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]

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]

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.