scholarly journals Circuit Tolerance Design Using Belief Rule Base

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Xiao-Bin Xu ◽  
Zheng Liu ◽  
Yu-Wang Chen ◽  
Dong-Ling Xu ◽  
Cheng-Lin Wen
Keyword(s):  
High Speed ◽  
Nonlinear Modeling ◽  
Optimization Method ◽  
Quantitative Information ◽  
Rule Base ◽  
Nonlinear Relationship ◽  
Highly Nonlinear ◽  
Belief Rule Base ◽  
Feasibility Region ◽  
Brb System

A belief rule-based (BRB) system provides a generic nonlinear modeling and inference mechanism. It is capable of modeling complex causal relationships by utilizing both quantitative information and qualitative knowledge. In this paper, a BRB system is firstly developed to model the highly nonlinear relationship between circuit component parameters and the performance of the circuit by utilizing available knowledge from circuit simulations and circuit designers. By using rule inference in the BRB system and clustering analysis, the acceptability regions of the component parameters can be separated from the value domains of the component parameters. Using the established nonlinear relationship represented by the BRB system, an optimization method is then proposed to seek the optimal feasibility region in the acceptability regions so that the volume of the tolerance region of the component parameters can be maximized. The effectiveness of the proposed methodology is demonstrated through two typical numerical examples of the nonlinear performance functions with nonconvex and disconnected acceptability regions and high-dimensional input parameters and a real-world application in the parameter design of a track circuit for Chinese high-speed railway.

scholarly journals An Effective Soft-Sensor Method Based on Belief-Rule-Base and Differential Evolution for Tipping Paper Permeability Measurement

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Rong Hu ◽  
Qinli Zhang ◽  
Bin Qian ◽  
Leilei Chang ◽  
Zhijie Zhou
Keyword(s):  
Solution Space ◽  
Soft Sensor ◽  
Rule Base ◽  
Permeability Measurement ◽  
Measuring Device ◽  
De Algorithm ◽  
Mutation Strategy ◽  
Belief Rule Base ◽  
Optimization Parameters ◽  
Brb System

The current paper presents a soft-sensor method based on belief-rule-base (BRB) system for solving the problem of tipping paper permeability measurement in the tobacco industry. Firstly, BRB is utilized to establish a model between the feature variables in the tipping paper image and the corresponding paper permeability obtained by the traditional measuring device. Unlike the traditional case of BRB, this paper adds the output attribute as the optimization parameters. In this way, the feasible solution space can be enlarged to obtain an effective BRB model. Second, in order to find the reasonable parameters of BRB in a complex nonconvex solution space, an enhanced differential evolutionary (DE) algorithm is developed to train BRB, which not only embeds a simplex method to stress the balance between the global and local search but also designs a perturbation operation and an adaptively selected mutation strategy to maintain the diversity of search direction. The test results and comparisons based on the data collected from a cigarette factory in China show that the presented method is effective and robust.

scholarly journals An internet of things belief rule base smart system to predict earthquake

2021 ◽  
Vol 10 (2) ◽  
pp. 149
Author(s):  
Md. Mahashin Mia ◽  
Abdullah Al Hasan ◽  
Rahman Atiqur ◽  
Rashed Mustafa
Keyword(s):  
Expert System ◽  
Internet Of Things ◽  
Animal Behavior ◽  
Fuzzy System ◽  
Rule Base ◽  
Smart System ◽  
Attribute Weight ◽  
Belief Rule Base ◽  
Probable Occurrence ◽  
Brb System

<p><span>An intelligent belief rule base (BRB) based system with internet of things (IoT) integration can evaluate earthquake prediction (EP). This ingenious and rational system can predict earthquake by aggregating changed animal behavior combined with environmental and chemical changes which are taken as real time inputs from sensors. The BRB expert system blends knowledge demonstration criterion like attribute weight, rule weight, belief degree. The intelligent BRB system with IoT predicts the probable occurrence of the earthquake in a region based on the sign and symptoms culled by the persistent sensors. The final result taken from Intelligent BRB system with IoT integration is compared with expert and fuzzy-based system. The projected method gives a better prediction than the up-to-date expert system and fuzzy system</span></p>

scholarly journals A BRB Based Fault Prediction Method of Complex Electromechanical Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Bangcheng Zhang ◽  
Xiaojing Yin ◽  
Zhanli Wang ◽  
Xiaoxia Han ◽  
Zhi Gao
Keyword(s):  
Optimal Algorithm ◽  
Quantitative Information ◽  
Numerical Control ◽  
Fault Prediction ◽  
Rule Base ◽  
Cnc Milling ◽  
Electromechanical Systems ◽  
Belief Rule Base ◽  
Qualitative Knowledge ◽  
Complex Electromechanical Systems

