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6.expert systems

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  • 1.  
  • 2. INTRODUCTION
    • AI programs that achieve expert level competence (ability) in solving problems in particular task area by use of knowledge base about that particular task area are known as KNOWLEDGE BASED OR EXPERT SYSTEMS.
    • These are complex AI programs.
    • Expert systems are generally software's .
    • These software helps us to provide an answer to a problem .
    • It helps to clarify uncertainties that comes in sy stem .
  • 3. TASK-DOMAIN
    • The human intellectual (requiring the use of mind) trying to be captured in an expert system is called the task domain .
    • TASK —means some goal oriented, problem solving activity.
    • DOMAIN —means area within which the task is being performed.
  • 4. PERFORMANCE
    • Performance of the expert system is based on following methods:-
    • Knowledge engineering:-
    • Building an expert system is known as KNOWLEDGE ENGINEERING.
    • In this knowledge gathers from subject matter experts and then codifying this knowledge according to the formalism.
    • Persons doing this are called KNOWLEDGE ENGINEER .
  • 5.  
  • 6. COMPONENTS OF EXPERT SYSTEMS
    • BUILIDING BLOCKS OF EXPERT SYSTEM:-
    • Every expert system consist of two principal parts:
    • (a) Knowledge base
    • (b) Reasoning or inference
  • 7. Knowledge base
    • It is expert systems contain both factual and heuristic knowledge.
    • Factual knowledge is that knowledge of task domain that is widely shared, typically found in textbooks or journals.
    • Heuristic knowledge is less exhaustive, more experiential, more judgmental knowledge of performance.
  • 8. Reasoning
    • Two methods of reasoning when using inference rules: 
    • (i) Backward chaining: it starts with list of goals and works backward if there is data which will allow it to conclude these goals.
    • (ii) Forward chaining: it starts with data available and then concludes a desired goal.
  • 9. THE APPLICATION OF EXPERT SYSTEMS
    • Its applications spread in a wide range i.e. in industrial and commercial problems etc.
    • Diagnosis and troubleshooting of devices and system of all kinds
    • Planning and scheduling
    • Configuration of manufactured objects
    • Financial decision making
    • Knowledge publishing
    • Process monitoring and control
  • 10. ADVANTAGES
    • COSISTENT: it provides consistent answer for repetitive decisions, processes and tasks
    • MAINTAINS: it holds and maintain levels of information
    • CLARIFY: it clarify the logic of decision making
    • NO HUMAN NEED: it cannot needs human, it works continuously
    • MULTIUSER: a multi user expert system can serve more users at a time
  • 11. DIS-ADVANTAGES
    • SENSE: it lacks common sense needed in decision making
    • CREATIVENESS: it cannot respond creatively like a human expert would in unusual circumstances
    • ERRORS: in knowledge base errors may occur and this leads wrong decisions
    • ENVIRONMENTS: if knowledge base is changed it cannot adapt changing environments
  • 12. USES OF EXPERT SYSTEMS
    • In medical field
    • In agricultural
    • In education etc.
  • 13. IN MEDICAL FIELD
  • 14.  
  • 15. EXAMPLES OF ES IN MEDICAL (1) PXDES
    • It is example of medical expert system.
    • It is a lung disease, X-ray diagnosis.
    • It takes our lungs picture from upper side of body which looks like a shadow.
    • The shadow is used to determine the type and degree of harmness.
    • These systems include three modes: 
    • The knowledge base
    • The explanation interface
    • The knowledge acquisition
    • (1) KNOWLEDGE BASE:-
    • It contains the data of X-ray representations of various stages of the disease. 
    • (2) EXPLANATION INTERFACE :-
    • It details the conclusion.
    • (3) KNOWLEDGE ACQUISITION :-
    • It allow medical experts to add or change information in the system.
  • 16. (2) CaDet
    • It is for early cancer detection.
    • Clinical data related to early cancer detection and to cancer risk factors was collected and incorporated in database, together with heuristic rules for evaluating this data.
  • 17. (3) DXplain
    • It is used for diagnosis.
    • Its data based contain approximately 4,500 suggestion for over 2,000 different diseases.
  • 18. (4) MYCIN
    • It is simple example of ES.
    • It performs a task normally done by a human expert.
    • It attempts to recommend appropriate therapies for patient with bacterial infections.
    • It uses LISP structures for writing internally rules.
    • It uses these rules to reason backward to the clinical data available from its goal of finding disease-causing organism.
  • 19. (5) GERMWATCHER
    • It is for infection control.
  • 20. AGRICULTURAL EXPERT SYSTEMS
    • WHY?
    • It is same as other knowledge based systems.
    • It uses to give answer about pest control, the need to spray, selection of a chemical to spray, weather damage recovery such as freeze etc.
  • 21.  
  • 22. ARICULTURAL EXPERT SYSTEM
    • (1) RICE-CROP DOCTOR:
    • This ES is developed by NATIONAL INSTITUTE OF AGRICULTURAL EXTENSION MANAGEMENT.
    • Its main work is to diagnose pests and diseases for rice crop and suggest preventive measures.
    • It has knowledge about diseases and pests for identification and suggesting preventive measures.
    • (1) DISEASES :
    • Rice blast
    • Brown spots
    • Rice tungro virus
    • Bacterial leaf blight etc
    • (2) PESTS:
    • Stem borers
    • Brown plant hopper
    • Rice leaf folder
    • Green leaf hopper etc
  • 23. AGRICULTURAL EXPERT SYSTEM
    • (2) AGREX:
    • It gives correct advice to farmers.
    • Topics of advice are fertilizer application, crop protection, irrigation scheduling and diagnosis of diseases in paddy and post harvest technology of fruits and vegetables
  • 24. AGRICULTURAL EXPERT SYSTEM
    • NAMES OF SOME OTHER EXPERT SYSTEMS:
    • CLIPS
    • GIS
    • LEY
    • CALEX
  • 25. AGRICULTURAL EXPERT SYSTEM
    • ADVANTAGES:-
    • It has ability to imitate human thought and reasoning.
    • It makes modification of knowledge very convenient.
    • It helps increases the production of crops
    • It has ability to handle uncertain information
    • It helps the farmers to take single point decision.
  • 26. EXPERT SYSTEMS IN EDUCATION
    • WHY?
    • Because it allow users to ask question on some education problems.
  • 27. IN EDUCATION
    • FIELDS:
    • Computer animation
    • Computer science
    • Engineering
    • Language (expert system teaches language)
  • 28.  
  • 29. IN EDUCATION
    • This figure shows the architecture of ITS for teaching engineering student which has embedded expert system inside.
    • For each student expert system will create performance of student and change levels (like easy to difficult).