Transcript Artificial Neural Networks - University of Northampton

Artificial Intelligence Techniques
Applications of Neural Networks
Example Applications




Analysis of data
Classifying in EEG
Pattern recognition in ECG
EMG disease detection.
Gueli N et al (2005) The influence of lifestyle on cardiovascular
risk factors analysis using a neural network Archives of Gerontology
and Geriatrics 40 157–172



To produce a model of risk facts in
heart disease.
MLP used
The accuracy was relatively good for
chlorestremia and triglyceremdia:



Training phase around 99%
Testing phase around 93%
Not so good for HDL
Subasi A (in press) Automatic recognition of alertness level from
EEG by using neural network and wavelet coefficients Expert
Systems with Applications xx (2004) 1–11

Electroencephalography (EEG)


Recordings of electrical activity from the
brain.
Classifying operation



Awake
Drowsy
Sleep

MLP




15-23-3
Hidden layer – log-tanh function
Output layer – log-sigmoid function
Input is normalise to be within the
range 0 to 1.

Accuracy




95%+/-3% alert
93%+/-4% drowsy
92+/-5% sleep
Feature were extracted and form the
input to the network, from wavelets.
Karsten Sternickel (2002) Automatic pattern recognition in ECG
time series Computer Methods and Programs in Biomedicine 68
109–115




ECG – electrocardiographs – electrical
signals from the heart.
Wavelets again.
Classification of patterns
Patterns were spotted
Abel et al (1996) Neural network analysis of the EMG
interference pattern Med. Eng. Phys. Vol. 18, No. 1. pp.
12-l 7



EMG – Electromyography – muscle
activity.
Interference patterns are signals
produce from various parts of a musclehard to see features.
Applied neural network to EMG
interference patterns.

Classifying





Nerve disease
Muscle disease
Controls
Applied various different ways of
presenting the pattern to the ANN.
Good for less serve cases, serve cases
can often be see by the clinician.
Example Applications




Wave prediction
Controlling a vehicle
Image processing
Condition monitoring
Wave prediction




Raoa S, Mandal S(2005) Hindcasting of
storm waves using neural networks
Ocean Engineering 32 (2005) 667–684
MLP used to predict storm waves.
2:2:2 network
Good correlation between ANN model and
another model
van de Ven P, Flanagan C, Toal D (in press)
Neural network control of underwater vehicles
Engineering Applications of Artificial Intelligence



Semiautomous vehicle
Control using ANN
ANN replaces a mathematical model of
the system.
Kuo RJ, et al (in press) Part family
formation through fuzzy ART2 neural
network Decision Support Systems


Image recognition of part
Deals with the shifting of the part
Silva et al (2000) THE ADAPTABILITY OF A TOOL WEAR
MONITORING SYSTEM UNDER CHANGING CUTTING
CONDITIONS Mechanical Systems and Signal Processing
(2000) 14(2), 287-298




Modelling tool wear
Combines ANN with other AI (Expert
systems)
Self organising Maps (SOM) and ART2
investigated
SOM better for extracting the required
information.