卫星星座优化设计的分布式遗传算法

遗传算法在区域卫星星座的优化设计中可以得到很好的结果。但使用遗传算法时，往往计算量很大，星座规模较大时会带来计算上的困难。充分利用计算机网络的空闲计算资源进行分布式计算可以解决这一问题，文章提出了相应的分布式计算模型，给出了实现方法，算例表明分布式遗传算法效率很高，该分布式计算方法也可以推广到其他应用领域。     

Retrieval of vegetation equivalent water thickness from reflectance using genetic algorithm (GA)-partial least squares (PLS) regression

This study aimed to investigate the performance of genetic algorithms coupled with partial least squares (GA-PLS) modeling of spectral reflectance in retrieving equivalent water thickness (EWT) at leaf and canopy level. A genetic algorithm was used to identify a subset of spectral bands sensitive to the variation in EWT, and PLS was then applied to relate the identified bands to EWT values. GA-PLS was applied to leaf level reflectance available from LOPEX dataset, and canopy data includes reflectance simulated by a leaf radiative transfer model PROSPECT and a canopy radiative transfer model SAILH and acquired by airborne visible/infrared imaging spectrometer (AVIRIS). The results indicate that GA-PLS has the capability of retrieving EWT from leaf and canopy reflectance, and achieved good estimation accuracy, i.e. low root mean square errors (RMSE) and high squared correlation coefficients (R²). For the retrieval at leaf level, the estimation accuracy can be as good as RMSE = 0.0019 g/cm² and R² = 0.939 or better. For the retrieval at canopy level, the model accuracy is RMSE = 0.0061 g/cm² and R² = 0.966 or better when PROSPECT-SAILH simulated reflectance was used; when AVIRIS image spectra were used, the model accuracy is RMSE = 0.0094 g/cm² and R² = 0.8734 for the calibration, and RMSE = 0.0132 g/cm² and R² = 0.7756 for the validation. These results from GA-PLS modeling support the conclusion that GA-PLS has the potential to be applied to AVIRIS, Hyperion and HyMap imagery for retrieving EWT. The selected bands for the AVIRIS datasets differ from those for the LOPEX and PROSPECT-SAILH simulated datasets, and this inconsistence of the selected bands for different datasets indicates that the GA-PLS method has the advantage of tuning the optimum bands for PLS regression and accommodating the effects of confounding factors.     

A new hybrid aerodynamic optimization framework based on differential evolution and invasive weed optimization

Since many aerodynamic optimization problems in the area of aeronautics contain highly nonlinear objectives and multiple local optima, it is still a challenge for most of the traditional optimization methods to find the global optima. In this paper, a new hybrid optimization framework based on Differential Evolution and Invasive Weed Optimization (IWO_DE/Ring) is developed, which combines global and local search to improve the performance, where a Multiple-Output Gaussian Process (MOGP) is used as the surrogate model. We first use several test functions to verify the performance of the IWO_DE/Ring method, and then apply the optimization framework to a supercritical airfoil design problem. The convergence and the robustness of the proposed framework are compared against some other optimization methods. The IWO_DE/Ring-based approach provides much quicker and steadier convergence than the traditional methods. The results show that the stability of the dynamic optimization process is an important indication of the confidence in the obtained optimum, and the proposed optimization framework based on IWO_DE/Ring is a reliable and promising alternative for complex aeronautical optimization problems.     

基于遗传算法和序列二次规划法的结构稳健性优化设计方法

针对目前结构优化设计方法未考虑参数随机性的问题,提出基于遗传算法和序列二次规划法的结构稳健性优化设计方法.将结构产品的质量特性作为优化目标,性能函数的可靠度指标作为约束条件,建立稳健性优化设计模型.利用序列二次规划法计算其性能函数的可靠度指标,在此基础上,利用遗传算法进行迭代计算,得出最优设计结果.最后,将某型导引头导...     

