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- W4320067726 abstract "The field of Artificial Intelligence (AI) has noticeably developed in recent years. The literature includes a tremendous number of contributions proposed by worldwide researchers. These algorithms can be used for a variety of purposes such as classifications, clustering, and forecasting, to mention a few. The problem that researchers frequently face is the appropriateness of the algorithm they use for their data. Moreover, researchers usually benchmark their work with the literature, which also needs to select appropriate algorithms that fit their needs. Another problem that researchers face is that when developing a new algorithm or modify an existing they need to have extensive knowledge about algorithms. These issues may take a lot of time and effort that are consumed in exploring the literature. This research comes to provide a network model as a guide that gathers most of the AI available algorithms in the literature aiming to make it easier for researchers to understand AI algorithms. The proposed network model includes nodes and edges. Each node represents an AI algorithm and the edges are created among them when they have parameters in common. The findings show the efficiency of the proposed model in supporting researchers in selecting appropriate algorithms for their works. Finally, this work is considered novel since it collects most of the AI algorithms in a standalone model." @default.
- W4320067726 created "2023-02-12" @default.
- W4320067726 creator A5059129599 @default.
- W4320067726 creator A5067539302 @default.
- W4320067726 date "2022-08-31" @default.
- W4320067726 modified "2023-09-28" @default.
- W4320067726 title "A Novel Network Model for Artificial Intelligence Algorithms" @default.
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- W4320067726 doi "https://doi.org/10.1109/iccitm56309.2022.10032030" @default.
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