inproceedings

[1]	Georg Ruß and Rudolf Kruse. Exploratory hierarchical clustering for management zone delineation in precision agriculture. volume NA of LNAI, pages na-na. Springer, 2011. to appear. [ bib ]
[2]	Georg Ruß and Rudolf Kruse. Machine learning methods for spatial clustering on precision agriculture data. pages NA-NA. IOS Press, 2011. to appear. [ bib ]
[3]	Rudolf Kruse, Matthias Steinbrecher, and Christian Moewes. Data mining applications in the automotive industry. pages 23-40, Singapore, 2010. Research Publishing Services. [ bib \| DOI \| http ]
[4]	Rudolf Kruse, Matthias Steinbrecher, and Christian Moewes. Temporal pattern mining. pages 3-8, Gliwice, Poland, 2010. IEEE Press. [ bib \| http ]
[5]	Georg Ruß and Rudolf Kruse. Regression models for spatial data: An example from precision agriculture. volume 6171 of LNAI, pages 450-463. Springer, 2010. [ bib \| DOI \| http ]
[6]	Georg Ruß, Rudolf Kruse, and Martin Schneider. A clustering approach for management zone delineation in precision agriculture. International Society of Precision Agriculture, 2010. [ bib ]
[7]	Georg Ruß, Rudolf Kruse, Martin Schneider, and Peter Wagner. Using advanced regression models for determining optimal soil heterogeneity indicators. Studies in Classification, Data Analysis, and Knowledge Organization, pages 463-471, Dresden, 2010. Springer. doi: http://dx.doi.org/10.1007/978-3-642-10745-0_50. [ bib \| http ]
[8]	Georg Ruß and Alexander Brenning. Data mining in precision agriculture: Management of spatial information. volume 6178 of LNAI, pages 350-359. Springer, 2010. [ bib \| DOI ]
[9]	Georg Ruß and Rudolf Kruse. Feature selection for wheat yield prediction. volume 26 of Proceedings of AI-2009, pages 465-478. Springer, 2010. [ bib \| DOI \| http ]
[10]	Roland Winkler, Frank Rehm, and Rudolf Kruse. Clustering with repulsive prototypes. Studies in Classification, Data Analysis, and Knowledge Organization, pages 207-215. Springer Verlag, 2010. [ bib \| DOI \| http ]
[11]	Roland Winkler, Annette Temme, Christoph Bösel, and Rudolf Kruse. Clustering radar tracks to evaluate efficiency indicators. pages 71-94. The Second ENRI International Workshop on ATM/CNS (EIWAC2010), 2010. [ bib \| http ]
[12]	Matthias Steinbrecher and Rudolf Kruse. Assessing the strength of structural changes in cooccurrence graphs: Advances in artificial intelligence, 32nd annual german conference on ai, paderborn, germany. volume 5803 of Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, pages 476-483. Springer Verlag, 2009. [ bib ]
[13]	Mirko Böttcher, Martin Spott, and Rudolf Kruse. An algorithm for anticipating future decision trees from concept-drifting data. volume 25 of Proceedings of AI-2008, pages 293-306, London, 2009. Springer. [ bib ]
[14]	Mirko Böttcher, Martin Spott, and Rudolf Kruse. A condensed representation of itemsets for analyzing their evolution over time. Lecture Notes in Artificial Intelligence (LNAI). Springer, 2009. (to appear). [ bib ]
[15]	Jörg Beyer, Kai Heesche, Werner Hauptmann, Clemens Otte, and Rudolf Kruse. Ensemble learning for multi-source information fusion. volume 5590 of Lecture Notes in Computer Science, pages 748-756, Heidelberg, 2009. Springer. [ bib \| DOI \| http ]
[16]	Georg Ruß. Data mining of agricultural yield data: A comparison of regression models. volume 5633 of LNAI, pages 24-37, Berlin, Heidelberg, 2009. Springer. [ bib \| DOI \| http ]
[17]	Georg Ruß, Rudolf Kruse, Martin Schneider, and Peter Wagner. Visual data mining of agriculture data. Poster Proceedings, pages 30-44, Leipzig, Germany, 2009. IBaI publishing. [ bib ]
[18]	Georg Ruß, Rudolf Kruse, Martin Schneider, and Peter Wagner. Visualization of agriculture data using self-organizing maps. volume 16 of Proceedings of AI-2008, pages 47-60, London, 2009. Springer. [ bib \| http ]
[19]	Matthias Steinbrecher and Rudolf Kruse. Fuzzy descriptions to identify temporal substructure changes of cooccurrence graphs. pages 1177-1182, 2009. [ bib ]
[20]	Matthias Steinbrecher and Rudolf Kruse. Clustering association rules with fuzzy concepts. Studies in Classification, Data Analysis, and Knowledge Organization, pages 197-206. Springer Verlag, 2009. [ bib ]
[21]	Mirko Böttcher, Martin Spott, and Rudolf Kruse. Predicting future decision trees from evolving data. pages 33-42, Pisa, Italy, 2008. IEEE Computer Society. [ bib \| DOI ]
[22]	Steffen Kempe and Rudolf Kruse. Mining temporal patterns in an automotive environment. pages 521-528, Málaga, 2008. [ bib ]
