This paper addresses the challenging problem of developing the automatic algorithm for solving direct current circuit problem. Leveraging on the innovated methods it proposes a high-performance relation based algorithm, called RaDCC. The challenges of the problem lie in relation acquisition and relation inference presentation after adopting the newly-established relation principle of solving problems. A high-performance procedure is developed for the challenging task of relation acquisition by leveraging on three innovated methods. Three methods are an enhanced schematics understanding method that can understand complicated structures of schematics, an extended syntax-semantics model method and a unit-theorem inference method to acquire schematic relations, explicit text relations and implicit text relations, respectively. To address another challenging problem of readable solution generation an action-schema presentation method is proposed to convert relation inference actions into relation inference presentations. The experimental results show that the proposed algorithm is high-performance since it achieves an accuracy of over 83.2% for solving problems from textbooks and 70.6% for solving problems from examination papers on a dataset that contains 1012 direct current circuit problems collected from the authority sources, much higher than the performance of the baseline algorithm.

本文解决了开发用于解决直流电路问题的自动算法的挑战性问题。利用创新的方法，它提出了一种基于高性能关系的算法，称为RaDCC。问题的挑战在于采用新建立的解决问题的关系原理后的关系获取和关系推理表示。通过利用三种创新方法，开发了一种高性能程序来应对具有挑战性的关系获取任务。三种方法是一种增强的原理图理解方法，可以理解原理图的复杂结构；一种扩展的语法-语义模型方法和一种用于获取原理图关系，显式文本关系和隐式文本关系的单位定理推断方法。为了解决可读解决方案生成的另一个具有挑战性的问题，提出了一种动作模式表示方法，以将关系推理动作转换为关系推理表示。实验结果表明，该算法具有较高的性能，因为在包含1012个从权威来源收集的直流电路问题的数据集上，该算法解决教科书中的问题的准确率达到83.2％以上，解决试卷中的问题的精度达到70.6％以上。 ，远高于基准算法的性能。