University admission process: a prescriptive analytics approach-Reference-Cited by-同舟云学术

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University admission process: a prescriptive analytics approach

Published:2022-08-19 Issue:1 Volume:56 Page:233-256
ISSN:0269-2821
Container-title:Artificial Intelligence Review
language:en
Short-container-title:Artif Intell Rev

Author:

Kiaghadi Mohammadreza,Hoseinpour Pooya

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Link

https://link.springer.com/content/pdf/10.1007/s10462-022-10171-y.pdf

Reference54 articles.

1. Abbas AE (2010) Constructing multiattribute utility functions for decision analysis. In: Risk and optimization in an uncertain world. In: INFORMS, pp 62–98

2. Achabal DD, McIntyre SH, Smith SA, Kalyanam K (2000) A decision support system for vendor managed inventory. J Retail 76(4):430–454

3. Acharya MS, Armaan A, Antony AS (2019) A comparison of regression models for prediction of graduate admissions. In: 2019 International conference on computational intelligence in data science (ICCIDS). IEEE, pp 1–5.

4. Adekitan AI, Noma-Osaghae E (2019) Data mining approach to predicting the performance of first year student in a university using the admission requirements. Educ Inf Technol 24(2):1527–1543

5. Albawi S, Mohammed TA, Al-Zawi S (2017) Understanding of a convolutional neural network. In 2017 International conference on engineering and technology. IEEE, pp 1–6

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