一种基于CBR的系统建模方法
A Methodological Approach to Model CBR-based Systems
摘要：
人工智能（AI）已被用于各个领域，以支持系统优化并找到解决方案，其中复杂性使得使用算法和算法学具有挑战性。基于案例的推理（CBR）是一种人工智能技术，广泛应用于管理、医学、设计、建筑、零售和智能电网等领域。CBR是一种解决问题的技术，通过使用过去的经验来获取新的知识。CBR部署的主要挑战之一是目标系统建模过程。本文提出了一种简单的方法，模型基于CBR的应用程序使用的概念，抽象和具体的模型。将建模过程分为两个模型，便于在应用领域和CBR技术之间分配专业知识。该方法的目的是促进CBR建模过程，并促进CBR在计算机科学以外的各个领域的使用。
英文摘要：
Artificial intelligence (AI) has been used in various areas to support system optimization and find solutions where the complexity makes it challenging to use algorithmic and heuristics. Case-based Reasoning (CBR) is an AI technique intensively exploited in domains like management, medicine, design, construction, retail and smart grid. CBR is a technique for problem-solving and captures new knowledge by using past experiences. One of the main CBR deployment challenges is the target system modeling process. This paper presents a straightforward methodological approach to model CBR-based applications using the concepts of abstract and concrete models. Splitting the modeling process with two models facilitates the allocation of expertise between the application domain and the CBR technology. The methodological approach intends to facilitate the CBR modeling process and to foster CBR use in various areas outside computer science.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
