Research project evaluation and selection: an evidential reasoning rule-based method for aggregating peer review information with reliabilities
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DOI: 10.1007/s11192-015-1770-8
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Cited by:
- Li, Heyang & Wu, Meijun & Wang, Yougui & Zeng, An, 2022. "Bibliographic coupling networks reveal the advantage of diversification in scientific projects," Journal of Informetrics, Elsevier, vol. 16(3).
- Simon Hirzel & Tim Hettesheimer & Peter Viebahn & Manfred Fischedick, 2018. "A Decision Support System for Public Funding of Experimental Development in Energy Research," Energies, MDPI, vol. 11(6), pages 1-18, May.
- Zhu, Weidong & Zhang, Tianjiao & Wu, Yong & Li, Shaorong & Li, Zhimin, 2022. "Research on optimization of an enterprise financial risk early warning method based on the DS-RF model," International Review of Financial Analysis, Elsevier, vol. 81(C).
- Fernandez Martinez, Roberto & Lostado Lorza, Ruben & Santos Delgado, Ana Alexandra & Piedra, Nelson, 2021. "Use of classification trees and rule-based models to optimize the funding assignment to research projects: A case study of UTPL," Journal of Informetrics, Elsevier, vol. 15(1).
- Fang Liu & Wei-dong Zhu & Yu-wang Chen & Dong-ling Xu & Jian-bo Yang, 2017. "Evaluation, ranking and selection of R&D projects by multiple experts: an evidential reasoning rule based approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1501-1519, June.
- Weidong Zhu & Shaorong Li & Hongtao Zhang & Tianjiao Zhang & Zhimin Li, 2022. "Evaluation of scientific research projects on the basis of evidential reasoning approach under the perspective of expert reliability," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 275-298, January.
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Keywords
Research project evaluation and selection; Evidential reasoning; Reliability; Confusion matrix;All these keywords.
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