[23]	Christian Moewes and Rudolf Kruse. Adjusting monitored experiments to real-world cases by matching labeled time series motifs. Schriftenreihe des IAI, Universität Karlsruhe (TH), pages 214-223. Universitätsverlag Karlsruhe, 2008. [ bib ]
[24]	Christian Moewes, Clemens Otte, and Rudolf Kruse. Tackling multiple-instance problems in safety-related domains by quasilinear {SVM}. volume 48 of Advances in Soft Computing, pages 409-416. Springer Berlin/Heidelberg, 2008. [ bib \| DOI \| http ]
[25]	Christian Moewes and Rudolf Kruse. Unification of fuzzy {SVMs} and rule extraction methods through imprecise domain knowledge. pages 1527-1534, Torremolinos (Málaga), 2008. [ bib ]
[26]	Frank Rügheimer and Rudolf Kruse. An uncertainty representation for set-valued attributes with hierarchical domains. pages 197-203, Málaga, 2008. [ bib ]
[27]	Georg Ruß, Rudolf Kruse, Detlef Nauck, and Mirko Böttcher. Relevance feedback for association rules by leveraging concepts from information retrieval. volume 24 of Proceedings of AI-2007, pages 253-266, Cambridge, 2008. Springer. [ bib \| DOI \| http ]
[28]	Georg Ruß, Rudolf Kruse, Peter Wagner, and Martin Schneider. Data mining with neural networks for wheat yield prediction. volume 5077 of LNAI, pages 47-56, Leipzig, 2008. Springer Verlag. [ bib \| DOI ]
[29]	Georg Ruß, Rudolf Kruse, Martin Schneider, and Peter Wagner. Estimation of neural network parameters for wheat yield prediction. volume 276 of IFIP International Federation for Information Processing, pages 109-118. Springer Boston, 2008. [ bib \| DOI ]
[30]	Georg Ruß, Rudolf Kruse, Martin Schneider, and Peter Wagner. Optimizing wheat yield prediction using different topologies of neural networks. pages 576-582, Málaga, 2008. [ bib ]
[31]	Matthias Steinbrecher and Rudolf Kruse. Identifying temporal trajectories of association rules with fuzzy descriptions. pages 1-6, New York City, NY, 2008. [ bib \| DOI ]
[32]	Matthias Steinbrecher and Rudolf Kruse. Visualization of local dependencies of possibilistic network structures: At the junction of rough sets and fuzzy sets. volume 224 of Studies in Fuzziness and Soft Computing, pages 93-104. Springer Berlin / Heidelberg, 2008. doi: Visualization of Local Dependencies of Possibilistic Network Structures. [ bib ]
[33]	Christian Borgelt and Rudolf Kruse. An extended objective function for prototype-less fuzzy clustering. pages 146-151, 2007. [ bib ]
[34]	Siddeswara Mayura Guru, Matthias Steinbrecher, Saman K. Halgamuge, and Rudolf Kruse. {Multiple Cluster Merging and Multihop Transmission in Wireless Sensor Networks}. volume 4459 of Lecture Notes in Computer Science. Springer Verlag, 2007. [ bib \| DOI ]
[35]	Steffen Kempe, Jochen Hipp, and Rudolf Kruse. Fsmtree: An efficient algorithm for mining frequent temporal patterns. Studies in Classification, Data Analysis, and Knowledge Organization, pages 253-260, Berlin, Heidelberg, 2007. Springer. [ bib \| DOI \| .pdf ]
[36]	Rudolf Kruse, Christian Borgelt, Detlef Nauck, N. J. van Eck and, and Matthias Steinbrecher. {The role of soft computing in intelligent data analysis}. pages 9-17, 2007. Invited paper. [ bib ]
[37]	Frank Rehm, Rudolf Kruse, Georg Ruß, and Frank Klawonn. Modern data visualization for air traffic management. pages 19-24, 2007. [ bib \| DOI \| http ]
[38]	Georg Ruß, Mirko Böttcher, and Rudolf Kruse. Relevance feedback for association rules using fuzzy score aggregation. pages 54-59, 2007. [ bib \| DOI \| http ]
[39]	Matthias Steinbrecher and Rudolf Kruse. Visualisierung bayesscher netze zur diagnoseunterstützung. volume 1980 of VDI-Berichte. VDI-Verlag, 2007. [ bib ]
[40]	Matthias Steinbrecher and Rudolf Kruse. {Visualization of Possibilistic Potentials}. volume 4529 of Lecture Notes in Computer Science, pages 295-303. Springer Berlin / Heidelberg, 2007. [ bib \| DOI ]
[41]	Christian Borgelt and Rudolf Kruse. Finding the number of fuzzy clusters by resampling. IEEE Press, Piscataway, NJ, USA, 2006. [ bib \| DOI \| http ]
[42]	Rudolf Kruse, Jörg Gebhardt, Frank Rügheimer, and Heinz Detmer. Planning with graphical models. 2006. [ bib ]
[43]	M. J. Lesot and Rudolf Kruse. Data summarisation by typicality-based clustering for vectorial and non vectorial data. In Fuzzy Systems, 2006 IEEE International Conference on, pages 547-554, 2006. [ bib \| DOI ]
[44]	Marie-Jeanne Lesot, Frank Rehm, Frank Klawonn, and Rudolf Kruse. Prediction of aircraft flight duration. Delft, Netherlands, 2006. [ bib \| http ]
