IPC분류정보
국가/구분 |
United States(US) Patent
등록
|
국제특허분류(IPC7판) |
|
출원번호 |
UP-0506585
(2006-08-18)
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등록번호 |
US-7765175
(2010-08-13)
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발명자
/ 주소 |
- Crandall, John G.
- Chatfield, Glen F.
|
출원인 / 주소 |
- OPTIMUM Power Technology, L.P.
|
대리인 / 주소 |
|
인용정보 |
피인용 횟수 :
18 인용 특허 :
44 |
초록
▼
An expert system having a data storage device and a processor. The data storage device stores models having attributes, objectives having rules for evaluating the models, and strategies having rules for modifying the attributes. The processor evaluates a selected model in accordance with a selected
An expert system having a data storage device and a processor. The data storage device stores models having attributes, objectives having rules for evaluating the models, and strategies having rules for modifying the attributes. The processor evaluates a selected model in accordance with a selected objective and having the variable attribute set in accordance with a selected strategy to determine a characteristic value associated with the selected model and the variable attribute setting. The processor also stores information associated with improved results in the data storage device.
대표청구항
▼
What is claimed is: 1. An expert system, comprising: a data storage device, in which is stored a knowledgebase having a database structure that includes: a plurality of models, each defining one of a device and a process, each model including a plurality of attributes including a variable attribute
What is claimed is: 1. An expert system, comprising: a data storage device, in which is stored a knowledgebase having a database structure that includes: a plurality of models, each defining one of a device and a process, each model including a plurality of attributes including a variable attribute, the attributes corresponding to attributes of one of the device and the process defined by the model; a plurality of objectives, each objective including an objective rule for evaluating a characteristic of at least one of the models; a plurality of strategies, each strategy including a strategic rule for modifying the variable attribute of at least one of the models; and a sub-knowledgebase including an identification of at least one of the models, an identification of at least one of the objectives, and an identification of at least one of the strategies; and a processor coupled to the data storage device, the processor executing instructions which, cause the processor to: evaluate a selected model identified in the sub-knowledgebase in accordance with a selected objective identified in the sub-knowledgebase, the variable attribute of the model being set in accordance with a selected strategy identified in the sub-knowledgebase to determine a characteristic value associated with the selected model and the variable attribute setting; determine, using the objective rule, whether the characteristic value is an improvement over a previous characteristic value; and store a result in the storage device so as to be accessible to a user when the characteristic value is an improvement over the previous characteristic value, the result including an identification of the selected model and the variable attribute setting used to determine the improved characteristic value for one of the device and the process defined by the model. 2. The expert system of claim 1, wherein the result is stored in association with the selected model. 3. The expert system of claim 1, wherein the result is stored with a pointer identifying the selected model. 4. The expert system of claim 1, wherein at least two models are identified in the sub-knowledgebase and the instructions cause the processor to evaluate more than one model identified in the sub-knowledgebase. 5. The expert system of claim 1, wherein the instructions cause the processor to create a new model having the plurality of attributes of the selected model and a variable attribute value determined using the strategy. 6. The expert system of claim 1, wherein the objective rule includes a goal. 7. The expert system of claim 1, wherein each strategy further includes an identification of the variable attribute to which the strategic rule applies. 8. The expert system of claim 1, wherein the selected model includes a plurality of variable attributes and the selected strategy includes a strategic rule for each of at least a subset of the plurality of variable attributes. 9. The expert system of claim 8, wherein the selected strategy further includes an identification of the variable attributes to which the strategic rules apply. 10. The expert system of claim 1, wherein the strategic rule defines how the variable attribute is to be varied. 11. The expert system of claim 1, wherein the strategic rule includes a range of values for the variable attribute. 12. The expert system of claim 1, wherein at least two strategies are identified in the sub-knowledgebase and the instructions cause the processor to evaluate the selected model in accordance with more than one strategy identified in the sub-knowledgebase. 13. The expert system of claim 1, further comprising an input device coupled to the processor, the input device to accept instructions from a user. 14. The expert system of claim 13, wherein the processor receives instructions from the input device which further cause the processor to modify the selected model. 15. The expert system of claim 13, wherein the processor receives instructions from the input device which further cause the processor to modify the selected objective. 16. The expert system of claim 1, wherein the selected objective is stored in the storage device if the characteristic value is an improvement over a previous characteristic value. 17. The expert system of claim 13, wherein the processor receives instructions from the input device which further cause the processor to modify the selected strategy. 