A New Prediction Model Based on Belief Rule Base for System's Behavior Prediction

2011 ◽  
Vol 19 (4) ◽  
pp. 636-651 ◽  
Author(s):  
Xiao-Sheng Si ◽  
Chang-Hua Hu ◽  
Jian-Bo Yang ◽  
Zhi-Jie Zhou
Keyword(s):  
Prediction Model ◽  
Rule Base ◽  
Behavior Prediction ◽  
Model Based ◽  
Belief Rule Base

A hidden fault prediction model based on the belief rule base with power set and considering attribute reliability

2019 ◽  
Vol 62 (10) ◽  
Author(s):  
Zhijie Zhou ◽  
Zhichao Feng ◽  
Changhua Hu ◽  
Xiaoxia Han ◽  
Zhiguo Zhou ◽  
...  
Keyword(s):  
Prediction Model ◽  
Fault Prediction ◽  
Rule Base ◽  
Model Based ◽  
Belief Rule Base ◽  
Power Set ◽  
Hidden Fault

New health-state assessment model based on belief rule base with interpretability

2021 ◽  
Vol 64 (7) ◽  
Author(s):  
Zhijie Zhou ◽  
You Cao ◽  
Guanyu Hu ◽  
Youmin Zhang ◽  
Shuaiwen Tang ◽  
...  
Keyword(s):  
State Assessment ◽  
Assessment Model ◽  
Rule Base ◽  
Health State ◽  
Model Based ◽  
Belief Rule Base

scholarly journals Health State Prediction of Aero-Engine Gas Path System Considering Multiple Working Conditions Based on Time Domain Analysis and Belief Rule Base

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 26
Author(s):  
Xiaojing Yin ◽  
Guangxu Shi ◽  
Shouxin Peng ◽  
Yu Zhang ◽  
Bangcheng Zhang ◽  
...  
Keyword(s):  
Prediction Model ◽  
Working Conditions ◽  
Time Domain ◽  
Monitoring Data ◽  
Rule Base ◽  
Health State ◽  
Health States ◽  
State Prediction ◽  
Belief Rule Base ◽  
Path System

The gas path system is an important part of an aero-engine, whose health states can affect the security of the airplane. During the process of aircraft operation, the gas path system will have different working conditions over time, owing to the change of control parameters. However, the different working conditions which change the symmetry of the system will affect parameters of the health state prediction model for the gas path system. The symmetry of the system will also change. Therefore, it is important to consider the influence of variable working conditions when predicting the health states of gas path system. The accuracy of the health state prediction results of the gas path system will be low if the same evaluation standard is used for different working conditions. In addition, the monitoring data of the gas path system’s health state feature quantity is huge while the fault data which can reflect the health states of the gas path system are poor. Thus, it is difficult to establish a health state prediction model only by using the monitoring data of the gas path system. In order to avoid problems, this paper proposes a health state prediction model considering multiple working conditions based on time domain analysis and a belief rule base. First, working condition is divided by using time domain characteristics. Then, a belief rule base (BRB) theory-based health state prediction model is built, which can fuse expert knowledge and fault monitoring data to improve modeling accuracy. The reference value of the feature is given by the fuzzy C-means algorithm in a model. To decrease the uncertainty of expert knowledge, the covariance matrix adaptive evolution strategy (CMA-ES) is used as the optimization algorithm. Finally, a NASA public dataset without labels is used to verify the proposed health state model. The results show that the proposed health prediction model of a gas path system can accurately realize health state prediction under multiple working conditions.

scholarly journals A new health prediction model for a sensor network based on belief rule base with attribute reliability

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shaohua Li ◽  
Jingying Feng ◽  
Wei He ◽  
Ruihua Qi ◽  
He Guo
Keyword(s):  
Prediction Model ◽  
Sensor Network ◽  
Expert Knowledge ◽  
Average Distance ◽  
Rule Base ◽  
Distance Method ◽  
Oil Storage ◽  
Belief Rule Base ◽  
Qualitative Knowledge ◽  
Monitoring Information

AbstractHealth prediction plays an essential role in improving the reliability of a sensor network by guiding the network maintenance. However, affected by interference factors in the real operational environment, the reliability of the monitoring information about the sensor network tends to decline, which affects the health prediction accuracy. Furthermore, the lack of monitoring information and high complexity of the network increase the difficulty of health prediction. To solve these three problems, this paper proposes a new sensor network health prediction model based on the belief rule base model with attribute reliability (BRB-r). The BRB-r model is an expert system that fully considers the qualitative knowledge and quantitative data of the sensor network. In addition, it can address the fuzziness and nondeterminacy of this qualitative knowledge. In the new model, the unreliable monitoring information of the sensor network is handled by the attribute reliability mechanism. The reliability of the sensor is calculated by the average distance method. Due to the effect of the fuzziness and nondeterminacy of expert knowledge, the health status of the sensor network cannot be accurately estimated by the initial health prediction model. Consequently, the optimization model for the health prediction model is established. Finally, a case study regarding a sensor network for oil storage tanks is conducted, and the validity of this method is demonstrated.

A Model for Hidden Behavior Prediction of Complex Systems Based on Belief Rule Base and Power Set

2018 ◽  
Vol 48 (9) ◽  
pp. 1649-1655 ◽  
Author(s):  
Zhi-Jie Zhou ◽  
Guan-Yu Hu ◽  
Bang-Cheng Zhang ◽  
Chang-Hua Hu ◽  
Zhi-Guo Zhou ◽  
...  
Keyword(s):  
Complex Systems ◽  
Rule Base ◽  
Behavior Prediction ◽  
Belief Rule Base ◽  
Power Set

Aeronautical relay health state assessment model based on belief rule base with attribute reliability

2020 ◽  
Vol 197 ◽  
pp. 105869 ◽  
Author(s):  
Zhijie Zhou ◽  
Zhichao Feng ◽  
Changhua Hu ◽  
Guanyu Hu ◽  
Wei He ◽  
...  
Keyword(s):  
State Assessment ◽  
Assessment Model ◽  
Rule Base ◽  
Health State ◽  
Model Based ◽  
Belief Rule Base

Hidden Behavior Prediction of Complex Systems Under Testing Influence Based on Semiquantitative Information and Belief Rule Base

2015 ◽  
Vol 23 (6) ◽  
pp. 2371-2386 ◽  
Author(s):  
Zhi-Jie Zhou ◽  
Chang-Hua Hu ◽  
Guan-Yu Hu ◽  
Xiao-Xia Han ◽  
Bang-Cheng Zhang ◽  
...  
Keyword(s):  
Complex Systems ◽  
Rule Base ◽  
Behavior Prediction ◽  
Belief Rule Base

A user behavior prediction model based on parallel neural network and k-nearest neighbor algorithms

2017 ◽  
Vol 20 (2) ◽  
pp. 1703-1715 ◽  
Author(s):  
Gaowei Xu ◽  
Carl Shen ◽  
Min Liu ◽  
Feng Zhang ◽  
Weiming Shen
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Nearest Neighbor ◽  
User Behavior ◽  
Behavior Prediction ◽  
K Nearest Neighbor ◽  
Model Based
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