[45]	Frank Rehm, Frank Klawonn, and Rudolf Kruse. Rule classification visualization of high-dimensional data. 2006. [ bib ]
[46]	Frank Rehm, Frank Klawonn, and Rudolf Kruse. Visualization of single clusters. volume 4029 of Lecture Notes in Computer Science, pages 663-671. Springer, 2006. [ bib \| DOI ]
[47]	Frank Rehm, Frank Klawonn, and Rudolf Kruse. Visualization of fuzzy rule classifiers for flight duration forecast. 2006. event_dates=2006-09-27 - 2006-09-28;. [ bib \| http ]
[48]	Frank Rügheimer, Detlef Nauck, and Rudolf Kruse. Informationsfusion in neuro-fuzzy-systemen. pages 113-125. Universitätsverlag Karlsruhe, 2006. in German. [ bib ]
[49]	Georg Ruß, Arthur L. Hsu, Aminul Islam, Saman K. Halgamuge, Rudolf Kruse, Alan J. Smith, and Md A. Karim. Detection of faulty semiconductor wafers using dynamic growing self organizing map. pages 761-766, New Jersey, 2006. Piscataway. [ bib \| DOI \| http ]
[50]	Matthias Steinbrecher and Rudolf Kruse. Visualization of local dependencies of possibilistic network structures. pages 77-80, 2006. [ bib ]
[51]	Artificial intelligence and soft computing - icaisc 2006, 8th international conference, zakopane, poland, june 25-29, 2006, proceedings. volume 4029 of Lecture Notes in Computer Science. Springer, 2006. [ bib ]
[52]	Christian Borgelt and Rudolf Kruse. Fuzzy and probabilistic clustering with shape and size constraints. pages 945-950. Tsinghua University Press and Springer-Verlag, 2005. [ bib ]
[53]	Christian Borgelt and Rudolf Kruse. Probabilistic graphical models for the diagnosis of analog electrical circuits. pages 100-110. Springer-Verlag, 2005. [ bib \| http ]
[54]	Christian Borgelt, Andreas Nürnberger, and Rudolf Kruse. Fuzzy learning vector quantization with size and shape parameters. pages 195-200. IEEE Press, 2005. [ bib \| DOI \| .pdf ]
[55]	Christian Döring, Christian Borgelt, and Rudolf Kruse. Effects of irrelevant attributes in fuzzy clustering. pages 862-866. IEEE Press, 2005. [ bib \| DOI ]
[56]	Frank Rehm, Frank Klawonn, and Rudolf Kruse. Mdspolar: A new approach for dimension reduction to visualize high dimensional data. volume 3646 of Lecture Notes in Computer Science, pages 316-327, Berlin, Heidelberg, 2005. Springer. [ bib \| DOI ]
[57]	Frank Rehm, Frank Klawonn, and Rudolf Kruse. Visualizing single fuzzy c-means clusters. Gesellschaft für Informatik, 2005. [ bib \| http ]
[58]	Marie-Jeanne Lesot and Rudolf Kruse. Kernel-based outlier preserving clustering. Universität Göttingen, 2005. [ bib ]
[59]	Frank Rügheimer and Rudolf Kruse. Information miner - a data analysis platform. Universitat Politènica de Catalunya, 2005. [ bib \| .pdf ]
[60]	Frank Rügheimer and Rudolf Kruse. Datenanalyse-plattform informationminer. Universitätsverlag Karlsruhe, 2005. in German. [ bib \| .pdf ]
[61]	From data and information analysis to knowledge engineering - proc. 29th ann. conf. of the german classification society (gfkl 2005, magdeburg, germany). Springer-Verlag, 2005. [ bib \| http ]
[62]	Xiaomeng Wang, Christian Borgelt, and Rudolf Kruse. Mining fuzzy frequent item sets. pages 528-533. Tsinghua University Press and Springer-Verlag, 2005. [ bib ]
[63]	Christian Borgelt and Rudolf Kruse. Shape and size regularization in expectation maximization and fuzzy clustering. volume 3202/2004, pages 52-62. Springer-Verlag, 2004. [ bib \| DOI \| .pdf ]
[64]	Christian Döring, Christian Borgelt, and Rudolf Kruse. Fuzzy clustering of quantitative and qualitative data. pages 84-89. IEEE Press, 2004. [ bib ]
[65]	Frank Rehm, Frank Klawonn, and Rudolf Kruse. Ausrei{ss}ererkennung mit fuzzy-clustering-methoden. Universitätsverlag Karlsruhe, 2004. [ bib ]
[66]	Frank Rehm, Frank Klawonn, and Rudolf Kruse. New approaches to noise clustering for detecting outliers. 2004. [ bib ]
[67]	Rudolf Kruse. Soft computing for information mining. 2004. [ bib ]
[68]	Jörg Gebhardt, Frank Rügheimer, Heinz Detmer, and Rudolf Kruse. Adaptable markov models in industrial planning. IEEE Press, 2004. [ bib \| .pdf ]
[69]	Xiaomeng Wang, Detlef Nauck, M. Spott, and Rudolf Kruse. Fuzzy decision trees - a new ci-method for the automatic data analysis platform spida. Universitätsverlag Karlsruhe, 2004. [ bib ]
[70]	Xiaomeng Wang, Detlef Nauck, M. Spott, and Rudolf Kruse. Intelligent data analysis with fuzzy decision trees. 2004. [ bib ]
[71]	Xiaomeng Wang, Detlef Nauck, M. Spott, and Rudolf Kruse. The fuzzy decision tree module in the automatic data analysis platform spida. Uni Göttingen, 2004. [ bib ]
[72]	A. Eichhorn, Daniela Girimonte, Aljoscha Klose, and Rudolf Kruse. Neuro-fuzzy classification of surface form deviations. pages 902-907, 2003. [ bib ]
