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设计中开发计算理论的一个挑战是必须能支持计算机制的有效运用 ,这一机制允许从设计专家那儿或设计样例中取得产生 ,累加和转换的设计知识。而其中的一个方法是把机器学习机制综合成基于知识的支持系统 ,以模拟设计过程初级阶段 ,使设计成为一个增加和诱导学习的过程。模拟的需要产生于在不同的提取阶段获取 ,提炼和转移设计知识的需求 ,从而使得能轻而易举的熟练操作。在设计中 ,现有的知识产生于过去的设计解决方案 ,而过去的解决方案提供的反馈信息能更新和提高设计理论知识基础。但是 ,没有学习接受能力 ,设计系统不能反映设计家们在这一领域的成长经历 ,也不能反映设计家们从以往设计案例中提取知识的能力。在此提出了方案设计和效力评价中的三种方法
One of the challenges in developing computational theory in design is that it must be able to support the efficient use of computational mechanisms that allow the generation, accumulation, and transformation of design knowledge from design professionals or design examples. One of these approaches is to integrate machine learning mechanisms into a knowledge-based support system to simulate the initial stages of the design process, making the design a process of augmenting and inducing learning. The need for simulation stems from the need to acquire, refine and transfer design knowledge at different stages of the extraction, thereby making it easy to master. In design, the existing knowledge stems from past design solutions, and the feedback provided by past solutions can update and enhance the knowledge base of design theory. However, without learning ability to accept, the design system does not reflect the designer’s growth experience in this area, nor does he reflect the designer’s ability to extract knowledge from past design cases. Here are three options for program design and effectiveness evaluation