Data driven construction and inference methodology of belief rule-base

doi:10.11772/j.issn.1001-9081.2014.08.2155

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (8): 2155-2160.DOI: 10.11772/j.issn.1001-9081.2014.08.2155

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Data driven construction and inference methodology of belief rule-base

YU Ruiyin¹,YANG Longjie²,FU Yanggeng²

1. College of Mathematics and Computer Science, Fuzhou University, Fuzhou Fujian 350116, China
2. College of Mathematics and Computer Science, Fuzhou University, Fuzhou Fujian 350116, China;

Received:2014-04-29 Revised:2014-05-08 Online:2014-08-10 Published:2014-08-01
Contact: FU Yanggeng

数据驱动的置信规则库构建与推理方法

余瑞银,杨隆浩,傅仰耿

福州大学数学与计算机科学学院，福州350116

通讯作者: 傅仰耿
作者简介:余瑞银(1990-),男,福建福州人,硕士研究生,主要研究方向：智能决策、置信规则库推理；杨隆浩(1990-),男,福建南平人,硕士研究生,主要研究方向：智能决策、置信规则库推理；傅仰耿(1981-),男,福建泉州人,讲师,博士,CCF会员,主要研究方向：不确定多准则决策、置信规则库推理、移动互联网。
基金资助:
国家自然科学基金青年项目;国家杰出青年科学基金项目;国家自然科学基金面上项目;福建省教育厅A类科技项目;福州大学科技发展基金资助项目

Abstract

Abstract:

Considering the problem of the low inference accuracy of the extended Belief Rule Base (BRB) which was proposed by Liu, etc (LIU J, MARTINEZ L, CALZADA A, et al. A novel belief rule base representation, generation and its inference methodology. Knowledge-Based Systems, 2013, 53: 129-141), an improved method of rule-base construction and inference was proposed. This approach was based on the method of Liu's rule-base construction, and a new generation method of rule antecedents and a new calculation method of rule weights were provided. Subsequently, in order to avoid activating so many unnecessary rules, the 80/20 rule was introduced to improve the strategy of rule activation. Then an integrated construction and inference methodology of belief rule-base was formed. Finally, in order to validate the accuracy and efficiency of the new approach, the case study in pipeline leak detection was provided. The experimental results show that the proposed approach not only can keep lower time-consumption, but also can make the Mean Absolute Error (MAE) of system be reduced to 0.17342. This proves that the new approach has high accuracy and efficiency.

摘要：

针对Liu等(LIU J, MARTINEZ L, CALZADA A, et al. A novel belief rule base representation, generation and its inference methodology. Knowledge-Based Systems, 2013, 53: 129-141)提出的扩展置信规则库(BRB)推理精度不够高的问题，提出了一种改进的规则库构建与推理方法。在Liu等提出的规则库构建方法的基础上，给出了一种新的生成规则前件与计算规则权重的方法；同时为了避免大量不必要的规则被激活，引入80/20法则改进规则激活策略，并最终形成完整的置信规则库构建与推理方法。通过输油管道检漏的实例对所提方法的准确性和效率进行对比分析。实验结果表明，所提方法能够在保证低耗时的同时，将系统平均绝对误差(MAE)降低到0.17342，具有较高的效率和精度。

CLC Number:

TP18
TP273.5

YU Ruiyin YANG Longjie FU Yanggeng. Data driven construction and inference methodology of belief rule-base[J]. Journal of Computer Applications, 2014, 34(8): 2155-2160.

余瑞银杨隆浩傅仰耿. 数据驱动的置信规则库构建与推理方法[J]. 计算机应用, 2014, 34(8): 2155-2160.

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Data driven construction and inference methodology of belief rule-base

数据驱动的置信规则库构建与推理方法

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