[73]	Advances in intelligent data analysis v - proc. 5th int. symp. on intelligent data analysis (ida2003, berlin, germany). Springer-Verlag, 2003. [ bib \| http ]
[74]	Christian Borgelt and Rudolf Kruse. Speeding up fuzzy clustering with neural network techniques. IEEE Press, 2003. [ bib ]
[75]	Heiko Timm, Christian Döring, and Rudolf Kruse. Differentiated treatment of missing values in fuzzy clustering. pages 354-361, 2003. LNAI 2715. [ bib ]
[76]	Rudolf Kruse and A. Keller. Fuzzy rule generation for transfer passenger analysis. 2003. [ bib ]
[77]	Aljoscha Klose, Daniela Girimonte, and Rudolf Kruse. Extending neuro fuzzy systems to semi-supervised learning. 2002. [ bib ]
[78]	Christian Borgelt and Rudolf Kruse. Learning graphical models by extending optimal spanning trees ipmu'02. 2002. [ bib \| .pdf ]
[79]	A. Eichhorn, Daniela Girimonte, Aljoscha Klose, and Rudolf Kruse. Surface quality analysis with soft computing. volume 75 of 10th Zittau Fuzzy Colloquium, pages 292-299. IPM, 2002. [ bib ]
[80]	Heiko Timm, Frank Klawonn, and Rudolf Kruse. An extension of partially supervised fuzzy cluster. 2002. [ bib ]
[81]	Heiko Timm, Christian Döring, and Rudolf Kruse. Fuzzy clusteranalyse von daten mit fehlenden werten. pages 99-112, 2002. J. Biethahn, AFN. [ bib ]
[82]	Rudolf Kruse and Aljoscha Klose. Information mining with fuzzy methods: Trends and current challenges. pages 117-120, 2002. [ bib ]
[83]	Rudolf Kruse and Christian Borgelt. Data mining with graphical models. Discovery Science, pages 2-11. Springer, 2002. LNCS 2534. [ bib ]
[84]	Heiko Timm and Rudolf Kruse. A modification to improve possibilistic fuzzy cluster analysis. In Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on, volume 2, pages 1460-1465, 2002. [ bib \| DOI ]
[85]	Christian Borgelt and Rudolf Kruse. An empirical investigation of the {K2} metric. pages 240-251. Springer-Verlag, 2001. [ bib ]
[86]	Christian Borgelt and Rudolf Kruse. Learning graphical models with hypertree structure using a simulated annealing approach. IEEE Press, 2001. [ bib ]
[87]	Christian Döring, Rudolf Kruse, Heiko Timm, and Christian Borgelt. Fuzzy cluster analysis with cluster repulsion. 2001. On CD-ROM. [ bib ]
[88]	Rudolf Kruse. Information mining. pages 6-9. De Montfort University, 2001. [ bib ]
[89]	Heiko Timm, Christian Borgelt, Christian Döring, and Rudolf Kruse. Fuzzy cluster analysis with cluster repulsion. Verlag Mainz, 2001. [ bib ]
[90]	Andreas Nürnberger, Aljoscha Klose, and Rudolf Kruse. Analyzing borders between partially contradicting fuzzy classification rules. pages 59-63, 2000. [ bib ]
[91]	Aljoscha Klose, Rudolf Kruse, H. Gross, and U. Thoennessen. Automatische adaption struktureller bildanalysealgorithmen unter verwendung von data mining techniken. pages 91-96. VDI-Verlag, 2000. [ bib ]
[92]	Aljoscha Klose, Rudolf Kruse, K. Schulz, and U. Thoennessen. Controlling asymmetric errors in neuro-fuzzy classification. ACM Press, 2000. [ bib ]
[93]	Aljoscha Klose, Rudolf Kruse, H. Gross, and U. Thoennessen. Tuning on the fly of structural image analysis algorithms using data mining. SPIE Press, 2000. [ bib ]
[94]	Andreas Nürnberger, Rudolf Kruse, and Aljoscha Klose. Effects of antecedent pruning in fuzzy classification systems. pages 154-157, 2000. [ bib ]
[95]	Christian Borgelt and Rudolf Kruse. Learning from imprecise data: Possibilistic graphical models. pages 190-203. Consiglio Nazionale delle Ricerche, 2000. [ bib ]
[96]	Christian Borgelt, Heiko Timm, and Rudolf Kruse. Using fuzzy clustering to improve naive {B}ayes classifiers and probabilistic networks. IEEE Press, 2000. [ bib ]
[97]	Christian Borgelt, Jörg Gebhardt, and Rudolf Kruse. Possibilistic graphical models. volume 408 of CISM Courses and Lectures, pages 51-68. Springer-Verlag, 2000. [ bib ]
[98]	J. Marx-Gómez, C. Rautenstrauch, Andreas Nürnberger, and Rudolf Kruse. Hybrid approach to forecast returns of scrapped products to recycling and remanufacturing. 2000. [ bib ]
[99]	Rudolf Kruse and Aljoscha Klose. Information mining: Applications in image processing. pages 266-285. Springer, 2000. [ bib ]
[100]	Andreas Nürnberger, Aljoscha Klose, and Rudolf Kruse. Discussing cluster shapes of fuzzy classifiers. pages 546-550. New York, 1999. [ bib ]
[101]	Andreas Nürnberger, A. Radetzky, and Rudolf Kruse. Determination of elastodynamic model parameters using a recurrent neuro-fuzzy system. Verlag Mainz, 1999. [ bib ]
