A Deep Belief Network and Case Reasoning Based Decision Model for Emergency Rescue
The frequent occurrence of major public emergencies in China has caused significant human and economic losses. To carry out successful rescue operations in such emergencies, decisions need to be made as efficiently as possible. Using earthquakes as an example of a public emergency, this paper combin...
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| Veröffentlicht in: | International journal of computers, communications & control communications & control, 2020-06, Vol.15 (3) |
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| creator | Chang, Dan Fan, Rui Sun, Zitong |
| description | The frequent occurrence of major public emergencies in China has caused significant human and economic losses. To carry out successful rescue operations in such emergencies, decisions need to be made as efficiently as possible. Using earthquakes as an example of a public emergency, this paper combines the Deep Belief Network (DBN) and Case-Based Reasoning (CBR) models to improve the case representation and case retrieval steps in the decision-making process, then designs and constructs a decision-making model. The validity of the model is then verified by an example. The results of this study can be applied to maximize the efficiency of emergency rescue decisions. |
| doi_str_mv | 10.15837/ijccc.2020.3.3836 |
| format | Article |
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| ispartof | International journal of computers, communications & control, 2020-06, Vol.15 (3) |
| issn | 1841-9836 1841-9844 |
| language | eng |
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| source | DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | Belief networks Decision making Earthquakes Economic impact Emergencies Reasoning Rescue operations Seismic activity |
| title | A Deep Belief Network and Case Reasoning Based Decision Model for Emergency Rescue |
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