| dc.creator |
Ozkan, Kursad |
|
| dc.date |
2017-12-31T21:00:00Z |
|
| dc.date.accessioned |
2020-10-06T11:24:47Z |
|
| dc.date.available |
2020-10-06T11:24:47Z |
|
| dc.identifier |
d3c0087f-4728-450d-a1e8-84e0a4842a76 |
|
| dc.identifier |
10.26650/forestist.2018.340634 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/d3c0087f-4728-450d-a1e8-84e0a4842a76/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/72938 |
|
| dc.description |
The various diversity measures used to measure biodiversity include the Margalef index, McIntosh index, Simpson index, Brillouin index, and Shannon entropy. Of these measures, the most popular is Shannon entropy (H). In this study, with respect to measuring biodiversity, we compare Shannon entropy-the essential aspect of Information theory-with the Deng and Improved Deng entropies, as proposed within the framework of the Dempster-Shafer evidential theory. To do so, we used a hypothetical dataset of three complexes. Based on this hypothetic data, ecologically speaking, we obtained the most reasonable result from the improved Deng entropy. There are two reasons for this result: 1) Mass functions cannot be used when computing the Shannon entropy, and 2) Deng entropy does not take into consideration the scale of the frame of discernment. |
|
| dc.language |
eng |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
Comparing Shannon entropy with Deng entropy and improved Deng entropy for measuring biodiversity when a priori data is not clear |
|
| dc.type |
info:eu-repo/semantics/article |
|