Justification for the selection of manufacturing technologies: a fuzzy-decision-tree-based approach
Justification for the selection of manufacturing technologies: a fuzzy-decision-tree-based approach
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DOI：
10.1080/00207543.2011.638943
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发表时间：
2012-10
影响因子：
9.2
通讯作者：
L. Evans;N. Lohse;K. Tan;P. Webb;M. Summers
中科院分区：
文献类型：
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作者：
L. Evans;N. Lohse;K. Tan;P. Webb;M. Summers
本文提出了一种改进的替代制造技术论证模型。该方法基于模糊决策树，提供了一种方法，能够识别技术案例库中的模式，以支持制造系统的评估。专家是决策过程中极具影响力的个人；他们在选择投资时提供支持和指导。体验型任务建立在以前的案例或专家经验的基础上，因此很难用理性的形式来表达。该概念基于案例推理、规则归纳和专家系统理论的多个特点。该框架围绕模糊决策树数据挖掘技术构建，提供了使用受监管的案例信息作为辅助决策过程的结构化经验的能力。模糊归纳法从一组经验数据中提取形式规则，专家系统哲学计算用于解决问题的人类专业知识的经验基础。测试用例表明了该分类算法的稳定性，并验证了该算法在领域内的适用性。
In this paper, a developed model for the justification of alternative manufacturing technologies is presented. The approach, based on fuzzy decision trees, provides a methodology capable of identifying patterns within a technology case repository to support the evaluation of manufacturing systems. Experts are highly influential individuals in the decision process; they provide support and guidance when selecting investments. The experience-oriented task is founded on previous cases or an experts’ experience, and therefore difficult to express in a rational form. The concept is based on a number of characteristics of the case-based reasoning, rule induction and expert system theory. Structured around the fuzzy-decision-tree data-mining technique, the framework provides the ability of using regulated case information to act as structured experience for assisting in the decision process. Fuzzy induction extracts formal rules from a set of experience data, and the expert system philosophy computes the experience base of human expertise for problem-solving. A test case indicates the stability of the classification algorithm and verifies the applicability within the domain.