Fault prediction is an effective and important approach to improve the reliability and reduce the risk of accidents for complex electromechanical systems. In order to use the quantitative information and qualitative knowledge efficiently to predict the fault, a new model is proposed on the basis of belief rule base (BRB). Moreover, an evidential reasoning (ER) based optimal algorithm is developed to train the fault prediction model. The screw failure in computer numerical control (CNC) milling machine servo system is taken as an example and the fault prediction results show that the proposed method can predict the behavior of the system accurately with combining qualitative knowledge and some quantitative information.

scholarly journals Reliability Assessment Model for Industrial Control System Based on Belief Rule Base

2019 ◽  
Vol 14 (3) ◽  
pp. 419-436 ◽  
Author(s):  
Yuhe Wang ◽  
Peili Qiao ◽  
Zhiyong Luo ◽  
Guanglu Sun ◽  
Guangze Wang
Keyword(s):  
Control System ◽  
Reliability Assessment ◽  
Quantitative Information ◽  
Assessment Method ◽  
Assessment Model ◽  
Rule Base ◽  
Industrial Control System ◽  
Industrial Control ◽  
Proposed Model ◽  
Belief Rule Base

This paper establishes a novel reliability assessment method for industrial control system (ICS). Firstly, the qualitative and quantitative information were integrated by evidential reasoning(ER) rule. Then, an ICS reliability assessment model was constructed based on belief rule base (BRB). In this way, both expert experience and historical data were fully utilized in the assessment. The model consists of two parts, a fault assessment model and a security assessment model. In addition, the initial parameters were optimized by covariance matrix adaptation evolution strategy (CMA-ES) algorithm, making the proposed model in line with the actual situation. Finally, the proposed model was compared with two other popular prediction methods through case study. The results show that the proposed method is reliable, efficient and accurate, laying a solid basis for reliability assessment of complex ICSs.

A safety assessment model based on belief rule base with new optimization method

2020 ◽  
Vol 203 ◽  
pp. 107055 ◽  
Author(s):  
Zhichao Feng ◽  
Zhijie Zhou ◽  
Changhua Hu ◽  
Xiaojun Ban ◽  
Guanyu Hu
Keyword(s):  
Safety Assessment ◽  
Optimization Method ◽  
Assessment Model ◽  
Rule Base ◽  
Model Based ◽  
Belief Rule Base

scholarly journals Health Status Prediction Based on Belief Rule Base for High-Speed Train Running Gear System

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 4145-4159 ◽  
Author(s):  
Chao Cheng ◽  
Jiuhe Wang ◽  
Wanxiu Teng ◽  
Mingliang Gao ◽  
Bangcheng Zhang ◽  
...  
Keyword(s):  
Health Status ◽  
High Speed ◽  
Gear System ◽  
Rule Base ◽  
High Speed Train ◽  
Belief Rule Base

A model for online failure prognosis subject to two failure modes based on belief rule base and semi-quantitative information

2014 ◽  
Vol 70 ◽  
pp. 221-230 ◽  
Author(s):  
Zhi-Jie Zhou ◽  
Chang-Hua Hu ◽  
Xiao-Xia Han ◽  
Hua-Feng He ◽  
Xiao-Dong Ling ◽  
...  
Keyword(s):  
Failure Modes ◽  
Quantitative Information ◽  
Rule Base ◽  
Belief Rule Base ◽  
Failure Prognosis

High Speed Information Network Planning using Stochastic Optimization Method

2013 ◽  
Author(s):  
Ki-Sang Song ◽  
Arun K. Somani
Keyword(s):  
Stochastic Optimization ◽  
Network Design ◽  
Multimedia Information ◽  
High Speed ◽  
Minimum Cost ◽  
Optimization Method ◽  
Multimedia Communication ◽  
Network Design Problem ◽  
Information Network ◽  
Traffic Characteristics

From the 1994 CAIS Conference: The Information Industry in Transition McGill University, Montreal, Quebec. May 25 - 27, 1994.Broadband integrated services digital network (B-ISDN) based on the asynchronous transmission mode (ATM) is becoming reality to provide high speed, multi bit rate multimedia communications. Multimedia communication network has to support voice, video and data traffics that have different traffic characteristics, delay sensitive or loss sensitive features have to be accounted for designing high speed multimedia information networks. In this paper, we formulate the network design problem by considering the multimedia communication requirements. A high speed multimedia information network design alogrithm is developed using a stochastic optimization method to find good solutions which meet the Quality of Service (QoS) requirement of each traffic class with minimum cost.

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