[102]	Andreas Nürnberger, Aljoscha Klose, Detlef Nauck, and Rudolf Kruse. Improving the clarity of neuro-fuzzy classifiers. 1999. [ bib ]
[103]	Christian Borgelt and Rudolf Kruse. A critique of inductive causation. pages 68-79. Springer-Verlag, 1999. [ bib ]
[104]	Detlef Nauck and Rudolf Kruse. Fuzzy classification rules using categorical and metric variables. pages 133-144. Leipziger Universitätsverlag, 1999. [ bib ]
[105]	Detlef Nauck and Rudolf Kruse. Fusing expert knowledge and information from data with nefclass. pages 386-393. Sunnyvale, CA, 1999. [ bib ]
[106]	Detlef Nauck and Rudolf Kruse. Learning in neuro-fuzzy systems with symbolic attributes and missing values. pages 142-147. Perth, 1999. [ bib ]
[107]	Detlef Nauck, Ulrike Nauck, and Rudolf Kruse. Nefclass for java - new learning algorithms. pages 472-476. IEEE, 1999. [ bib ]
[108]	Rudolf Kruse, Christian Borgelt, and Detlef Nauck. Fuzzy data analysis: Challenges and perspectives. pages 1211-1216. IEEE Press, 1999. [ bib ]
[109]	Rudolf Kruse, Christian Borgelt, and Detlef Nauck. {D}ata {M}ining mit neuro-{F}uzzy-{S}ystemen. 1999. [ bib ]
[110]	Rudolf Kruse, Christian Borgelt, and Detlef Nauck. Data mining with fuzzy methods: Status and perspectives. Verlag Mainz, 1999. [ bib ]
[111]	S. Siekmann, Rudolf Kruse, Jörg Gebhardt, F. van Overbeek, and R. Cooke. Information fusion in the context of stock index prediction. Springer, 1999. [ bib ]
[112]	Andreas Nürnberger, A. Radetzky, and Rudolf Kruse. A problem specific recurrent neural network for the description and simulation of dynamic spring models. pages 468-473, 1998. [ bib ]
[113]	Andreas Nürnberger, A. Radetzky, and Rudolf Kruse. Modelling and simulating a time-dependent physical system using fuzzy techniques and a recurrent neural network. pages 306-313. infix, 1998. [ bib ]
[114]	Andreas Nürnberger and Rudolf Kruse. Neuro-fuzzy techniques under matlab/simulink applied to a real plant. pages 572-576, 1998. [ bib ]
[115]	A. Radetzky, Andreas Nürnberger, D. P. Pretschner, and Rudolf Kruse. The simulation of elastic tissues in virtual laparoscopy using neural networks. pages 167-174, 1998. [ bib ]
[116]	Christian Borgelt and Rudolf Kruse. Efficient maximum projection of database-induced multivariate possibility distributions. volume 1, pages 663-668. IEEE Press, 1998. [ bib ]
[117]	Christian Borgelt and Rudolf Kruse. Possibilistic networks with local structure. volume 1, pages 634-638. Verlag Mainz, 1998. [ bib ]
[118]	Christian Borgelt, Jörg Gebhardt, and Rudolf Kruse. Possibilistic graphical models. 1998. [ bib ]
[119]	Detlef Nauck and Rudolf Kruse. Rule weights in fuzzy systems. 1998. [ bib ]
[120]	Detlef Nauck, Andreas Nürnberger, and Rudolf Kruse. Neuro-fuzzy classification. pages 287-294. Springer-Verlag, 1998. [ bib ]
[121]	Detlef Nauck and Rudolf Kruse. A neuro-fuzzy approach to obtain interpretable fuzzy systems for function approximation. pages 1106-1111, 1998. [ bib ]
[122]	Rudolf Kruse and G. Saake. Proceedings des workshops data mining und data warehousing am rande der informatik'98. Universität Magdeburg, 1998. [ bib ]
[123]	Jörg Gebhardt and Rudolf Kruse. Information source modelling for consistent data fusion. pages 27-34. CSREA Press, 1998. [ bib ]
[124]	Rudolf Kruse. Intelligente systeme: Wie geht man mit unvollkommenen informationen um? Antrittsvorlesung, Magdeburg, 1998. Otto-von-Guericke-Universität. [ bib ]
[125]	Christian Borgelt and Rudolf Kruse. Neuere entwicklungen im {D}ata {M}ining mit {B}ayesschen netzen. MIT GmbH, 1998. [ bib ]
[126]	Christian Borgelt and Rudolf Kruse. Possibilistic networks: Data mining applications. volume 1, pages 603-607. Verlag Mainz, 1998. [ bib ]
[127]	Rudolf Kruse and Christian Borgelt. Data mining with graphical models. volume 1, pages 17-30, 1998. [ bib ]
[128]	Andreas Nürnberger and Rudolf Kruse. Learning methods for fuzzy systems. pages 367-372. IOS-Press, 1998. [ bib ]
[129]	Heiko Timm and Rudolf Kruse. Fuzzy-clusteranalyse mit dataengine. 1998. [ bib ]
[130]	Rudolf Kruse and Heiko Timm. Fuzzy cluster analysis with missing values. pages 242-246, 1998. [ bib ]
[131]	Rudolf Kruse and Detlef Nauck. How the learning of rule weights affects the interpretability of fuzzy systems. pages 1235-1240, 1998. [ bib ]
[132]	Andreas Nürnberger, Detlef Nauck, L. Merz, and Rudolf Kruse. A neuro-fuzzy development tool for fuzzy controllers under matlab/simulink. pages 1029-1033, 1997. [ bib ]
[133]	Andreas Nürnberger and Rudolf Kruse. Learning methods for fuzzy systems. 1997. [ bib ]