18. The expert system of claim 1, wherein the selected strategy is stored in the storage device if the characteristic value is an improvement over a previous characteristic value. 19. The expert system of claim 13, wherein the processor receives instructions from the input device which further cause the processor to perform one or more of: create a new model, retrieve one of the models from the knowledgebase, retrieve and edit one of the models from the knowledgebase, store a new model in the knowledgebase, create a new objective, retrieve one of the objectives from the knowledgebase, retrieve and edit one of the objectives from the knowledgebase, store a new objective in the knowledgebase, create a new strategy, retrieve one of the strategies from the knowledgebase, retrieve and edit one of the strategies from the knowledgebase, and store a new strategy in the knowledgebase. 20. The expert system of claim 1 further comprising an output device coupled to the processor, wherein the processor further includes instructions that cause the output device to display the selected strategy to the user, display the selected objective to the user, display the selected model to the user, display the characteristic value to the user, and display the result to the user. 21. The expert system of claim 1, wherein the evaluation includes simulating the operation of a device. 22. The expert system of claim 1, wherein the evaluation includes simulating a process. 23. The expert system of claim 1, wherein the evaluation includes solving a problem. 24. The expert system of claim 1, wherein the evaluation includes solving an equation. 25. The expert system of claim 1, wherein the instructions further cause the processor to evaluate the model repeatedly using a plurality of different values for the variable attribute in accordance with the strategic rule. 26. The expert system of claim 1, wherein the instructions further cause the processor to: evaluate the selected model with the variable attribute set to a base value to determine a base characteristic value; generate a plurality of different values for the variable attribute; and evaluate the selected model with the variable attribute set to each of the plurality of different values to determine a characteristic value associated with the model and each variable attribute setting. 27. The expert system of claim 1, wherein the instructions further cause the processor to rank the characteristic value, using the objective rule, in relation to a previous value determined for the characteristic. 28. The expert system of claim 1, wherein the instructions further cause the processor to store the selected model with the variable attribute setting in the sub-knowledgebase when the characteristic value is an improvement over the previous characteristic value. 29. The expert system of claim 1, wherein the instructions further cause the processor to store the variable attribute setting used to determine the improved characteristic value with a pointer to a previously stored model used in the evaluation that resulted in the improved characteristic value. 30. The expert system of claim 1, wherein the instructions further cause the processor to store the improved characteristic value in the sub-knowledgebase. 31. An expert system, comprising: a data storage device, in which is stored: a plurality of models, each defining one of a device and a process, each model including a plurality of attributes including a variable attribute, the attributes corresponding to attributes of one of the device and the process defined by the model; a plurality of objectives, each objective including an objective rule for evaluating a characteristic of at least one of the models; and a plurality of strategies, each strategy including a strategic rule for modifying the variable attribute; and a processor coupled to the data storage device, the processor executing instructions which, cause the processor to: create a new strategy; evaluate a selected model stored in the data storage device in accordance with a selected objective stored in the data storage device and having the variable attribute set in accordance with at least one of the new strategy and one of the strategies stored in the data storage device to determine a characteristic value associated with the selected model and the variable attribute setting; store an identification of the new strategy used in the evaluation in the data storage device; determine, using the objective rule, whether the characteristic value is an improvement over a previous characteristic value; and store a result in the storage device when the characteristic value is an improvement over the previous characteristic value, the result including an identification of the selected model and the variable attribute setting used to determine the improved characteristic value for one of the device and the process defined by the model. 32. The expert system of claim 31, wherein the instructions further cause the processor to store an identification of a user who created the new strategy with the new strategy. 33. The expert system of claim 32, wherein the instructions further cause the processor to prevent the user who created the new strategy from removing the new strategy from the data storage device. 34. The expert system of claim 31, wherein the instructions further cause the processor to store an identification of one of the plurality of strategies from which the new strategy was created with the new strategy. 35. The expert system of claim 1, wherein the device includes an internal combustion engine. 36. The expert system of claim 1, wherein the selected model, the selected objective, and the selected strategy are selected by a user. 37. The expert system of claim 1, wherein the selected model, the selected objective, and the selected strategy are selected by the processor.
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