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 ） 。
詹淳旭 , Masters Advisor：黃博滄
- Abou-El-Hossein, K. A., & Yahya, Z. (2005). High-speed end-milling of AISI 304 stainless steels using new geometrically developed carbide inserts. Journal of Materials Processing Technology, 162–163(0), 596-602.
- Ahilan, C., Kumanan, S., Sivakumaran, N., & Edwin Raja Dhas, J. (2013). Modeling and prediction of machining quality in CNC turning process using intelligent hybrid decision making tools. Applied Soft Computing, 13(3), 1543-1551.
- Ak, R., Li, Y., Vitelli, V., Zio, E., López Droguett, E., & Magno Couto Jacinto, C. (2013). NSGA-II-trained neural network approach to the estimation of prediction intervals of scale deposition rate in oil & gas equipment. Expert Systems with Applications, 40(4), 1205-1212.
- Asadi, S., Hadavandi, E., Mehmanpazir, F., & Nakhostin, M. M. (2012). Hybridization of evolutionary Levenberg–Marquardt neural networks and data pre-processing for stock market prediction. Knowledge-Based Systems, 35(0), 245-258.
- Briza, A. C., & Naval Jr, P. C. (2011). Stock trading system based on the multi-objective particle swarm optimization of technical indicators on end-of-day market data. Applied Soft Computing, 11(1), 1191-1201.
The cart has had several articles, so do you want to clear it, or add together to the cart?