Artificial Intelligence
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
International Journal of Approximate Reasoning
ECM: An evidential version of the fuzzy c-means algorithm
Pattern Recognition
MOGAMOD: Multi-objective genetic algorithm for motif discovery
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Analysis of evidence-theoretic decision rules for pattern classification
Pattern Recognition
An evidence-theoretic k-NN rule with parameter optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Maximal confidence intervals of the interval-valued belief structure and applications
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Structural damage identification based on Bayesian theory and improved immune genetic algorithm
Expert Systems with Applications: An International Journal
Computers & Mathematics with Applications
Hi-index | 12.07 |
To estimate the unmeasured parameter from experts and running data, in this paper, a novel method named ''immune genetic algorithm-based adaptive evidential classification rule (IGA-EC)'' was proposed. The IGA-EC model was realized by two strategies: (1) a new parametric distance metric was applied instead of Euclidean distance to enhance the robust adaptive ability of the traditional evidence-theoretic classification rule; and (2) the powerful evolutionary algorithm immune genetic algorithm was used to parallel search the global optimal solutions of the parameters involved in the proposed model. To validate IGA-EC model, some experiments were conducted based on some popular data sets, and the experimental results show that the proposed method was powerful with respect to the accuracy. Finally, the IGA-EC model was used to estimate the unmeasured parameter level of coal powder filling in the ball mill in power plant. From the analysis of the estimating results, it suggests that the proposed method was applicable for estimating the level of coal powder, and the proposed method can also be applied for estimating other unmeasured parameters in industry.