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The difference between interactive evolution-ary computation (IEC) and traditional evolutionary computation (TEC) is that in IEC individuals' fitness is subjectively assigned by the user, while in TEC the fitness is objectively given by function or others. The user in IEC assigns fitness according to his/her preference. Therefore, if his/her preference drifts, the implicit fitness function for preference...
The thesis, in order to solve the fault diagnosis problem of oil Parameter, adaptive neural network-based fuzzy inference system (ANFIS) was applied to build a fault diagnosis model of automobile engine, with the construction of ANFIS, by using gradient descent genetic algorithm and optimization of system parameters of neutral network learning algorithm, inputs the fusion data into ANFIS, and introduces...
The thesis introduces grey system model and RBF neural network. In the light of the drawbacks and merits of the two models, the author puts forward the residue amending combined prediction model, and makes a contrast between the three models in prediction and precision. The result indicates that, the combined model is better than that of the single models for higher precision and smaller error.
Reducing users' fatigue and improving the performance are two focuses of the research of interactive evolutionary computation (IEC). Aiming at the focuses, knowledge learning in IEC is put forward. Before the discussion of knowledge learning, the issue of information sampled from history evolution is discussed, from which the knowledge is extracted. The knowledge learning based on gene-sense-unit...
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