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Human operators are vital in safely operating complex systems, such as nuclear power plants (NPPs). In order to account for the role of the human, HRA experts have developed a variety of methods primarily targeting the quantitative dimension of human behaviour, with limited focus on the qualitative. The most recent shift has been towards Machine Learning (ML)-based methods for predicting HEPs. Prominent among these new methods are Logistic Regression (LR) and Bayesian Networks (BN). Amongst ML methods, Artificial Neural Networks (ANN) are also a good candidate model but have not been adequately explored in HEP evaluation. This article presents a comparative analysis of the above three approaches. The results indicate that ANN based models can replicate the qualitative HRA in their HEP predictions. Therefore, if qualitatively appropriate HRA data is available, then ANN-based models, utilizing operator performance data maybe a good alternative for HEP evaluation. The comparative scheme developed in this article can serve as the basis for future comparison amongst methods that employ an amalgamation of qualitative and quantitative methods in HRA.<\/jats:p>","DOI":"10.1007\/s13198-025-02960-9","type":"journal-article","created":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T06:19:31Z","timestamp":1759817971000},"page":"166-191","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine learning based predictive model to enhance human reliability analysis for risk assessment of nuclear reactors"],"prefix":"10.1007","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4494-421X","authenticated-orcid":false,"given":"Vipul","family":"Garg","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4460-7341","authenticated-orcid":false,"given":"Gopika","family":"Vinod","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3003-4098","authenticated-orcid":false,"given":"Vivek","family":"Kant","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,7]]},"reference":[{"key":"2960_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2020.107043","volume":"202","author":"S Abrishami","year":"2020","unstructured":"Abrishami S, Khakzad N, Hosseini SM (2020a) A data-based comparison of BN-HRA models in assessing human error probability: an offshore evacuation case study. 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All the participants who participated in the conduction of HRA experiments in this study are nuclear industry professionals. HRA data was collected as a part of training program aimed to enhance their skills and knowledge, which is a routine\/regular practice in the nuclear industry. This is an on-going activity and prior institutional approval is available for the same.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human and animal rights"}},{"value":"Prior informed consent was taken from all the participants before conduction of HRA experiments and all methods were carried out in accordance with the relevant guidelines and regulations.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"No authors have conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}