1.Use knowledge in the form of rules of thumb or heuristics to solve problems in a narrow domain.
2.In a human brain,knowledge exists in a compiled form.
3.capable of explaining a line of reasoning and providing the details.
4.use inexact reasoning and can deal with incomplete,uncertain and fuzzy information.
5.can make mistakes when information is incomplete or fuzzy.
6.Enhance the quality of problem solving via years of learning and practical training. This process is slow,inefficient and expensive.
expert systems
1.Process knowledge expressed in the form of rules and use symbolic reasoning to solve problems in a narrow domain.
2.Provide a clear separation of knowledge from its processing.
3.Trace the rules fired during a problem-solving session and explain how a particular conclusion was reached and why specific data was needed.
4.Permit inexact reasoning and can deal with incomplete,uncertain and fuzzy data.
5.Can make mistakes when data is incomplete or fuzzy.
6.Enhance the quality of problem solving by adding new rules or adjusting old ones in the knowledge base.When new knowledge is acquired,changes are easy to accomplish.
conventional programs
1.Process data and use algorithms, a series of well-defined operations, to solve general numerical problems.
2.Do not separate knowledge from the control structure to process this knowledge.
3.Do not explain how a particular result was obtained and why input data was needed.
4.Work only on problems where data is complete and exact.
5.Provide no solution at all,or a wrong one,when data is incomplete or fuzzy.
6.Enhance the quality of problem solving by changing the program code,which affects both the knowledge and its processing,making changes difficult.
1.Use knowledge in the form of rules of thumb or heuristics to solve problems in a narrow domain.2.In a human brain,knowledge exists in a compiled form.3.capable of explaining a line of reasoning and providing the details.4.use inexact reasoning and can deal with incomplete,uncertain and fuzzy information.5.can make mistakes when information is incomplete or fuzzy.6.Enhance the quality of problem solving via years of learning and practical training. This process is slow,inefficient and expensive.expert systems1.Process knowledge expressed in the form of rules and use symbolic reasoning to solve problems in a narrow domain.2.Provide a clear separation of knowledge from its processing.3.Trace the rules fired during a problem-solving session and explain how a particular conclusion was reached and why specific data was needed.4.Permit inexact reasoning and can deal with incomplete,uncertain and fuzzy data.5.Can make mistakes when data is incomplete or fuzzy.6.Enhance the quality of problem solving by adding new rules or adjusting old ones in the knowledge base.When new knowledge is acquired,changes are easy to accomplish.conventional programs1.Process data and use algorithms, a series of well-defined operations, to solve general numerical problems.2.Do not separate knowledge from the control structure to process this knowledge.3.Do not explain how a particular result was obtained and why input data was needed.4.Work only on problems where data is complete and exact.5.Provide no solution at all,or a wrong one,when data is incomplete or fuzzy.6.Enhance the quality of problem solving by changing the program code,which affects both the knowledge and its processing,making changes difficult.
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