Soft Computing

1
Soft Computing

• Lecture 21
• Review of using of NN for solving of real tasks

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Autopilot airplane

• LoFLYTE (Low-Observable Flight Test Experiment)
  is developed for NASA and USA Air Force by
  Accurate Automation Corp., Chattanooga, TN.
• Speed is 4-5 M
• NN is learning by pilot (storing associations
  between situation and action of pilot) and after
  that may control without pilot

3
Project TNA

• System for searching of plastic explosive in
  baggage in airports is developed by SAIC (Science
  Application International Corporation)
• NN analyzes of spectrum of baggage after
  irradiation of it by slow neutrons
• Recognition of explosive with probability 97,
  speed is 10 units per minute

4
Using of NN on financial markets

• Citibank uses NN from 1990. In 1992 yield was 25
  which is large more then most of brokers
• Chemical Bank uses NN (from company Neural Data)
  for previous processing of transactions in
  currency exchanges in 23 countries for detection
  of shady bargains
• Fidelity of Boston uses NN for control of
  portfolio with volume 3 billion USA, Deere Co
  100 million USA, LBS Capital 400 million USA
• Proceedings of one seminar AI in Wall Street
  includes 6 large volumes.

5
Recognition of stolen credit cards

• Developer is HNC Software Corp., now Fair Isaac
  Corporation http//www.fairisaac.com
• Software Falcon based on NN
• This company controls more then 220 million
  accounts
• NN is learning to recognize unusual behavior of
  clients with credit card

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Active reclaim in Internet

• Developer is Aptex Software Inc.
• Software SelectCast based on NN
• NN is learning by interesting of users and offers
  to client such reclaim which may be interesting
  for him

7
Control of mobile robots

• LSTM for robots
• Planning of path and navigation
• Recognition of objects

8
Camera-robot coordination is function
approximation

• The system we focus on in this section is a work
  floor observed by a fixed cameras and a robot
  arm. The visual system must identify the target
  as well as determine the visual position of the
  end-effector.

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Camera-robot coordination is function
approximation (2)
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Camera-robot coordination is function
approximation (3).Two approach to use neural
networks

• Usage of feed-forward networks
• Indirect learning
• General learning
• Specialized learning
• Usage of topology conserving maps

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Camera-robot coordination is function
approximation (4). feed-forward networks
Indirect learning system for robotics. In each
cycle the network is used in two different
places first in the forward step then for
feeding back the error
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Camera-robot coordination is function
approximation (5). feed-forward networks (2)
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Sensor based control
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The structure of the network for the autonomous
land vehicle
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Drama
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Diagnosis of cancer

• Yulei Jiang, assistant professor of radiology at
  the University of Chicago
• System that uses a perceptron neural network to
  analyze eight input nodes, converting the output
  node into a robability measure, which Jiang calls
  likelihood of malignancy.
• The system is trained on a set of cases, using
  the leave-one-out method, which is a
  cross-validation technique for estimating
  generalization error based on resampling. A net
  is trained a number of times, each time leaving
  out one of the subsets. The omitted subset
  computes whatever error criterion is of interest.
  The system initially learns from digitized screen
  mammograms.
• The eight input nodes represent features of
  calcifications, areas in breast tissue where tiny
  calcium deposits build up and might indicate the
  presence of cancer.

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