Systems, and Neural Networks

cartcletchAI and Robotics

Oct 19, 2013 (3 years and 10 months ago)

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Artificial Intelligence, Expert
Systems, and Neural Networks

Group 10

Cameron Kinard

Leaundre Zeno

Heath Carley

Megan Wiedmaier

Introduction


Artificial Intelligence


Expert Systems


Neural Networks


Business Use


Real World Application

What is Artificial Intelligence?


A branch of science dealing with behavior,
learning, and adaptation in machines.


Two Categories


Conventional


Computational


The two most common types of AI are
expert systems and neural networks.

Conventional Artificial Intelligence


A method involving the use of structured
formulas and statistical analysis.


Methods include


Expert systems


Case based reasoning


Bayesian networks


Behavior based AI.

Computational Artificial Intelligence


The method of analyzing existing
information and recognizing patterns.
Simply put, it has the ability to learn from
existing information.


Methods include


Neural networks


Evolutionary computation


Fuzzy systems.


What is an Expert System?


A program structured by a set of rules and
procedures that take the knowledge, supplied by
an expert, and recommend a course of action in
order to solve specific problems.


They use reasoning to work through problems
and offer recommendations that address these
problems.


They are ideal for diagnostic and prescriptive
problems.


They are usually built for specific applications
called domains.

Expert System Use


Field use


Accounting


Financial management


Production


Process control


Medication prescription


In many other domains

Expert Systems
-

Advantages


Its gathering and use of expertise


They can perform many functions that will
benefit organizations


Reduction in training costs


Decrease human error


Providing consistent answers to repetitive tasks


Safeguard sensitive company information


Expert Systems
-

Disadvantages


Its inability to solve problems for which it
was not designed


Its inability to use common sense and
judgment to solve newly encountered
problems

What is a Neural Network?


Artificial intelligence systems that can be
trained to recognize patterns and adapt to
new concepts and knowledge.


They are not bound by a set of rules
designed for a specific application.


They are able to imitate the human ability
to process information without following a
set of rules.

What are Neural Networks?


They use interconnecting neurons to
produce an output.


A neural network uses its neurons
collectively to execute its functions.


A neuron is the basic functioning element in a
neural network that takes inputs and produces
outputs.


This allows the neural network to continue
performing even if some of its neurons are
not functioning

Neural Network Use


They are useful for identification, classification,
and forecasting when dealing with a large
amount of information.


They are used in speech and visual recognition.


Field use


Engineering


Drilling


Meteorology


Medical


Insurance industries


Military.

Neural Networks
-

Advantages


They can adjust to new information on
their own.


They are able to function without
structured information.


They are able to process large volumes of
data.

Neural Networks
-

Disadvantage


The neural networks have hidden layers.


The fact that these layers are hidden
prohibits users from adjusting the
connections reducing control of the
system.

Overall Business Use


The systems increase completion rates
and decrease error by reducing human
interaction.


These systems protect information and
utilize knowledge more efficiently to make
intelligent decisions.


Companies can gain an edge over their
competitors by implementing these
systems.

Real World Applications


Banks


Hospitals


Credit Card Companies


Manufacturers


Robotics


Medical Fields

Conclusion


Artificial Intelligence


Expert Systems


Neural Networks


Business Uses


Real World Applications

Any questions?