Publications SRS
In accordance with the well known and accepted rule in the engineering field, the author sequence of all publications (1989 to present) is related to the FLAE system (first-last-author-emphasis system).
2022 |
Journal- and book contributions |
Ameyaw, D. A.; Deng, Q.; Söffker, D.: How to evaluate classifier performance in the presence of additional effects: A new POD-based approach allowing certification of machine learning approaches. Machine Learning with Applications (Elsevier), Volume 7, 15 March, 2022.[PDF][LINK]
Ameyaw, D. A.; Deng, Q.; Söffker, D.: Evaluating Machine Learning-Based Classification Approaches: A New Method for Comparing Classifiers Applied to Human Driver Prediction Intentions. IEEE Access, Vol. 10, 2022, pp. 62429-62439.[PDF][LINK]
Bakhshande, F.; Ameyaw, D. A.; Madan, N.; Söffker, D.: New Metric for Evaluation of Deep Neural Network Applied in Vision-Based Systems. Applied Science, Vol. 12, No. 7, 2022, pp. 3251.[PDF][LINK]
David, R.; Söffker,D.: A study on a HMM-based state machine approach for lane changing behavior recognition. IEEE Access, Vol. 10, 2022, pp 122954-122964.[PDF][LINK]
Demmerling, A. L.; Wei, X.; Söffker, D.: Extended tapping torque test to differentiate metalworking fluids. Tribology International, Vol. 175, 2022, 107819.[LINK]
Deng, Q.; Söffker, D.: A Review of HMM-Based Approaches of Driving Behaviors Recognition and Prediction. IEEE Transactions on Intelligent Vehicles (TIV), Vol. 7, No. 1, March, 2022, pp. 21-31.[PDF][LINK]
Moulik, B.; Bose, B.; Ali, A.M.; Söffker, D.: Energy management strategy for electric vehicles and connected renewable energy systems in a micro grid environment of a university campus. Transforming Mobility Ð What Next?, 2022, pp. 195Ð217.[PDF][LINK]
Owino, L.; Söffker, D.: How much is enough in watering plants? State-of-the-art in irrigation control: advances, challenges, and opportunities with respect to precision irrigation. Frontiers in Control Engineering, Lausanne, 2022.[PDF][LINK]
Pham, H. A.; Söffker, D.: Improved model-free adaptive predictive control based on recursive least-squares estimation algorithm. Asian J. Control, 2022.[PDF][LINK]
Sheng, W.; Liu, Y.; Söffker, D.: A novel adaptive boosting algorithm with distance-based weighted least square support vector machine and filter factor for carbon fiber reinforced polymer multi-damage classification. Structural Health Monitoring, Vol. 22(2), 2022, pp. 1273-1289.[LINK]
Sheng, W.; Liu,Y.; Söffker,D. : A novel AdaBoost algorithm with distance-based WLSSVM and filter factor for CFRP multi-damage classification. Structural Health Monitoring, 2022, accepted.
Tanshi, F.; Söffker, D.: Determination of takeover time budget based on analysis of driver behavior. IEEE Open Journal of Intelligent Transportation Systems, Vol. 3, 2022, pp. 813-824.[PDF][LINK]
Thind, N. S.; Hering, J.; Söffker, D.: Fast and precise generic model for position-based trajectory prediction of vessels. MDPI Automation, No. 4, 2022, pp. 633-645.[PDF][LINK]
Referenzierbare und mehrfach referierte Konferenzbeiträge |
Bejaoui, A.; F; Söffker, D.: Supervision concept for situated human driving applied to inland shipping. IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), Macau, China, 2022, pp. 244-249.[PDF][LINK]
Bejaoui, A.; He, C.; Söffker, D.: Novel model-based decision support system for reliable human machine systems in complex situations. Annual Conference of the PHM Society 2022, Nashville, Tennessee, USA, 2022.[PDF][LINK]
Boschmann, W.; Söffker, D.: Complementary and situation sensitive object detection, review performance, and performance dependencies of common approaches. IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2022), Macau, China, 2022, pp. 888-892.[PDF][LINK]
David, R.; Söffker, D.: Effect of environmental and eye-tracking information: An Artificial Neural Network-based state machine approach for human driver intention recognition. IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA), Salerno, Italy, 2022, pp. 16-22.
