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

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 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

Hidden behavior prediction of complex system based on time-delay belief rule base forecasting model

2020 ◽  
Vol 203 ◽  
pp. 106147
Author(s):  
Guan-Yu Hu ◽  
Zhi-Jie Zhou ◽  
ChangHua Hu ◽  
Bang-Cheng Zhang ◽  
Zhi-Guo Zhou ◽  
...  
Keyword(s):  
Complex System ◽  
Time Delay ◽  
Forecasting Model ◽  
Rule Base ◽  
Behavior Prediction ◽  
Belief Rule Base

scholarly journals A Fusion Prognostic Method for Remaining Useful Life Prediction Based on an Extended Belief Rule Base and Particle Filters

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Bincheng Wen ◽  
Mingqing Xiao ◽  
Guanghao Wang ◽  
Zhao Yang ◽  
Jianfeng Li ◽  
...  
Keyword(s):  
Life Prediction ◽  
Particle Filters ◽  
Remaining Useful Life ◽  
Rule Base ◽  
Belief Rule Base ◽  
Useful Life

A new approximate belief rule base expert system for complex system modelling

2021 ◽  
pp. 113558
Author(s):  
You Cao ◽  
Zhijie Zhou ◽  
Changhua Hu ◽  
Shuaiwen Tang ◽  
Jie Wang
Keyword(s):  
Complex System ◽  
Expert System ◽  
Rule Base ◽  
System Modelling ◽  
Belief Rule Base

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 An Evolutionary Belief Rule-Based Clinical Decision Support System to Predict COVID-19 Severity under Uncertainty

2021 ◽  
Vol 11 (13) ◽  
pp. 5810
Author(s):  
Faisal Ahmed ◽  
Mohammad Shahadat Hossain ◽  
Raihan Ul Islam ◽  
Karl Andersson
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Experimental Result ◽  
Rule Base ◽  
Rule Based ◽  
Belief Rule Base

Accurate and rapid identification of the severe and non-severe COVID-19 patients is necessary for reducing the risk of overloading the hospitals, effective hospital resource utilization, and minimizing the mortality rate in the pandemic. A conjunctive belief rule-based clinical decision support system is proposed in this paper to identify critical and non-critical COVID-19 patients in hospitals using only three blood test markers. The experts’ knowledge of COVID-19 is encoded in the form of belief rules in the proposed method. To fine-tune the initial belief rules provided by COVID-19 experts using the real patient’s data, a modified differential evolution algorithm that can solve the constraint optimization problem of the belief rule base is also proposed in this paper. Several experiments are performed using 485 COVID-19 patients’ data to evaluate the effectiveness of the proposed system. Experimental result shows that, after optimization, the conjunctive belief rule-based system achieved the accuracy, sensitivity, and specificity of 0.954, 0.923, and 0.959, respectively, while for disjunctive belief rule base, they are 0.927, 0.769, and 0.948. Moreover, with a 98.85% AUC value, our proposed method shows superior performance than the four traditional machine learning algorithms: LR, SVM, DT, and ANN. All these results validate the effectiveness of our proposed method. The proposed system will help the hospital authorities to identify severe and non-severe COVID-19 patients and adopt optimal treatment plans in pandemic situations.

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