Nijat Mehdiyev

Orcid: 0000-0001-7899-1017

According to our database1, Nijat Mehdiyev authored at least 27 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization.
Cogn. Comput., September, 2024

Uncertainty-aware multi-criteria decision analysis for evaluation of explainable artificial intelligence methods: A use case from the healthcare domain.
Inf. Sci., February, 2024

Deep learning-based clustering of processes and their visual exploration: An industry 4.0 use case for small, medium-sized enterprises.
Expert Syst. J. Knowl. Eng., February, 2024

2023
Interpretable and Explainable Machine Learning Methods for Predictive Process Monitoring: A Systematic Literature Review.
CoRR, 2023

Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective.
CoRR, 2023

Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring.
CoRR, 2023

Explainable Artificial Intelligence Meets Uncertainty Quantification for Predictive Process Monitoring.
Proceedings of the 2nd International Workshop on Process Management in the AI Era (PMAI 2023) co-located with 31st International Joint Conference on Artificial Intelligence (IJCAI 2023), 2023

2021
Explainable Artificial Intelligence (XAI) Supporting Public Administration Processes - On the Potential of XAI in Tax Audit Processes.
Proceedings of the Innovation durch Informationssysteme, 2021

Local Post-Hoc Explanations for predictive Process Monitoring in manufacturing.
Proceedings of the 29th European Conference on Information Systems, 2021

2020
Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring.
CoRR, 2020

A Novel Business Process Prediction Model Using a Deep Learning Method.
Bus. Inf. Syst. Eng., 2020

Explainable Process Predictions (xPP): A Holistic Framework and Applications (Extended Abstract).
Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining (ICPM 2020), 2020

Prescriptive Process Analytics with Deep Learning and Explainable Artificial Intelligence.
Proceedings of the 28th European Conference on Information Systems, 2020

2019
Towards Explainable Process Predictions for Industry 4.0 in the DFKI-Smart-Lego-Factory.
Künstliche Intell., 2019

Substitution of hazardous chemical substances using Deep Learning and t-SNE.
Proceedings of the Human Practice. Digital Ecologies. Our Future. 14. Internationale Tagung Wirtschaftsinformatik (WI 2019), 2019

2017
A Multi-stage Deep Learning Approach for Business Process Event Prediction.
Proceedings of the 19th IEEE Conference on Business Informatics, 2017

iPRODICT - Intelligent Process Prediction based on Big Data Analytics.
Proceedings of the BPM 2017 Industry Track co-located with the 15th International Conference on Business Process Management (BPM 2017), 2017

2016
Determination of Event Patterns for Complex Event Processing Using Fuzzy Unordered Rule Induction Algorithm with Multi-objective Evolutionary Feature Subset Selection.
Proceedings of the 49th Hawaii International Conference on System Sciences, 2016

2015
Towards an Extended Metamodel of Event-Driven Process Chains to Model Complex Event Patterns.
Proceedings of the Advances in Conceptual Modeling, 2015

Determination of Rule Patterns in Complex Event Processing Using Machine Learning Techniques.
Proceedings of the Complex Adaptive Systems 2015 Conference, San Jose, 2015

Sensor event mining with hybrid ensemble learning and evolutionary feature subset selection model.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
Interest rate prediction: a neuro-hybrid approach with data preprocessing.
Int. J. Gen. Syst., 2014

A Hybrid Neuro-fuzzy Model to Forecast Inflation.
Proceedings of the Complex Adaptive Systems 2014 Conference, 2014

2013
Stock Market Prediction Using a Combination of Stepwise Regression Analysis, Differential Evolution-based Fuzzy Clustering, and a Fuzzy Inference Neural Network.
Intell. Autom. Soft Comput., 2013

Type-2 Fuzzy Clustering and a Type-2 Fuzzy Inference Neural Network for the Prediction of Short-term Interest Rates.
Proceedings of the Complex Adaptive Systems 2013 Conference, 2013

2012
A New Hybrid Approach For Forecasting Interest Rates.
Proceedings of the Complex Adaptive Systems 2012 Conference, 2012

2011
Stock Market Prediction with Multiple Regression, Fuzzy Type-2 Clustering and Neural Networks.
Proceedings of the Complex Adaptive Systems 2011 Conference, 2011


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