Customized Product Configuration Rule Intelligent Extraction and Dynamic Updating Method Based on the Least Recently Used Dynamic Decision Tree

Abstract

Abstract In the traditional customized product (CP) configuration design system, the configuration rules in the database usually rely on the manual input and maintenance of experienced designers. In complex product design, configuration rules are numerous, complex, and difficult to understand. The way of human input based on experience consumes plenty of resources, which are strictly limited by experienced designers. This overreliance on those experienced designers has seriously restricted the development of enterprises. To address this problem, a least recently used dynamic decision tree (LRU-DDT) algorithm for CP configuration rule intelligent extraction and dynamic updating is put forward in this article. Based on the decision table majority (DTM) classifier, the condition attributes are first reduced. An improved J48 decision tree algorithm is proposed to extract the CP configuration rules. In addition, the CP configuration rules can be dynamically updated based on LRU-DDT. To verify the proposed method, the GB10 high-speed elevator configuration design process is taken as an example. The configuration rules are extracted and updated by the proposed algorithms. The results show that the configuration solution efficiency is improved by 16%.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 5 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.