[1]梁慧,曹峰,钱宇华,等.图像情境下的数字序列逻辑学习[J].智能系统学报,2019,14(6):1189-1198.[doi:10.11992/tis.201905044]
　LIANG Hui,CAO Feng,QIAN Yuhua,et al.Number sequence logic learning in image context[J].CAAI Transactions on Intelligent Systems,2019,14(6):1189-1198.[doi:10.11992/tis.201905044]
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图像情境下的数字序列逻辑学习

《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 14 期数: 2019年第6期 页码: 1189-1198 栏目: 学术论文—知识工程 出版日期: 2019-11-05
Title:
Number sequence logic learning in image context
作者:
梁慧1,3, 曹峰1,3, 钱宇华1,2,3, 郭倩1,3, 梁新彦1,3
1. 山西大学 大数据科学与产业研究院, 山西 太原 030006;
2. 山西大学 计算智能与中文信息处理教育部重点实验室, 山西 太原 030006;
3. 山西大学 计算机与信息技术学院, 山西 太原 030006
Author(s):
LIANG Hui1,3, CAO Feng1,3, QIAN Yuhua1,2,3, GUO Qian1,3, LIANG Xinyan1,3
1. Research Institute of Big Data Science and Industry, Shanxi University, Taiyuan 030006, China;
2. Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan 030006, China;
3. School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China
关键词:
人工智能; 逻辑推理; 逻辑学习; 深度学习; 数字序列; 图像处理; 神经网络; 模式构建
Keywords:
artificial intelligence; logical reasoning; logical learning; deep learning; number sequences; image processing; neural network; pattern construction
分类号:
TP181
DOI:
10.11992/tis.201905044
摘要:
针对未知的数字和规则的模式构建问题，本文提供了一种从图像角度解决数字序列逻辑学习问题的手段。该方法是在计算机不知道图像间关系和图像内包含的内容的意义的前提下，让计算机自主地学习出其中包含的内在逻辑模式，从而进行数字序列的预测。本文构建了4个大型数据集：Linear序列、Multiplication序列、Fio序列和Nested序列，然后使用几种代表性的深度神经网络来完成数字序列逻辑学习任务，并对实验结果加以分析比较，事实证明，本文所提出的方法在一定程度上可以解决未知的数字和规则的模式构建问题，这为一系列未知逻辑模式构建任务提供了一种可能性。
Abstract:
To solve the problem of pattern construction of unknown numbers and rules, in this paper, we provide a method to solve the problems of number sequence logic learning from the image perspective. The method allows the computer to automatically learn the inherent logic pattern without prior knowledge of the meaning of the image content or of the relationship between images so as to predict the number sequence. Four large datasets were constructed: linear sequences, multiplication sequences, fio sequences, and nested sequences, and then several representative deep neural networks were used to complete the number sequence logic learning task. By analyzing the experimental results, the method was found capable of solving the problem of pattern construction for unknown numbers and rules to a certain extent, which will provide a potential solution for a series of unknown logic pattern construction tasks.
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备注/Memo

收稿日期:2019-04-15。
基金项目:国家自然科学基金项目（61672332，61432011，U1435212，61872226）；山西省海外归国人员研究项目（2017023）；山西省自然科学基金计划资助项目（201701D121052）
作者简介:梁慧,女,1994年生,硕士研究生,主要研究方向为机器学习、深度学习和逻辑学习;曹峰,男,1980年生,副教授,博士,主要研究方向为人工智能、空间数据挖掘。主持国家自然科学青年基金项目1项,山西省青年科技研究基金项目1项,参与山西省青年科技研究基金项目2项,获中国科学院大学优秀毕业生称号,博士论文被评为中国科学院地理科学与资源研究所优秀博士论文。发表学术论文10余篇;钱宇华,男,1976年生,教授,博士生导师,主要研究方向为人工智能、大数据、复杂网络、数据挖掘与机器学习。2014-2016年,连续入选爱思唯尔中国高被引学者榜单。曾获得山西省科学技术奖(自然科学类)一等奖,教育部宝钢教育基金特等奖,CCF优秀博士论文奖,山西省"五四青年奖章",全国百篇优秀博士论文提名奖,获发明专利2项。发表学术论文80余篇
通讯作者:钱宇华.E-mail:jinchengqyh@126.com

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