David, R.; Söffker, D.: Effect of environmental and eye-tracking information: An Artificial Neural Network-based state machine approach for human driver intention recognition. The 12th IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA), Salerno, Italy, 2022, pp. 16-22.[LINK]
Denker, J.; Iannino, V.; Laudenberg, C.; Tenner, A.; Daun, M.; Jelali, M.: Improved temperature monitoring and control of production lines in casting through BaSyx framework and edge intelligence. IEEE World Congress on Computational Intelligence, Padua, Italy, 2022.[LINK]
Diepers, F.; Polke, D.; Ahle, E.; Söffker, D.: Data-Driven Force Control of an Automated Scratch Test. 10th International Conference on Control, Mechatronics and Automation (ICCMA), Belval, Luxembourg, 2022, pp. 94-99.[PDF][LINK]
Donandt, K.; Böttger, K.; Söffker, D.: Short-term Inland Vessel Trajectory Prediction with Encoder-Decoder Models. IEEE 25th International Conference on Intelligent Transportation Systems (IEEE ITSC 2022), Macau, China, 2022, pp. 974-979.[PDF][LINK]
Gerz, F.; Bastürk, T.; Kirchhoff, J.; Denker, J.; Al-Shrouf, L.; Jelali, M. : A comparative study and a new industrial platform for decentralized anomaly detection using machine learning algorithms.. IEEE World Congress on Computational Intelligence, Padua, Italy, 2022.[LINK]
He, C.; Bejaoui, A. ; Söffker, D.: Situated and personalized monitoring of human operators during complex situations. European Conference on Safety and Reliability (ESREL), Dublin, Ireland, 2022.[PDF][LINK]
He, C.; Söffker, D.: Identification of human driver critical behaviors and related reliability evaluation in real time. European Conference on Safety and Reliability (ESREL), Dublin, Ireland, 2022.[PDF]
Kipchirchir, E.; Do, M. H.; Njiri, J. G.; Söffker, D.: Mixed-Sensitivity Robust Disturbance Accommodating Control for Load Mitigation and Speed Regulation of Wind Turbines. European Control Conference (ECC) 2022, London, 2022, pp. 1012-1017.[PDF][LINK]
Liebeton, J.; Söffker, D.: Practical experiences to know making Acoustic Emission-based SHM successful. European Workshop on Structural Health Monitoring, (EWSHM) Springer Nature Switzerland AG, Palermo, Italy, Vol. 3, 2022, pp. 812 - 819.[PDF][LINK]
Owino, L.; Söffker, D.: Deficit irrigation-based growth control of maize plants using hybrid model predictive / trellis decoding algorithm. IFAC Conference on Sensing, Control and Automation Technologies for Agricontrol, Munich, 2022.[PDF][LINK]
Polke, D.; Diepers, F.; Ahle, E.; Söffker, D.: Development of a Framework for Data-Driven Modeling with Cloud Services in the Process Industry. IEEE International Conference on Automation, Robotics and Computer Engineering, Wuhan, China, 2022, pp. 109-115.[PDF][LINK]
Severin, T.; Söffker, D.: Sensor optimization for altitude estimation of spraying drones in vineyards. IFAC Conference on Sensing, Control and Automation Technologies for Agricontrol, Munich, Vol. 55(32), 2022, pp. 107-112.[PDF][LINK]
Thind, N. S; Söffker, D.: Probabilistic ship behavior prediction using generic models. IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2022), Macau, China, 2022.[PDF][LINK]
Thind, N. S.; Ameyaw, D. A.; Söffker, D.: Adaptive situated and reliable prediction of object trajectories. European Conference of Safety and Reliability (ESREL), Dublin, 2022.[PDF]
Viehöfer, S.; Brauer, P.; Söffker, D.: Modeling and simulation of aquaculture systems. IFAC Conference on Sensing, Control and Automation Technologies for Agricontrol, Munich, 2022.[PDF][LINK]
Wei, X.; Jochmann, F.; Demmerling, A. L.; Söffker, D.: Application of transfer learning in metalworking fluid distinction. ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (ASME IDETC), St. Louis Missouri, 2022.[PDF][LINK]
Wei, X.; Söffker, D.: A new unsupervised learning approach for CWRU bearing state distinction. European Workshop on Structural Health Monitoring (EWSHM 2022) , Vol. 270, 2022, 312-319.[PDF][LINK]
Wei, X.; Söffker, D.: A new data processing method for Acoustic Emission signals for metalworking fluid classification. Annual Conference of the Prognostics and Health Management Society (PHM 2022), Nashville, Tennessee, 2022.[PDF][LINK]
Weitere Konferenzbeiträge |
Vorträge/Sonstiges |
Benrabia, I.; Moulik, B.; Söffker,D.: Role of energy management systems (EMS) in the development of Eco-cities: a system-oriented review introducing an agent perspective. Wissenschaftsforum Mobilität 2022, Duisburg, 2022.[LINK]
Mohd Fadil, M. K.; Boschmann, W.; Söffker, D.: Localization of inland vessels in a waterway environment: Application of point cloud registration and SLAM approaches.. AIC, Duisburg, 2022.