20-06-2012, 05:43 PM
Real Time Expert System
[attachment=24939]
Introduction
Real-time expert systems [1] are on-line knowledge-based
systems that combine analytical process models with
conventional process control while reasoning about the past,
present, and future to assess on-going developments and plan
appropriate actions.
Indicators that a real-time expert system might be appropriate,
especially when conventional techniques have failed or are
impractical, include problem-solving situations where humans
suffer from cognitive overload, fail to effectively monitor
all available information, are unable to resolve conflicting
constraints, are expensive.
Many "real-time" expert systems are 'soft' real-time systems, in
that they claim to be fast. A 'hard' real-time system would have
features that guarantee a response within a fixed amount of
real-time (e.g., bounded computation, not just a fast matchrecognize-
act cycle).
Systems like G2 use event-driven processing as a method of
limiting forward chaining.
Real time expert system architecture
Here we have passive elements like data files and knowledge
base which are denoted by square boxes and active elements
are data, knowledge manager, processes which are denoted
by dashed ovals. Data exchange between active and passive
elements is shown by arrows and communication between
active elements is shown by dashed arrows. We have divided
this architecture into two subsystems: intelligent subsystem
and real time subsystem. The interface divides and connects
the two subsystems.
Life cycle of Real time expert system
Lifecycle of real time expert system is similar to that of any
software system. Main stages are shown by rectangular boxes.
Basic sequence of any real time expert system is:
1. Task analysis and specification
2. Software design
3. Coding
4. Testing
5. Documentation and Implementation
Real-Time Expert System- Applications
Real time expert systems [4] are being used in almost all fields
like medical, aerospace, communications, process control,
robotics etc. Following are few expert systems used in medical
field:
1. CAPS: CAPS is a system that combines a patternrecognition
module with a system module to perform respiratory
and anesthesia monitoring. The pattern-recognition module
characterizes and analyzes each segment of a capnogram.
(A capnogram is a carbon dioxide wave form produced by
monitoring patient respired gases during surgery.) The analysis
of the capnogram is then used by the expert system module
to generate a probable diagnosis and recommend therapy or
equipment adjustments. The system was implemented using
the EXSYS tool on an IBM PC/AT.
[attachment=24939]
Introduction
Real-time expert systems [1] are on-line knowledge-based
systems that combine analytical process models with
conventional process control while reasoning about the past,
present, and future to assess on-going developments and plan
appropriate actions.
Indicators that a real-time expert system might be appropriate,
especially when conventional techniques have failed or are
impractical, include problem-solving situations where humans
suffer from cognitive overload, fail to effectively monitor
all available information, are unable to resolve conflicting
constraints, are expensive.
Many "real-time" expert systems are 'soft' real-time systems, in
that they claim to be fast. A 'hard' real-time system would have
features that guarantee a response within a fixed amount of
real-time (e.g., bounded computation, not just a fast matchrecognize-
act cycle).
Systems like G2 use event-driven processing as a method of
limiting forward chaining.
Real time expert system architecture
Here we have passive elements like data files and knowledge
base which are denoted by square boxes and active elements
are data, knowledge manager, processes which are denoted
by dashed ovals. Data exchange between active and passive
elements is shown by arrows and communication between
active elements is shown by dashed arrows. We have divided
this architecture into two subsystems: intelligent subsystem
and real time subsystem. The interface divides and connects
the two subsystems.
Life cycle of Real time expert system
Lifecycle of real time expert system is similar to that of any
software system. Main stages are shown by rectangular boxes.
Basic sequence of any real time expert system is:
1. Task analysis and specification
2. Software design
3. Coding
4. Testing
5. Documentation and Implementation
Real-Time Expert System- Applications
Real time expert systems [4] are being used in almost all fields
like medical, aerospace, communications, process control,
robotics etc. Following are few expert systems used in medical
field:
1. CAPS: CAPS is a system that combines a patternrecognition
module with a system module to perform respiratory
and anesthesia monitoring. The pattern-recognition module
characterizes and analyzes each segment of a capnogram.
(A capnogram is a carbon dioxide wave form produced by
monitoring patient respired gases during surgery.) The analysis
of the capnogram is then used by the expert system module
to generate a probable diagnosis and recommend therapy or
equipment adjustments. The system was implemented using
the EXSYS tool on an IBM PC/AT.