面向可解释性人工智能与大数据的模糊系统发展展望

陈德旺; 蔡际杰; 黄允浒

doi:10.11959/j.issn.2096-6652.201937

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面向可解释性人工智能与大数据的模糊系统发展展望

学术论文 | 更新时间：2024-06-05

- 面向可解释性人工智能与大数据的模糊系统发展展望
- Development prospect of fuzzy system oriented to interpretable artificial intelligence and big data
- 智能科学与技术学报 2019年1卷第4期页码：327-334
- 作者机构：
  
  1. 福州大学数学与计算机科学学院，福建福州 350108
  2. 福州大学智慧地铁福建省高校重点实验室，福建福州 350108
- 作者简介：
  
  [ "陈德旺（1976- ），男，博士，福州大学数学与计算机科学学院教授、博士生导师，福建省“闽江学者特聘教授”，美国加州大学伯克利分校访问学者，中国自动化协会混合智能专委会副主任，中国自动化协会粒计算专委会秘书长，IEEE 高级会员，IEEE Transaction on ITS编委，主要研究方向为人工智能、大数据、最优化、智慧地铁和智慧新能源等" ]
  [ "蔡际杰（1997- ），男，福州大学数学与计算机科学学院硕士生，主要研究方向为智能计算和大数据" ]
  [ "黄允浒（1990- ），男，福州大学数学与计算机科学学院博士生，主要研究方向为智能计算、大数据与最优化" ]
- 基金信息：
  
  国家自然科学基金项目(61976055);智慧地铁福建省高校重点实验室建设基金资助项目;The Construction of Key Laboratory of Intelligent Metro of Universities in Fujian Province(53001703);智慧地铁福建省高校重点实验室建设基金资助项目;The Construction of Key Laboratory of Intelligent Metro of Universities in Fujian Province(50013203)
- DOI：10.11959/j.issn.2096-6652.201937
  中图分类号： TP391.41，TP273
- 网络出版日期：2019-12，
  
  纸质出版日期：2019-12-20
- 稿件说明：
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陈德旺, 蔡际杰, 黄允浒. 面向可解释性人工智能与大数据的模糊系统发展展望[J]. 智能科学与技术学报, 2019,1(4):327-334.

Dewang CHEN, Jijie CAI, Yunhu HUANG. Development prospect of fuzzy system oriented to interpretable artificial intelligence and big data[J]. Chinese journal of intelligent science and technology, 2019, 1(4): 327-334.
陈德旺, 蔡际杰, 黄允浒. 面向可解释性人工智能与大数据的模糊系统发展展望[J]. 智能科学与技术学报, 2019,1(4):327-334. DOI： 10.11959/j.issn.2096-6652.201937.

Dewang CHEN, Jijie CAI, Yunhu HUANG. Development prospect of fuzzy system oriented to interpretable artificial intelligence and big data[J]. Chinese journal of intelligent science and technology, 2019, 1(4): 327-334. DOI： 10.11959/j.issn.2096-6652.201937.

摘要

模糊系统作为一种万能逼近器具有很强的可解释性，已被广泛应用在各个领域。尽管目前模糊系统的理论研究不够成熟，仍然存在诸如规则太多、优化困难、维度诅咒等问题，难以处理高维大数据。尽管深度神经网络取得了突出进展，能很好处理图像和语音等大数据，但其可解释性不好，难以用于安全相关的重要场合。因此，非常有必要研究一种基于模糊系统的可解释性强的人工智能算法。结合深度神经网络和模糊系统两者的优点，研究深度模糊系统及其算法，将有可能解决高维大数据问题。主要对模糊系统的发展历程与研究进展分别进行详细阐述，并根据其现有的问题指出其未来的发展方向，对进一步的研究问题进行展望。

Abstract

As a universal approximator with strong interpretability

fuzzy system has been widely used in various fields.Although the current theoretical research on fuzzy system is not mature enough

there are still many problems such as too many rules

optimization difficulties

dimension curse

which make it difficult to deal with high-dimensional large data.Although deep neural network has made remarkable progress and can process large data such as image and voice very well

its interpretability is not good and it is difficult to be used in important security-related occasions.Therefore

it is necessary to study an interpretable artificial intelligence algorithm based on fuzzy system.Combining the advantages of deep neural network and fuzzy system

it is possible to solve the problem of high dimensional and large data by studying the deep fuzzy system and its algorithm.The development history and research progress of fuzzy system separately was mainly reviews

and its future development direction according to its existing problems was pointed out

and the summary of this article and the prospect for further research about the problems were given.

关键词

Keywords

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