Nijat Mehdiyev

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

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization.

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

Cogn. Comput., September, 2024

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

Kamala Aliyeva, Nijat Mehdiyev

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.

Nijat Mehdiyev, Lea Mayer, Johannes Lahann, Peter Fettke

Expert Syst. J. Knowl. Eng., February, 2024

2023

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

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

CoRR, 2023

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

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

CoRR, 2023

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

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

CoRR, 2023

Explainable Artificial Intelligence Meets Uncertainty Quantification for Predictive Process Monitoring.

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

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.

Nijat Mehdiyev, Constantin Houy, Oliver Gutermuth, Lea Mayer, Peter Fettke

Proceedings of the Innovation durch Informationssysteme, 2021

Local Post-Hoc Explanations for predictive Process Monitoring in manufacturing.

Nijat Mehdiyev, Peter Fettke

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.

Nijat Mehdiyev, Peter Fettke

CoRR, 2020

A Novel Business Process Prediction Model Using a Deep Learning Method.

Nijat Mehdiyev, Joerg Evermann, Peter Fettke

Bus. Inf. Syst. Eng., 2020

Explainable Process Predictions (xPP): A Holistic Framework and Applications (Extended Abstract).

Nijat Mehdiyev

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.

Nijat Mehdiyev, Peter Fettke

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.

Jana-Rebecca Rehse, Nijat Mehdiyev, Peter Fettke

Künstliche Intell., 2019

Substitution of hazardous chemical substances using Deep Learning and t-SNE.

Patrick Lübbecke, Nijat Mehdiyev, Peter Fettke

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.

Nijat Mehdiyev, Joerg Evermann, Peter Fettke

Proceedings of the 19th IEEE Conference on Business Informatics, 2017

iPRODICT - Intelligent Process Prediction based on Big Data Analytics.

Nijat Mehdiyev, Andreas Emrich, Björn P. Stahmer, Peter Fettke, Peter Loos

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.

Nijat Mehdiyev, Julian Krumeich, Dirk Werth, Peter Loos

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.

Julian Krumeich, Nijat Mehdiyev, Dirk Werth, Peter Loos

Proceedings of the Advances in Conceptual Modeling, 2015

Determination of Rule Patterns in Complex Event Processing Using Machine Learning Techniques.

Nijat Mehdiyev, Julian Krumeich, David Enke, Dirk Werth, Peter Loos

Proceedings of the Complex Adaptive Systems 2015 Conference, San Jose, 2015

Sensor event mining with hybrid ensemble learning and evolutionary feature subset selection model.

Nijat Mehdiyev, Julian Krumeich, Dirk Werth, Peter Loos

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.

Nijat Mehdiyev, David Enke

Int. J. Gen. Syst., 2014

A Hybrid Neuro-fuzzy Model to Forecast Inflation.

David Enke, Nijat Mehdiyev

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.

David Enke, Nijat Mehdiyev

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.

David Enke, Nijat Mehdiyev

Proceedings of the Complex Adaptive Systems 2013 Conference, 2013

2012

A New Hybrid Approach For Forecasting Interest Rates.

David Enke, Nijat Mehdiyev

Proceedings of the Complex Adaptive Systems 2012 Conference, 2012

2011

Stock Market Prediction with Multiple Regression, Fuzzy Type-2 Clustering and Neural Networks.

David Enke, Manfred Grauer, Nijat Mehdiyev

Proceedings of the Complex Adaptive Systems 2011 Conference, 2011