The Natural Induction System AQ21 and its Application to Data Describing Patients with Metabolic Syndrome: Initial Results
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[1] Zoran Filipi,et al. Cam-phasing Optimization Using Artificial Neural Networks as Surrogate Models-Fuel Consumption and NOx Emissions , 2006 .
[2] Kenneth A. Kaufman,et al. Learning Patterns in Noisy Data: The AQ Approach , 2001, Machine Learning and Its Applications.
[3] R S Collantes,et al. The metabolic syndrome and nonalcoholic fatty liver disease. , 2006, Panminerva medica.
[4] Ryszard S. Michalski,et al. Generating Alternative Hypotheses in AQ Learning , 2004 .
[5] Dimitrios C. Rakopoulos,et al. The Effect of Various Dynamic, Thermodynamic and Design Parameters on the Performance of a Turbocharged Diesel Engine Operating under Transient Load Conditions , 2004 .
[6] Christian Setzkorn,et al. On the use of multi-objective evolutionary algorithms for the induction of fuzzy classification rule systems. , 2005, Bio Systems.
[7] Thomas Kruse,et al. Automated Model-Based GDI Engine Calibration Adaptive Online DoE Approach , 2002 .
[8] R. Michalski. Attributional Calculus: A Logic and Representation Language for Natural Induction , 2004 .
[9] Jan M. Zytkow,et al. Unified algorithm for undirected discovery of exception rules , 2005, Int. J. Intell. Syst..
[10] Kris V Kowdley,et al. Adiponectin--tipping the scales from NAFLD to NASH? , 2005, Gastroenterology.
[11] Mark Paul Gravesend Guerrier,et al. The Development of Model Based Methodologies for Gasoline IC Engine Calibration , 2004 .
[12] Christopher J. Rutland,et al. Improvement of Neural Network Accuracy for Engine Simulations , 2003 .
[13] Sven Meyer,et al. New Calibration Methods and Control Systems with Artificial Neural Networks , 2002 .
[14] Jacobus van Zyl,et al. Simultaneous Concept Learning of Fuzzy Rules , 2004, ECML.
[15] Kenneth A. Kaufman,et al. The AQ21 Natural Induction Program for Pattern Discovery: Initial Version and its Novel Features , 2006, 2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06).
[16] William W. Cohen. Fast Effective Rule Induction , 1995, ICML.
[17] Shigeyuki Morita,et al. Application of Fuzzy Control to Internal Combustion Engines , 1994 .
[18] S. Spinler,et al. Challenges Associated with Metabolic Syndrome , 2006, Pharmacotherapy.
[19] Chris Brace,et al. Dynamic Behaviour of a High Speed Direct Injection Diesel Engine , 1999 .
[20] Eric Rask,et al. Simulation-Based Engine Calibration: Tools, Techniques, and Applications , 2004 .
[21] David Lowe,et al. Validation of neural networks in automotive engine calibration , 1997 .
[22] Peter Clark,et al. The CN2 Induction Algorithm , 1989, Machine Learning.
[23] Z. Pawlak. Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .
[24] Steven P. Larson,et al. Clinical model for distinguishing nonalcoholic steatohepatitis from simple steatosis in patients with nonalcoholic fatty liver disease , 2006, Liver international : official journal of the International Association for the Study of the Liver.
[25] Cleophas C. Jackson,et al. Effects of Steady-State and Transient Operation on Exhaust Emissions from Nonroad and Highway Diesel Engines , 1998 .
[26] Zarich Sw,et al. Metabolic syndrome, diabetes and cardiovascular events: current controversies and recommendations. , 2006, Minerva cardioangiologica.
[27] Ryszard S. Michalski,et al. A Theory and Methodology of Inductive Learning , 1983, Artificial Intelligence.
[28] Zoran Filipi,et al. Cam-Phasing Optimization Using Artificial Neural Networks as Surrogate Models-Maximizing Torque Output , 2005 .
[29] Karen Schlauch,et al. Gene Expression of Leptin, Resistin, and Adiponectin in the White Adipose Tissue of Obese Patients with Non-Alcoholic Fatty Liver Disease and Insulin Resistance , 2006, Obesity surgery.
[30] Christopher M. Atkinson,et al. Dynamic Model-Based Calibration Optimization: An Introduction and Application to Diesel Engines , 2005 .
[31] R. M. Green,et al. Measuring the Cylinder-to-Cylinder EGR Distribution in the Intake of a Diesel Engine During Transient Operation , 2000 .