直接模拟复杂有趣的过程，而不是计算一套枯燥的演化公式，这是如今复杂系统研究中必不可少的要素。
Direct simulation of a process of interest, rather than the integration of a set of underlying evolution equations, is an indispensable element in the study of complex systems.
最后我们运用数值计算的方法研究了此系统的动力学演化。
Finally, we study dynamical evolution of this system using the numerical calculation.
分析计算机系统安全标准的演化过程，以及安全评价标准在安全产品评价中的实际应用情况。
The evolution history of computer security evaluation criteria and the application of security evaluation criteria to the evaluation of security products are analyzed.
为提高复杂工程系统的风险评估和计算效率，对工程系统中复杂性和信息密度演化进行研究。
The methodology is to use the information entropy to measure the risk degree of complex engineering system, and evaluate its relativity with information density evolution.
操作系统的功能因为以下一些原因而不断演化：1。计算资源的有效应用。
Operating system (OS) functions have evolved in response to the following considerations and issues: 1. Efficient utilization of computing resources 2.
计算结果表明，在若干次地震前，出现前兆系统的减熵异常过程，显示出在地震的孕育过程中，震源系统从无序向有序演化的过程。
The results show that the anomalous process on systematic decreasing entropy appears prior to several earthquakes, which indicates that the source system has evolved from disorder to order transiti…
根据前人成果，建立了煤层气地质演化史模型并以此为基础研制了计算机模拟系统。
According to the result of past researched, the author of this article established the geological evolution history model of coal bed gas and computer simulation system on this base.
因此分析量子信息处理系统在各种干扰下的演化规律，研究干扰对量子计算鲁棒性的影响，将非常有助于设计高可靠性的容错量子计算系统。
Thus exploring the robustness features of quantum information processing system in presence of various imperfections will be very helpful to design fault-tolerant quantum information processor.
在算法的状态估计阶段，采用混合系统粒子滤波和二元估计算法同时估计对象系统故障演化模型混合状态和未知参数的后验分布。
For state estimation of hybrid system with unknown transition probabilities, an adaptive estimation algorithm is proposed based on Monte Carlo particle filtering.
在算法的状态估计阶段，采用混合系统粒子滤波和二元估计算法同时估计对象系统故障演化模型混合状态和未知参数的后验分布。
For state estimation of hybrid system with unknown transition probabilities, an adaptive estimation algorithm is proposed based on Monte Carlo particle filtering.
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