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[1]张雄涛,胡文军,王士同.一种基于模糊划分和模糊加权的集成深度信念网络[J].智能系统学报,2019,14(5):905-914.[doi:10.11992/tis.201809018]
　ZHANG Xiongtao,HU Wenjun,WANG Shitong.Ensemble deep belief network based on fuzzy partitioning and fuzzy weighting[J].CAAI Transactions on Intelligent Systems,2019,14(5):905-914.[doi:10.11992/tis.201809018]

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一种基于模糊划分和模糊加权的集成深度信念网络

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《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 14 期数: 2019年第5期页码: 905-914 栏目: 学术论文—人工智能基础出版日期: 2019-09-05

Title:: Ensemble deep belief network based on fuzzy partitioning and fuzzy weighting

作者:: 张雄涛^1,2, 胡文军², 王士同¹; 1. 江南大学数字媒体学院, 江苏无锡 214122;
2. 湖州师范学院信息工程学院, 浙江湖州 313000

Author(s):: ZHANG Xiongtao^1,2, HU Wenjun², WANG Shitong¹; 1. School of Digital Media, Jiangnan University, Wuxi 214122, China;
2. School of Information Engineering, Huzhou University, Huzhou 313000, China

关键词:: 集成; 深度信念网络; 模糊划分; 模糊加权; 运行时间; 模糊聚类算法; 模糊理论

Keywords:: ensemble; deep belief network; fuzzy partition; fuzzy weighting; running time; fuzzy clustering algorithm (FCM); fuzzy theory

分类号:: O235;TP18

DOI:: 10.11992/tis.201809018

摘要:: 针对DBN算法训练时间复杂度高，容易过拟合等问题，受模糊理论启发，提出了一种基于模糊划分和模糊加权的集成深度信念网络，即FE-DBN（ensemble deep belief network with fuzzy partition and fuzzy weighting），用于处理大样本数据的分类问题。通过模糊聚类算法FCM将训练数据划分为多个子集，在各个子集上并行训练不同结构的DBN，将每个分类器的结果进行模糊加权。在人工数据集、UCI数据集上的实验结果表明，提出的FE-DBN比DBN精度均有所提升，具有更快的运行时间。

Abstract:: Aiming at the problems of high training time complexity and easy over-fitting of the deep belief network (DBN) algorithm, inspired by the fuzzy theory, an ensemble deep belief network based on fuzzy partitioning and fuzzy weighting, namely FE-DBN (ensemble deep belief network with fuzzy partition and fuzzy weighting), is proposed to deal with the classification of large-scale data. First, the training data is divided into several subsets by fuzzy clustering algorithm (FCM), and then the DBNs of different structures are trained in parallel on each subset. Finally, the results of each classifier are ensembled by fuzzy weighting. Experiments on artificial datasets and UCI datasets show that the proposed FE-DBN outperforms the DBN in terms of accuracy and running time.

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备注/Memo

收稿日期:2018-09-13。
基金项目:国家自然科学基金面上项目（61572236，61300151，61772198）.
作者简介:张雄涛,男,1984年生,博士研究生,主要研究方向为模式识别、模糊系统;胡文军,男,1977年生,教授,主要研究方向为模式识别、人工智能;王士同,男,1964年生,教授,主要研究方向为人工智能、数据挖掘、模糊系统。
通讯作者:张雄涛.E-mail:1047897965@qq.com

更新日期/Last Update: 1900-01-01

一种基于模糊划分和模糊加权的集成深度信念网络 PDF下载HTML

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一种基于模糊划分和模糊加权的集成深度信念网络

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