Nijat Mehdiyev
Título
Citado por
Citado por
Año
Stock market prediction with multiple regression, fuzzy type-2 clustering and neural networks
D Enke, M Grauer, N Mehdiyev
Procedia Computer Science 6, 201-206, 2011
722011
Time Series Classification using Deep Learning for Process Planning: A Case from the Process Industry
N Mehdiyev, J Lahann, A Emrich, D Enke, P Fettke, P Loos
Procedia Computer Science 114, 242-249, 2017
652017
Evaluating forecasting methods by considering different accuracy measures
N Mehdiyev, D Enke, P Fettke, P Loos
Procedia Computer Science 95, 264-271, 2016
502016
Stock market prediction using a combination of stepwise regression analysis, differential evolution-based fuzzy clustering, and a fuzzy inference neural network
D Enke, N Mehdiyev
Intelligent Automation & Soft Computing 19 (4), 636-648, 2013
492013
Determination of rule patterns in complex event processing using machine learning techniques
N Mehdiyev, J Krumeich, D Enke, D Werth, P Loos
Procedia Computer Science 61, 395-401, 2015
482015
A multi-stage deep learning approach for business process event prediction
N Mehdiyev, J Evermann, P Fettke
19th IEEE Conference on Business Informatics (CBI) 1, 119-128, 2017
402017
A hybrid neuro-fuzzy model to forecast inflation
D Enke, N Mehdiyev
Procedia Computer Science 36, 254-260, 2014
362014
A Novel Business Process Prediction Model Using a Deep Learning Method
N Mehdiyev, J Evermann, P Fettke
Business & Information Systems Engineering, 1-15, 2018
332018
Towards Explainable Process Predictions for Industry 4.0 in the DFKI-Smart-Lego-Factory
JR Rehse, N Mehdiyev, P Fettke
KI-Künstliche Intelligenz, 1-7, 2019
272019
Determination of event patterns for complex event processing using fuzzy unordered rule induction algorithm with multi-objective evolutionary feature subset selection
N Mehdiyev, J Krumeich, D Werth, P Loos
49th Hawaii International Conference on System Sciences (HICSS), 1719-1728, 2016
192016
Towards an extended metamodel of event-driven process chains to model complex event patterns
J Krumeich, N Mehdiyev, D Werth, P Loos
International Conference on Conceptual Modeling, 119-130, 2015
132015
Prescriptive process analytics with deep learning and explainable artificial intelligence
N Mehdiyev, P Fettke
28th European Conference on Information Systems (ECIS 2020), 2020
112020
iPRODICT–Intelligent Process Prediction based on Big Data Analytics
N Mehdiyev, A Emrich, B Stahmer, P Fettke, P Loos
92017
Interest rate prediction: a neuro-hybrid approach with data preprocessing
N Mehdiyev, D Enke
International Journal of General Systems 43 (5), 535-550, 2014
82014
Sensor event mining with hybrid ensemble learning and evolutionary feature subset selection model
N Mehdiyev, J Krumeich, D Werth, P Loos
2015 IEEE International Conference on Big Data (Big Data), 2159-2168, 2015
72015
Identification of distinct usage patterns and prediction of customer behavior
S Dadashnia, T Niesen, P Hake, P Fettke, N Mehdiyev, J Evermann
BPI Challenge, 2016
62016
Type-2 fuzzy clustering and a type-2 fuzzy inference neural network for the prediction of short-term interest rates
D Enke, N Mehdiyev
Procedia Computer Science 20, 115-120, 2013
62013
A new hybrid approach for forecasting interest rates
D Enke, N Mehdiyev
Procedia Computer Science 12, 259-264, 2012
62012
Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring
N Mehdiyev, P Fettke
Interpretable Artificial Intelligence: A Perspective of Granular Computing …, 2021
42021
Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing
N Mehdiyev, P Fettke
29th European Conference on Information Systems (ECIS 2021), 2021
22021
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20