model prediction, fitting accuracy of this relation model is higher than that of the partial least-squares regression method and linear regression model and the projection pursuit regression is an efficient method which can research the initial ballistic trajectory of ship launched torpedoes.


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