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Nijat Mehdiyev
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2020 – today
- 2024
- [j7]Nijat Mehdiyev, Maxim Majlatow, Peter Fettke:
Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization. Cogn. Comput. 16(5): 2674-2700 (2024) - [j6]Nijat Mehdiyev
, Lea Mayer, Johannes Lahann, Peter Fettke:
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. 41(2) (2024) - [j5]Kamala Aliyeva
Uncertainty-aware multi-criteria decision analysis for evaluation of explainable artificial intelligence methods: A use case from the healthcare domain. Inf. Sci. 657: 119987 (2024) - [c17]Nijat Mehdiyev, Maxim Majlatow, Peter Fettke:
Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring. xAI (3) 2024: 420-438 - 2023
- [c16]Nijat Mehdiyev, Maxim Majlatow, Peter Fettke:
Explainable Artificial Intelligence Meets Uncertainty Quantification for Predictive Process Monitoring. PMAI@IJCAI 2023: 29-32 - [i5]Nijat Mehdiyev, Maxim Majlatow, Peter Fettke:
Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring. CoRR abs/2304.05736 (2023) - [i4]Nijat Mehdiyev, Maxim Majlatow, Peter Fettke:
Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective. CoRR abs/2304.06412 (2023) - [i3]Nijat Mehdiyev, Maxim Majlatow, Peter Fettke:
Interpretable and Explainable Machine Learning Methods for Predictive Process Monitoring: A Systematic Literature Review. CoRR abs/2312.17584 (2023) - 2021
- [c15]Nijat Mehdiyev, Peter Fettke:
Local Post-Hoc Explanations for predictive Process Monitoring in manufacturing. ECIS 2021 - [c14]Nijat Mehdiyev, Constantin Houy, Oliver Gutermuth, Lea Mayer, Peter Fettke:
Explainable Artificial Intelligence (XAI) Supporting Public Administration Processes - On the Potential of XAI in Tax Audit Processes. Wirtschaftsinformatik 2021 - 2020
- [j4]Nijat Mehdiyev, Joerg Evermann, Peter Fettke:
A Novel Business Process Prediction Model Using a Deep Learning Method. Bus. Inf. Syst. Eng. 62(2): 143-157 (2020) - [c13]Nijat Mehdiyev, Peter Fettke:
Prescriptive Process Analytics with Deep Learning and Explainable Artificial Intelligence. ECIS 2020 - [c12]Nijat Mehdiyev:
Explainable Process Predictions (xPP): A Holistic Framework and Applications (Extended Abstract). ICPM Doctoral Consortium / Tools 2020: 17-18 - [i2]Nijat Mehdiyev, Peter Fettke:
Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring. CoRR abs/2009.02098 (2020) - [i1]Nijat Mehdiyev, Peter Fettke:
Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing. CoRR abs/2009.10513 (2020)
2010 – 2019
- 2019
- [j3]Jana-Rebecca Rehse
Towards Explainable Process Predictions for Industry 4.0 in the DFKI-Smart-Lego-Factory. Künstliche Intell. 33(2): 181-187 (2019) - [c11]Patrick Lübbecke, Nijat Mehdiyev, Peter Fettke:
Substitution of hazardous chemical substances using Deep Learning and t-SNE. Wirtschaftsinformatik 2019: 1418-1432 - 2017
- [c10]Nijat Mehdiyev, Andreas Emrich, Björn P. Stahmer, Peter Fettke, Peter Loos:
iPRODICT - Intelligent Process Prediction based on Big Data Analytics. BPM (Industry Track) 2017: 13-24 - [c9]Nijat Mehdiyev, Joerg Evermann, Peter Fettke:
A Multi-stage Deep Learning Approach for Business Process Event Prediction. CBI (1) 2017: 119-128 - 2016
- [c8]Nijat Mehdiyev, Julian Krumeich, Dirk Werth, Peter Loos:
Determination of Event Patterns for Complex Event Processing Using Fuzzy Unordered Rule Induction Algorithm with Multi-objective Evolutionary Feature Subset Selection. HICSS 2016: 1719-1728 - 2015
- [c7]Nijat Mehdiyev, Julian Krumeich, Dirk Werth, Peter Loos:
Sensor event mining with hybrid ensemble learning and evolutionary feature subset selection model. IEEE BigData 2015: 2159-2168 - [c6]Nijat Mehdiyev, Julian Krumeich, David Enke, Dirk Werth, Peter Loos:
Determination of Rule Patterns in Complex Event Processing Using Machine Learning Techniques. Complex Adaptive Systems 2015: 395-401 - [c5]Julian Krumeich, Nijat Mehdiyev, Dirk Werth, Peter Loos:
Towards an Extended Metamodel of Event-Driven Process Chains to Model Complex Event Patterns. ER Workshops 2015: 119-130 - 2014
- [j2]Nijat Mehdiyev, David Enke:
Interest rate prediction: a neuro-hybrid approach with data preprocessing. Int. J. Gen. Syst. 43(5): 535-550 (2014) - [c4]David Enke, Nijat Mehdiyev:
A Hybrid Neuro-fuzzy Model to Forecast Inflation. Complex Adaptive Systems 2014: 254-260 - 2013
- [j1]David Enke, Nijat Mehdiyev:
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. 19(4): 636-648 (2013) - [c3]David Enke, Nijat Mehdiyev:
Type-2 Fuzzy Clustering and a Type-2 Fuzzy Inference Neural Network for the Prediction of Short-term Interest Rates. Complex Adaptive Systems 2013: 115-120 - 2012
- [c2]David Enke, Nijat Mehdiyev:
A New Hybrid Approach For Forecasting Interest Rates. Complex Adaptive Systems 2012: 259-264 - 2011
- [c1]David Enke, Manfred Grauer, Nijat Mehdiyev:
Stock Market Prediction with Multiple Regression, Fuzzy Type-2 Clustering and Neural Networks. Complex Adaptive Systems 2011: 201-206
Coauthor Index
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