基于多目标进化算法的MEO区域通信星座优化设计

在分析星座轨道要素的基础上，研究了用改进非劣分层遗传算法（NSGA—Ⅱ）对中轨道（MEO）卫星的区域通信卫星近地点幅角、升交点赤经和平近点角等星座参数进行优化的方法，并对有5颗椭圆中轨卫星的星座进行了优化仿真。结果表明，优化后的星座不仅能在我国领土范围内提供实时通信服务，而且具有一定的全球覆盖能力。     

软硬件协同设计在远置终端系统设计中的应用

首先,对系统软硬件进行统一描述与建模;其次,重点介绍了动态规划法评估系统时间性能的方法和线性加权和法构造适应度函数的方法,并将两种方法与遗传算法相结合解决软硬件划分问题;最后进行了仿真,结果表明该方法能够有效的解决软硬件划分中的多目标优化设计。     

基于等基因序列双重随机遗传算法的复合材料铺层优化

复合材料铺层优化中常用的各种遗传算法，较难同时综合考虑表面45°、分层比例、连续铺层数限制等复杂工程约束问题，基于此，提出一种针对复合材料层压板的等基因序列双重随机遗传算法，在交换和突变算子中引入双重随机算法以保证优化迭代中基因序列的严格相等，基于SABRE 软件实现该优化算法，并通过算例验证算法的正确性。结果表明：该算法可满足均衡性、对称性、表面45°、连续铺层数限制、铺层比例等复杂工程约束，有较高的可靠性与工程适用性。     

零件工艺路线决策的GA方法

将基因算法应用于ＣＡＰＰ系统中的工艺路线排序。首先，将工艺路线决策的约束工艺知识表达为四种适用度函数，用自然数字链对零件特征加工单元进行基因编码，然后，通过选种、基因重组和基因变异，对群体进行多次计算和搜索，可以寻找到合理的工艺路线，该工艺路线同时也是较优的。     

On prediction of re-entry time of an upper stage from GTO

The evolution of objects in geostationary transfer orbit (GTO) is determined by a complex interplay of atmospheric drag and luni-solar gravity. These orbits are highly eccentric (eccentricity >0.7) and have large variations in velocity and perturbations during a revolution. The periodic changes in the perigee altitudes of these orbits are mainly due to the gravitational perturbations of the Sun and the Moon. The re-entry time of the objects in such orbits is sensitive to the initial conditions. The aim of this paper is to study the re-entry time of the cryogenic stage of the Indian geo-synchronous launch vehicle, GSLV-F04/CS, which has been decaying since 2 September 2007 from initial orbit with eccentricity equal to 0.706. Two parameters, initial eccentricity and ballistic coefficient, are chosen for optimal estimation. It is known that the errors are more in eccentricity for the observations based on two line elements (TLEs). These two parameters are computed with response surface method using a genetic algorithm for the selected eight different zones, based on rough linear variation of the mean apogee altitude during 200 days orbit evolution. The study shows that the GSLV-F04/CS will re-enter between 5 December 2010 and 7 January 2011. The methodology is also applied to study the re-entry of six decayed objects (cryogenic stages of GSLV and Molniya satellites). Good agreement is noticed between the actual and the predicted re-entry times. The absolute percentage error in re-entry prediction time for all the six objects is found to be less than 7%. The present methodology is being adopted at Vikram Sarabhai Space Centre (VSSC) to predict the re-entry time of GSLV-F04/CS.     

基于机器学习的卫星姿态控制律设计

传统的优化算法只能针对给定控制律的指定参数进行优化.机器学习的方法,不仅进化参数,而且可以按给定准则进化出卫星姿态控制律表达式.建立卫星姿态动力学模型及敏感器和执行机构的原理与误差模型,构成含噪声的单自由度的闭环数字仿真系统.统计一段时间内仿真结果的姿态精度和稳定度作为该控制律的适应度函数.针对姿态控制律选定合适的函数...