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6. The fact that the attributes must be numerical and comparable is stipulated by TOPSIS.
7. The relative closeness computed in TOPSIS can be used as a performance assessment of multi-response
8. Measurement of each response must be carefully made by the standard.
9. Systematic optimization of the problem is the focus of this section.
10. Determination from the experience of an engineer shows how much pressure is affected by time.
11. Further analysis of the facility is necessary for the practitioner to make an adjustment of the
12. Minimization of A and B levels can be achieved by setting factors A and B at A2.
|非正式工程英文技術報告 (11) (上)
* 簡要的描述工程方案所關心的事項 。經由一個句子描述工程機構對影響目標工程或客戶有關事項的關心程度。
簡要的描述工程方案所關心的事項 Our most recent project focused on how to avoid the large time requirement involved in designing a rule base. 闡明特定部門或客戶所關心的工程環境Many machine learning and optimization application-related problems are solved by using genetic algorithms (GAs) with the multi-state property. For instance, in chess, a good player often employs various strategies based on his opponent’s moves, the game’s progress, or the chess clock. Therefore, an intelligent chess playing program should consider the multi-state property to perform more effectively. Consider stock market investments as another example. Investors adopt various strategies according to whether the market is up or down. This behavior implies that a decision support system for investment should consider the multi-state property. Applying various strategies to distinct states of a problem is natural. A different solution or strategy should be employed by varying problem solving states to achieve the global optimum. However, conventional methods cannot solve multi-state problems. 介紹管理問題 Although genetic algorithms are widely applied to machine learning and optimization, conventional GAs have not received much attention. Conventional approaches can use human designed rule bases to represent a multi-state solution, as well as use GAs to alter the rule base. However, to our knowledge, no systematic method has been developed for dealing with the multi-state property in a GA-implemented system. If the solution varies with the problem state in a multi-state problem, conventional methods neglect the multi-state property and yield an inaccurate and unfeasible solution. For instance, an investment decision support system that adopts a single strategy, regardless of whether the market is up or down, leads to an unsuccessful investment. Although a rule base can be used to represent the multi-state property, designing the rule base requires many man hours.