| 1. | Wind pressures acting on buildings are complicated functions of both time and space
作用在建筑物表而的风荷载是一个空间和时间的复杂函数。 |
| 2. | Use embedded code for complex functions or functions that are used multiple times in a single report
对于复杂函数或在一个报表中多次使用的函数，使用嵌入代码。 |
| 3. | However , pso algorithm has weak local searching abilities and be applied to solving complex optimal problems with high dimensions
但粒子群算法的局部搜索能力较差,不能有效求解高维复杂函数优化问题。 |
| 4. | Lex has several functions and variables that provide different information and can be used to build programs that can perform complex functions
Lex有几个函数和变量提供了不同的信息，可以用来编译实现复杂函数的程序。 |
| 5. | Experimental results on several benchmark complex functions with high dimensions show that the algorithm can rapidly converge at high quality solutions
对典型高维复杂函数的仿真表明：算法在求解质量和求解速度两方面都得到了好的结果。 |
| 6. | Abstract new methods were joined into the quantum genetic algorithm to solve the defects of poor local search ability and more iterative times
摘要针对量子遗传算法在多维复杂函数优化中迭代次数多、易陷入局部极值等缺点，提出新的量子遗传算法。 |
| 7. | The simulation result of complicated function optimization shows that this improved crossover operation is much more effective than the standard crossover operation
对复杂函数优化的仿真计算结果表明，同标准交叉操作比较，改进的交叉操作更加有效。 |
| 8. | The performance in search efficiency , computation complexity of the algorithm is analyzed by optimizing benchmark complicated functions and the effect of pertinent parameters on its performance is also analyzed
将其应用于典型的复杂函数优化问题，简要分析算法在搜索效率、计算复杂性等方面的性能以及相关参数对算法性能的影响，说明算法的可行性。 |
| 9. | A new hybrid particle swarm optimization combined with genetic algorithm was proposed in order to solve complex questions with high dimensions and overcome pie - maturity and the weak ability of local search
摘要为解决高维复杂函数的优化问题，克服标准粒子群算法早熟收敛、局部搜索能力弱等缺点，在标准粒子群优化算法中融合了遗传算法的设计思想，提出了一种新颖的混合粒子群算法。 |
| 10. | Abstract a new hybrid particle swarm optimization combined with genetic algorithm was proposed in order to solve complex questions with high dimensions and overcome pre ? maturity and the weak ability of local search
摘要为解决高维复杂函数的优化问题，克服标准粒子群算法早熟收敛、局部搜索能力弱等缺点，在标准粒子群优化算法中融合了遗传算法的设计思想，提出了一种新颖的混合粒子群算法。 |
