Improved Artificial Immune System Algorithm with Local Search
The Artificial immune systems algorithms are Meta
heuristic optimization method, which are used for clustering and
pattern recognition applications are abundantly. These algorithms in
multimodal optimization problems are more efficient than genetic
algorithms. A major drawback in these algorithms is their slow
convergence to global optimum and their weak stability can be
considered in various running of these algorithms. In this paper,
improved Artificial Immune System Algorithm is introduced for the
first time to overcome its problems of artificial immune system. That
use of the small size of a local search around the memory antibodies
is used for improving the algorithm efficiently. The credibility of the
proposed approach is evaluated by simulations, and it is shown that
the proposed approach achieves better results can be achieved
compared to the standard artificial immune system algorithms
Artificial immune system, Cellular Automata,Cellular learning automata, Cellular learning automata,, Local search,Optimization.
Locating Critical Failure Surface in Rock Slope Stability with Hybrid Model Based on Artificial Immune System and Cellular Learning Automata (CLA-AIS)
Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.
CLA-AIS, failure surface, optimization methods, rock slope.
Hybrid Model Based on Artificial Immune System and Cellular Automata
The hybridization of artificial immune system with
cellular automata (CA-AIS) is a novel method. In this hybrid model,
the cellular automaton within each cell deploys the artificial immune
system algorithm under optimization context in order to increase its
fitness by using its neighbor-s efforts. The hybrid model CA-AIS is
introduced to fix the standard artificial immune system-s weaknesses.
The credibility of the proposed approach is evaluated by simulations
and it shows that the proposed approach achieves better results
compared to standard artificial immune system.
Artificial Immune System, Cellular Automat,neighborhood