stands for Digital Object Identifier
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.
Using DOI as a persistent link
To create a persistent link, add「http://dx.doi.org/」
before a DOI.
For instance, if the DOI of an article is 10.5297/ser.1201.002 , you can link persistently to the article by entering the following link in your browser: http://dx.doi.org/ 10.5297/ser.1201.002 。
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.
Cite a document with DOI
When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.
DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI Registration （ doi.airiti.com ） 。
黃韻如 , Masters Advisor：林國峰
繁體中文 DOI： 10.6342/NTU201902265
- 1. Abella, E. A. C., Van Westen, C. J., 2008. Qualitative landslide susceptibility assessment by multicriteria analysis: a case study from San Antonio del Sur, Guantánamo, Cuba. Geomorphology 94(3-4), 453-466.
- 2. Alfieri, L., Salamon, P., Bianchi, A., Neal, J., Bates, P., Feyen, L., 2014. Advances in pan‐European flood hazard mapping. Hydrological processes 28(13), 4067-4077.
- 3. Al-Abadi, A. M., 2018. Mapping flood susceptibility in an arid region of southern Iraq using ensemble machine learning classifiers: a comparative study. Arabian Journal of Geosciences 11(9), 218.
- 4. Bui, D. T., Tuan, T. A., Klempe, H., Pradhan, B., Revhaug, I., 2016. Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree. Landslides 13(2), 361-378.
- 5. Breiman, L., Friedman, J.H., Olsen, R.A., Stone, C.J., 1984. Classification and regression trees. Wadsworth and Brooks, New York, USA.
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