Name
Title | ||
|---|---|---|
A Model for Hidden Behavior Prediction of Complex Systems Based on Belief Rule Base and Power Set. |
Abstract | ||
|---|---|---|
It is important to predict the hidden behavior of a complex system. In the existing models for predicting the hidden behavior, the hidden belief rule base (HBRB) is an effective model which can use qualitative knowledge and quantitative data. However, the frame of discernment (FoD) of HBRB which is composed of some states or propositions and the universal set including all states or propositions i... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TSMC.2017.2665880 | IEEE Transactions on Systems, Man, and Cybernetics: Systems |
Keywords | Field | DocType |
Predictive models,Forecasting,Hidden Markov models,Security,Communication networks,Uncertainty,Inference algorithms | Computer science,Inference,Network security,Evolution strategy,Artificial intelligence,Evidential reasoning approach,Power set,Hidden Markov model,Machine learning,Universal set | Journal |
Volume | Issue | ISSN |
48 | 9 | 2168-2216 |
Citations | PageRank | References |
10 | 0.48 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| ZhiJie Zhou | 1 | 479 | 37.36 |
| Guan-Yu Hu | 2 | 19 | 1.27 |
| Bang-Cheng Zhang | 3 | 61 | 9.39 |
| C. H. Chang | 4 | 428 | 36.69 |
| Zhi-Guo Zhou | 5 | 111 | 9.47 |
| peili qiao | 6 | 16 | 3.28 |