[134]	Andreas Nürnberger, Rudolf Kruse, and Detlef Nauck. Neuro-fuzzy-regelung mit nefcon unter matlab/simulink. Universität Stuttgart, 1997. [ bib ]
[135]	Christian Borgelt and Rudolf Kruse. Learning probabilistic and possibilistic networks: Theory and applications. volume 1, pages 19-24, 1997. [ bib ]
[136]	Frank Klawonn and Rudolf Kruse. Techniques and applications of control systems based on knowledge based interpolation. Fuzzy Theory: Systems, Techniques and Application, pages 431-460. Academic Press, 1997. [ bib ]
[137]	Heiko Timm, Rudolf Kruse, Frank Klawonn, and Detlef Nauck. Flexible fuzzy clustering for data analysis as a plug-in library for data engine. pages 67-71, 1997. [ bib ]
[138]	Heiko Timm, Frank Klawonn, and Rudolf Kruse. Flexible fuzzy clustering for data analysis as a plug-in library for data engine. pages 91-96, 1997. [ bib ]
[139]	Rudolf Kruse and Christian Borgelt. Evaluation measures for learning probabilistic and possibilistic networks. volume 2, pages 669-676, 1997. [ bib ]
[140]	Rudolf Kruse and Christian Borgelt. Some experimental results on learning probabilistic and possibilistic networks with different evaluation measures. pages 71-85, 1997. [ bib ]
[141]	Rudolf Kruse, S. Siekmann, and R. Neuneier. Neuro-fuzzy methods in finance applied to the german stock index dax. 1997. [ bib ]
[142]	Rudolf Kruse and T. Sutter. Fuzzy queries in conventional databases for succession planning. 1997. [ bib ]
[143]	Rudolf Kruse and Detlef Nauck. Neuro-fuzzy systems for function approximation. pages 316-323, 1997. [ bib ]
[144]	Rudolf Kruse and Detlef Nauck. What are neuro-fuzzy classifiers? volume 3, pages 228-233, 1997. [ bib ]
[145]	Rudolf Kruse and Detlef Nauck. New learning strategies for nefclass. volume 4, pages 50-55, 1997. [ bib ]
[146]	Rudolf Kruse and Detlef Nauck. Function approximation by nefprox. pages 160-169, 1997. [ bib ]
[147]	S. Siekmann, Rudolf Kruse, and R. Neuneier. Advanced neuro-fuzzy techniques applied to the german stock index dax. 1997. [ bib ]
[148]	S. Siekmann, Rudolf Kruse, and R. Neuneier. Tägliche prognose des deutschen aktienindex dax mit neuro-fuzzy methoden. pages 7-18, 1997. [ bib ]
[149]	S. Siekmann, Rudolf Kruse, and R. Neuneier. Neuro-fuzzy in der finanzanalyse. in tagungsband des 2.workshops neuronale netze in ingenieursanwendungen. pages 67-78. Universität Stuttgart, 1997. [ bib ]
[150]	Christian Borgelt, Jörg Gebhardt, and Rudolf Kruse. Concepts for probabilistic and possibilistic induction of decision trees on real world data. volume 3, pages 1556-1560. Verlag Mainz, 1996. [ bib ]
[151]	Rudolf Kruse and Detlef Nauck. Neuronale fuzzy-systeme. Beiträge zur Herbstschule (HeKoNN96), GMD-Studien Nr. 300, pages 157-170. GMD-Forschungszentrum Informatik GmbH, 1996. [ bib ]
[152]	Detlef Nauck, Ulrike Nauck, and Rudolf Kruse. Generating classification rules with the neuro-fuzzy system (nefclass). pages 466-470. IEEE, Berkeley, 1996. [ bib ]
[153]	Jörg Gebhardt and Rudolf Kruse. Tightest hypertree decompositions of multivariate possibility distributions. pages 923-927, 1996. [ bib ]
[154]	Jörg Gebhardt and Rudolf Kruse. Measures of nonspecificity for decomposing possibility distributions. pages 177-179, 1996. [ bib ]
[155]	Jörg Gebhardt and Rudolf Kruse. On a tool for possibilistic reasoning in relational structures. pages 1471-1475, 1996. [ bib ]
[156]	Jörg Gebhardt and Rudolf Kruse. Parallel combination of information sources. 1996. [ bib ]
[157]	Detlef Nauck and Rudolf Kruse. Neuro-fuzzy classification with nefclass. pages 294-299. Springer-Verlag, 1996. [ bib ]
[158]	T. Sutter, G. S. Mollet, M. Schröder, Rudolf Kruse, and Jörg Gebhardt. Fuzzy queries for top management succession planning. pages 241-246, 1996. [ bib ]
[159]	Jörg Gebhardt and Rudolf Kruse. Learning possibilistic networks from data. pages 233-244, 1995. [ bib ]
[160]	Jörg Gebhardt and Rudolf Kruse. Learning possibilistic networks from data. pages 1575-1580, 1995. [ bib ]
[161]	Jörg Gebhardt and Rudolf Kruse. Reasoning and learning in probabilistic and possibilistic networks: {ECML95}, lecture notes in artificial intelligence. volume 912, pages 3-16. Springer, 1995. [ bib ]
[162]	Jörg Gebhardt and Rudolf Kruse. Learning possibilistic graphical models. pages 74-76, 1995. [ bib ]
[163]	Jörg Gebhardt and Rudolf Kruse. Discrete graphical models in possibility theory. 1995. [ bib ]
[164]	Jörg Gebhardt and Rudolf Kruse. A numerical framework for possibilistic abduction. Advances in Intelligent Computing. Springer, 1995. [ bib \| .pdf ]
