[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(05):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(05):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(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第14卷
期数:
2019年05期
页码:
905-914
栏目:
出版日期:
2019-09-05

文章信息/Info

Title:
Ensemble deep belief network based on fuzzy partitioning and fuzzy weighting
作者:
张雄涛12 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 Xiongtao12 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:
ensembledeep belief networkfuzzy partitionfuzzy weightingrunning timefuzzy 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.

参考文献/References:

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备注/Memo

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