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| Content Provider | Springer Nature Link |
|---|---|
| Author | Liu, Jianyong Wang, Huaixiao Sun, Yangyang Li, Ling |
| Copyright Year | 2015 |
| Abstract | The adaptive niche quantum-inspired immune clonal algorithm (ANQICA) is proposed by combining the quantum coding, immune clone and niche mechanism together to solve the multi-modal function optimization more effectively and make the function converge to as many as possible extreme value points. The quantum coding can better explore the solution space, the niche mechanism ensures the algorithm to converge to multi-extremum and the adaptive mechanism is introduced according to the characteristics of each procedure of the algorithm to improve the effect of the algorithm. Example analysis shows that the ANQICA is better in exploration and convergence. Therefore, the ANQICA can be used to solve the problem of multi-modal function optimization effectively. |
| Starting Page | 297 |
| Ending Page | 305 |
| Page Count | 9 |
| File Format | |
| ISSN | 15677818 |
| Journal | Natural Computing |
| Volume Number | 15 |
| Issue Number | 2 |
| e-ISSN | 15729796 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2015-03-17 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Optimization algorithm Quantum-inspired evolutionary algorithm Niche Adaptive Immune clonal algorithm Theory of Computation Evolutionary Biology Processor Architectures Artificial Intelligence (incl. Robotics) Statistical Physics, Dynamical Systems and Complexity |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science Applications |
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