[165]	Rudolf Kruse and J. Heinsohn. Unsicherheit und vagheit. 1995. [ bib ]
[166]	Frank Klawonn and Rudolf Kruse. From fuzzy sets to indistinguishability and back. 1995. [ bib ]
[167]	Frank Klawonn and Rudolf Kruse. Automatic generation of fuzzy controllers by fuzzy clustering. 1995. [ bib ]
[168]	Frank Klawonn, Detlef Nauck, and Rudolf Kruse. Generating rules from data by fuzzy and neuro-fuzzy methods. pages 223-230, 1995. [ bib ]
[169]	Rudolf Kruse and Detlef Nauck. Learning methods for fuzzy systems. pages 7-22, 1995. [ bib ]
[170]	Rudolf Kruse and Detlef Nauck. Neuronale fuzzy-systeme. Number 272 in GMD-Studien, pages 1-10. GMD-Forschungszentrum Informationstechnik GmbH, 1995. [ bib ]
[171]	L. M. De Campos, Jörg Gebhardt, and Rudolf Kruse. Axiomatic treatment of possibilistic independence. pages 77-88. Springer, 1995. [ bib ]
[172]	M. Schröder, Frank Klawonn, and Rudolf Kruse. Genetic algorithms and fuzzy situations for sequential optimization of control surfaces. pages 777-781, 1995. [ bib ]
[173]	Detlef Nauck and Rudolf Kruse. Neuro-fuzzy classification with nefclass. Springer-Verlag, 1995. [ bib ]
[174]	Detlef Nauck and Rudolf Kruse. {NEFCLASS} - a neuro-fuzzy approach for classification of data. pages 461-465, 1995. [ bib \| DOI ]
[175]	Detlef Nauck, Rudolf Kruse, and Roland Stellmach. New learning algorithms for the neuro-fuzzy environment {NEFCON-I}. pages 357-364, 1995. [ bib ]
[176]	Rudolf Kruse and Jörg Gebhardt. Focusing and learning in possibilistic dependency networks: Statistical sciences). pages 79-90. W.de Gruyter, 1995. [ bib ]
[177]	M. Schröder and Rudolf Kruse. Sequential optimization of characteristic mappings by means of genetic algorithms. 1995. [ bib ]
[178]	Jörg Gebhardt and Rudolf Kruse. A numerical framework for possibilistic abduction. 1994. [ bib ]
[179]	Jörg Gebhardt and Rudolf Kruse. On an information compression view of possibility theory. pages 1285-1288, 1994. [ bib ]
[180]	Jens Kinzel, Rudolf Kruse, and Frank Klawonn. Anpassung genetischer algorithmen zum erlernen und optimieren von fuzzy-reglern. Springer Verlag, 1994. [ bib ]
[181]	Jens Kinzel, Frank Klawonn, and Rudolf Kruse. Modifications of genetic algorithms for designing and optimizing fuzzy controllers. pages 28-33, 1994. [ bib ]
[182]	J. Beckmann, Jörg Gebhardt, Frank Klawonn, and Rudolf Kruse. Possibilistic inference and data fusion. pages 46-47, 1994. [ bib ]
[183]	Frank Klawonn and Rudolf Kruse. Fuzzy partitions and transformations. 1994. [ bib ]
[184]	M. Hartmann, Frank Klawonn, Rudolf Kruse, and K. Petras. Constructing rule bases and fuzzy sets for interpolation: Experiences from quality evaluation. pages 1671-1673, 1994. [ bib ]
[185]	Detlef Nauck and Rudolf Kruse. {NEFCON-I}: An {X-Window} based simulator for neural fuzzy controllers. pages 1638-1643, 1994. [ bib ]
[186]	Detlef Nauck and Rudolf Kruse. Choosing appropriate neuro-fuzzy models. pages 552-557, 1994. [ bib ]
[187]	Rudolf Kruse, Jörg Gebhardt, and Frank Klawonn. A fuzzy controller for idle speed regulation. pages 155-160, 1994. [ bib ]
[188]	Jörg Gebhardt and Rudolf Kruse. A new approach to semantical aspects of possibilistic reasoning. volume 747 of Lecture Notes in Computer Science. Springer Verlag, 1993. [ bib ]
[189]	Jörg Gebhardt, Rudolf Kruse, Clemens Otte, and M. Schröder. A fuzzy idle speed controller. 1993. [ bib ]
[190]	Frank Klawonn and Rudolf Kruse. Fuzzy control as interpolation on the basis of equality relations. 1993. [ bib ]
[191]	Rudolf Kruse. Fuzzy probability theory and fuzzy statistics. 1993. [ bib ]
[192]	Rudolf Kruse. On the extension of probability theory and statistics to the handling of fuzzy data. 1993. [ bib ]
[193]	Rudolf Kruse and M. Schröder. An application of equality relations to idle speed control. 1993. [ bib ]
[194]	Detlef Nauck and Rudolf Kruse. A fuzzy neural network learning fuzzy control rules and membership functions by fuzzy error backpropagation. pages 1022-1027, 1993. [ bib ]
[195]	Detlef Nauck, Frank Klawonn, and Rudolf Kruse. Combining neural networks and fuzzy controllers. pages 35-46. Springer-Verlag, 1993. [ bib ]
[196]	Rudolf Kruse, Jörg Gebhardt, and Frank Klawonn. On the interpretation of fuzzy controllers. 1993. [ bib ]
[197]	Philippe Smets and Rudolf Kruse. The transferable belief model for belief representation. 1993. [ bib ]
[198]	Detlef Nauck, Frank Klawonn, and Rudolf Kruse. Fuzzy sets, fuzzy controller and neural networks. 1992. [ bib ]
