CAJ | 학술논문

对优化问题和游牧民族迁徙行为的比较研究表明，两者存在相似之处，文中模拟了游牧民族迁徙机制，提出了一种迁徙策略，并且与粒子群优化算法相结合，提高了算法摆脱局部极值的能力，通过集成技术，充分发挥各种粒子群优化算法的优点，实现协同演化，提高了算法的全局搜索能力。最后应用于求解计算分子生物学中的一个复杂问题——生物序列模体识别，实验表明，该算法是有效的。
대우화문제화유목민족천사행위적비교연구표명，량자존재상사지처，문중모의료유목민족천사궤제，제출료일충천사책략，병차여입자군우화산법상결합，제고료산법파탈국부겁치적능력，통과집성기술，충분발휘각충입자군우화산법적우점，실현협동연화，제고료산법적전국수색능력。최후응용우구해계산분자생물학중적일개복잡문제——생물서렬모체식별，실험표명，해산법시유효적。
A comparative study of optimization and nomadic migration shows that there are similarities between the two processes. In this paper, migration strategy is proposed by the simulation of nomadic migration, and the local extremum problem of particle swarm optimization has been solved by merging migration strategy. At the same time, the algorithm with ensemble technique not only sufficiently exerts the advantages of different particle swarm optimization and carries out harmonious evolution, but also the global search capability of the algorithm has been enhanced badly. Finally, the novel algorithm has been used to deal with biological Sequence motif detection, which is a complex problem in computational molecular biology and the experiments show that the algorithm is effective.