矿山开采是一复杂的过程，其全局优化决策可视为一个复杂的大系统。
Mining is a complex process. The global optimum decision for mines can be regarded as a complex large system.
仿真及实际应用结果表明，算法地改进大大提高了其全局搜索能力，分时供电的优化能显著降低锌电解过程的用电费用。
Simulation and industrial practical results show that global search ability of IPSO is improved greatly and optimization of TSPS can decrease the power cost notably.
采用神经网络与遗传算法相结合的方法，用黑箱模型计算催化精馏过程，并进行了全局优化；
A method, which combined neural network and genetic algorithms, was employed to simulate the catalytic distillation process by black box model and optimize the operational parameters.
将混沌机制引入常规BP算法，利用混沌机制固有的全局游动，逃出权值优化过程中存在的局部极小点，解决了网络训练易陷入局部极小点的问题。
Chaotic mechanism is introduced to normal BP algorithm, and the problem of local limit value for network is solved using global moving characteristic of chaotic mechanism is weight optimization.
采用混合寻优策略，使优化过程中的探测点能免于陷入局部极小而进入全局最优点的所在区域；
Mixing optimization scheme enables the probe points to enter the area where the global optimization point locates.
进化策略算法是一种模拟自然界生物进化过程的全局优化方法。
Evolution strategies as global optimization search methods, are computing models simulating the evolutionary mechanisms of nature.
本文介绍了粒子群优化算法的基本原理，并通过建立记忆表，详尽描述了粒子群优化算法中个体极优和全局极优的搜寻求解过程。
This paper reviews the basic theory, and describes the seeking procedure of the personal best and the global best in PSO through establishing memory table.
结果表明：基于智能体的方法能实现多个运行决策的全局协调和集成，达到过程运行系统整体优化的目标。
The result shows that global coordination and optimization of process operating systems is achieved with the proposed approach.
工业生产过程自动化的概念已扩展到最优化和全局最优化。
The concept of industrial process automation has been extended to optimization and global optimization.
该算法能在优化过程中自动调整各参数，从而取得问题的全局优化解。
This algorithm can adjust parameters automatically in the optimization process to find the global optimal solution.
介绍了在化学机械抛光过程中，可以通过抛光头与抛光台运动速度关系优化配置，降低晶片表面不均匀度，从而更好地实现晶片局部和全局平坦化。
This paper introduces that we can reduce Within wafer nonuniformity (WIWNU) to achieve part and full planarization by distributing the speed of polishing head and polis.
由于标准粒子群优化(PSO)算法把惯性权值作为全局参数，因此很难适应复杂的非线性优化过程。
The standard particle Swarm optimization (PSO) algorithm cannot adapt to the complex and nonlinear optimization process, because the same inertia weight is used to update the velocity of particles.
由于标准粒子群优化(PSO)算法把惯性权值作为全局参数，因此很难适应复杂的非线性优化过程。
The standard particle Swarm optimization (PSO) algorithm cannot adapt to the complex and nonlinear optimization process, because the same inertia weight is used to update the velocity of particles.
应用推荐