[199]	Frank Klawonn, Jörg Gebhardt, and Rudolf Kruse. Logical approaches to uncertainty and vagueness in the view of the context model. 1992. [ bib ]
[200]	Jörg Gebhardt and Rudolf Kruse. A possibilistic interpretation of fuzzy sets by the context model. 1992. [ bib ]
[201]	Jörg Gebhardt and Rudolf Kruse. Possibility theory and the context model. 1992. [ bib ]
[202]	Jörg Gebhardt, Rudolf Kruse, and Detlef Nauck. Information compression in the context model. 1992. [ bib ]
[203]	Jörg Gebhardt and Rudolf Kruse. Zur interpretation von fuzzy controllern. 1992. [ bib ]
[204]	Detlef Nauck and Rudolf Kruse. Interpreting changes in the membership functions of a self adaptive neural fuzzy controller. 1992. [ bib ]
[205]	Detlef Nauck and Rudolf Kruse. Neural fuzzy controller learning by fuzzy error propagation. 1992. [ bib ]
[206]	Detlef Nauck and Rudolf Kruse. A neural fuzzy controller learning by fuzzy error propagation. pages 388-397, 1992. [ bib ]
[207]	Detlef Nauck and Rudolf Kruse. Interpreting changes in the fuzzy sets of a self-adaptive neural fuzzy controller. pages 146-152, 1992. [ bib ]
[208]	Jörg Gebhardt and Rudolf Kruse. An integrating model of partial ignorance. 1991. [ bib ]
[209]	Jörg Gebhardt and Rudolf Kruse. An integrating model of uncertainty and vagueness. 1991. [ bib ]
[210]	Jörg Gebhardt, Detlef Nauck, and Rudolf Kruse. Interpretation und analyse von fuzzy daten. 1991. [ bib ]
[211]	Rudolf Kruse and Jörg Gebhardt. New methods in statistics with vague data. 1991. [ bib ]
[212]	Rudolf Kruse. On the context model. Blanes, 1991. [ bib ]
[213]	Rudolf Kruse, E. Schwecke, and Frank Klawonn. On a tool for reasoning with mass distributions. 1991. [ bib ]
[214]	Rudolf Kruse, Frank Klawonn, and Detlef Nauck. Reasoning with mass distributions. pages 182-187, 1991. [ bib ]
[215]	Rudolf Kruse, Jörg Gebhardt, and Frank Klawonn. Reasoning with mass distributions and the context model. Lecture Notes in Computer Science. Springer Verlag, 1991. [ bib ]
[216]	Jörg Gebhardt and Rudolf Kruse. Some new aspects of testing hypotheses in fuzzy statistics. 1990. [ bib ]
[217]	Rudolf Kruse and E. Schwecke. On the representation of uncertain knowledge in the context of belief functions. 1990. [ bib ]
[218]	Rudolf Kruse and E. Schwecke. On the combination of information sources. 1990. [ bib ]
[219]	Rudolf Kruse and E. Schwecke. On the interpretation of conditioning concepts for belief functions. Reisensburg, Günzburg, 1990. [ bib ]
[220]	Rudolf Kruse and Jörg Gebhardt. On a dialog system for modelling and statistical analysis of linguistic data. 1989. [ bib ]
[221]	Rudolf Kruse and E. Schwecke. On the treatment of cyclic dependencies in causal networks. 1989. [ bib ]
[222]	Rudolf Kruse. Vages wissen in expertensystemen. Bremen, 1989. [ bib ]
[223]	P. Friedrich, W. Struckmann, and Rudolf Kruse. Das salzgittermodell - ein beispiel für die zusammenarbeit zwischen hochschule und industrie bei der entwicklung komplexer software-systeme. 1989. [ bib ]
[224]	Jörg Gebhardt and Rudolf Kruse. Statistische untersuchungen anhand von vagen daten. Springer Verlag, 1988. [ bib ]
[225]	Rudolf Kruse and K. D. Meyer. On calculating the covariance in the presence of vague data. 1988. [ bib ]
[226]	Rudolf Kruse and E. Schwecke. Fuzzy reasoning in a multidimensional space of hypotheses. pages 147-151, 1988. [ bib ]
[227]	Rudolf Kruse. Evidential reasoning in product spaces. Reisensburg, Günzburg, 1988. [ bib ]
[228]	Rudolf Kruse, Jörg Gebhardt, and J. Knop. On a dialog system for modelling and statistical analysis of linguistic data. 1988. [ bib ]
[229]	Rudolf Kruse and K. D. Meyer. Fuzzy markov chains and their application to processor power considerations. 1987. [ bib ]
[230]	Rudolf Kruse and K. D. Meyer. Parametric statistics in the presence of vague data. 1987. [ bib ]
[231]	Rudolf Kruse and K. D. Meyer. On linguistic modelling and linguistic approximation in the presence of vague data. 1987. [ bib ]
[232]	Rudolf Kruse, J. Freckmann, and M. Eike. Ein programmsystem für statistische untersuchungen mit unscharfen daten. 1987. [ bib ]
[233]	Rudolf Kruse. On a language and an interpreter for calculation and statistics on linguistic data. 1986. [ bib ]
[234]	Rudolf Kruse and K. D. Meyer. Statistics with fuzzy data. 1986. [ bib ]
[235]	Rudolf Kruse and K. D. Meyer. Confidence intervals for the parameter of the normal distribution in the presence of vague data. 1986. [ bib ]
[236]	Rudolf Kruse and K. D. Meyer. A consistent variance estimator in the presence of vague data. 1986. [ bib ]

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