Name
Abstract | ||
|---|---|---|
In this article, we consider the problem of construction of Probabilistic Boolean Networks (PBNs). Previous works have shown that Boolean Networks (BNs) and PBNs have many potential applications in modeling genetic regulatory networks and credit default data. A PBN can be considered as a Markov chain process and the construction of a PBN is an inverse problem. Given the transition probability matrix of the PBN, we try to find a set of BNs with probabilities constituting the given PBN. We propose a revised estimation method based on entropy approach to estimate the model parameters. Practical real credit default data are employed to demonstrate our proposed method. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CSO.2014.11 | CSO |
Keywords | Field | DocType |
entropy approach,genetic regulatory networks,parameter estimation,boolean networks,genetics,boolean networks, probabilistic boolean networks, inverse problem, transition probability matrix,credit default data,matrix algebra,estimation theory,inverse problems,probabilistic boolean networks,markov processes,pbn,markov chain process,transition probability matrix,inverse problem,revised estimation method,entropy,model parameter estimation,boolean algebra,network theory (graphs),probability,probabilistic logic,boolean functions,mathematical model | Boolean function,Boolean network,Credit default swap,Mathematical optimization,Markov process,Stochastic matrix,Computer science,Markov chain,Artificial intelligence,Inverse problem,Probabilistic logic,Machine learning | Conference |
ISSN | Citations | PageRank |
2158-799X | 4 | 0.38 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ruochen Liang | 1 | 4 | 0.38 |
| Yushan Qiu | 2 | 20 | 6.28 |
| Wai-Ki Ching | 3 | 683 | 78.66 |