Least Squares Support Vector Machine Classifiers
Neural Processing Letters
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Modern Regression Methods
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Modern automotive engines are controlled by the electronic control unit (ECU). The electronically controlled automotive engine power & torque is significantly affected with effective tune-up of ECU. Current practice of ECU tune-up relies on the experience of the automotive engineer. Therefore, engine tine-up is usually done by trial-and-error method because a mathematical power & torque model of the electronically controlled engine has not been determined yet. With an emerging technique, Support Vector Machines (SVM), the approximate power & torque model of an electronically controlled vehicle engine can be determined by training the sample data acquired from the dynamometer. This model can be used for the engine performance prediction. The construction and accuracy of the model are also discussed in this paper. The study shows that the predicted results are good agreement with the actual test results.