基于Downhill-Simplex算法的观测数据与作物生长模型同化方法研究

以夏玉米叶面积指数(LAI)、贮存器官干重(WSO)、地上总干重(TAGP)以及土壤水分含量(SM)为结合点,建立了基于Downhill-Simplex算法的作物生长模型WOFOST同化多种地面观测数据的一般方法或流程:开展观测数据与作物生长模型同化方法的正确性验证→利用Downhill-Simplex算法进行WOFOST模型的敏感性分析→选择敏感参数组合→通过优化效果确定待优化参数→利用新的观测数据对待优化参数进行优化,从而实现了观测数据与作物生长模型的同化,提升了模型的模拟能力。同化过程中遴选出的WOFOST模型的待优化参数主要包括比叶面积、最大CO2同化速率、初始地上部总干物重、根深最大日增量和初始土壤有效水等。

TLE orbit determination using simplex method

Two-Line Element(TLE)datasets are the only orbital data source of Earth-orbiting space objects for many civil users for their research and applications.The datasets have uneven qualities that may affect the reliability of the propagated positions of space objects using a single TLE.The least squares approach to use multiple TLEs also suffers from the poor quality of some TLEs,and reliable error information cannot be available.This paper proposes a simplex algorithm to estimate an optimal TLE from multiple TLEs and obtain the uncertainty of each element.It is a derivative-free technique that can deal with various orbit types.Experiments have demonstrated that using the TLE estimated from the simplex method is more reliable,stable,and effective than those from the batch least squares method.As an application example,the optimal TLE and its uncertainty are used for predicting the fallen area,keeping the actual fallen site in the prediction areas.

基于Downhill-Simplex算法的客舱照明优化设计方法研究

优化设计方法在照明设计中得到了广泛和深入的研究。针对民用飞机客舱照明设计方案,研究了Downhill-Simplex优化算法在客舱照明设计中的应用,编写了照明优化设计程序,通过客舱工作面照度均匀度优化设计实例对优化设计程序进行了验证。其中优化前客舱工作面照度均匀度为0.5,通过优化客舱工作面照度均匀度达到了0.8,表明优化算法是可靠的。本优化设计方法可用于飞机内外部照明、道路照明和投影设备等非成像光学设计领域。

Simplexmethod建模研讨

目的 Linear Programming的simplexmethod建模求最优解。方法应用simplexmethod.结果建立了LinearProgramming的数学模型并用simplexmethod求得了最优解.结论因为单纯形表反映了Linear Programming的所有信息,故用simplexmethod可简便地求得最优解.simplexmethod的基本思路是:先将Linear Programming用sim-plexmethod划为标准型,根据问题的标准型,进行初等行变换,将主元素列除主元素化为1外其余的元素均化为0,当基变量值全为非负时,问题就得到了最优解.

Global convergent algorithm for the bilevel linear fractional-linear programming based on modified convex simplex method

A global convergent algorithm is proposed to solve bilevel linear fractional-linear programming, which is a special class of bilevel programming. In our algorithm, replacing the lower level problem by its dual gap equaling to zero, the bilevel linear fractional-linear programming is transformed into a traditional sin- gle level programming problem, which can be transformed into a series of linear fractional programming problem. Thus, the modi- fied convex simplex method is used to solve the infinite linear fractional programming to obtain the global convergent solution of the original bilevel linear fractional-linear programming. Finally, an example demonstrates the feasibility of the proposed algorithm.

Estimation of mass transfer coefficient in ozone absorption by linear least square fitting and Simplex search methods

For physical ozone absorption without reaction,two parametric estimation methods,i.e.the common linear least square fitting and non-linear Simplex search methods,were applied,respectively,to determine the ozone mass transfer coefficient during absorption and both methods give almost the same mass transfer coefficient.While for chemical absorption with ozone decomposition reaction,the common linear least square fitting method is not applicable for the evaluation of ozone mass transfer coefficient due to the difficulty of model linearization for describing ozone concentration dissolved in water.The nonlinear Simplex method obtains the mass transfer coefficient by minimizing the sum of the differences between the simulated and experimental ozone concentration during the whole absorption process,without the limitation of linear relationship between the dissolved ozone concentration and absorption time during the initial stage of absorption.Comparison of the ozone concentration profiles between the simulation and experimental data demonstrates that Simplex method may determine ozone mass transfer coefficient during absorption in an accurate and high efficiency way with wide applicability.

Partial Pricing Rule Simplex Method with Deficient Basis

A new partial pricing column rule is proposed to the basis-deficiency-allowing simplex method developed by Pan.Computational results obtained with a set of small problems and a set of standard NETLIB problems show its promise of success.

PID Parameters for Tuning and Optimization of a Turbine EngineBased on the Simplex Search Method

A PID parameters tuning and optimization method for a turbine engine based on the simplex search method was proposed. Taking time delay of combustion and actuator into account, a simulation model of a PID control system for a turbine engine was developed. A performance index based on the integral of absolute error （IAE） was given as an objective function of optimization. In order to avoid the sensitivity that resulted from the initial values of the simplex search method, the traditional Ziegler-Nichols method was used to tune PID parameters to obtain the initial values at first, then the simplex search method was applied to optimize PID parameters for the turbine engine. Simulation results indicate that the simplex search method is a reasonable and effective method for PID controller parameters tuning and optimization.

Numerical Optimization of Sand Casting Parameters Using the Dantzig’s Simplex Method

This study adopts the Dantzig’s Simplex method to investigate optimization of sand casting parameters for optimum service performance. Some process variables and mechanical properties were adapted into the Simplex method. Aluminium alloy samples were cast, machined and subjected to a series of mechanical tests. From the body of data collected, linear functions and constraint equations were formulated and employed in the Dantzig’s Simplex method for optimization of process parameters. The results showed that the Simplex method can be adapted for studying performance opti- mization of castings.

Application of Simplex Method in the Radiotherapy Treatment

This work presents an application of the Simplex Method for solving an optimal planning problem for cancer treatment by radiotherapy. Linear Programming can aid the optimal planning for radiation therapy, where the concern is to apply a high enough radiation in the tumor while saving significantly healthy regions or critical organs.

Minimizing Complementary Pivots in a Simplex-Based Solution Method for a Quadratic Programming Problem

The paper presents an approach for avoiding and minimizing the complementary pivots in a simplex based solution method for a quadratic programming problem. The linearization of the problem is slightly changed so that the simplex or interior point methods can solve with full speed. This is a big advantage as a complementary pivot algorithm will take roughly eight times as longer time to solve a quadratic program than the full speed simplex-method solving a linear problem of the same size. The strategy of the approach is in the assumption that the solution of the quadratic programming problem is near the feasible point closest to the stationary point assuming no constraints.

Using the Simplex Method for a Type of Allocation Problems

In this study we discuss the use of the simplex method to solve allocation problems whose flow matrices are doubly stochastic. Although these problems can be solved via a 0 - 1 integer programming method, H. W. Kuhn [1] suggested the use of linear programming in addition to the Hungarian method. Specifically, we use the existence theorem of the solution along with partially total unimodularity and nonnegativeness of the incidence matrix to prove that the simplex method facilitates solving these problems. We also provide insights as to how a partition including a particular unit may be obtained.

Hybrid Improved Self-adaptive Differential Evolution and Nelder-Mead Simplex Method for Solving Constrained Real-Parameters

In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE （differential evolution） algorithm and exploitation capability of Nelder-Mead simplex method is presented （HISADE-NMS）. The DE has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters as number of particles （NP）, scaling factor （F） and crossover control （CR）, which are kept fixed throughout the entire evolutionary process. However, these control parameters are very sensitive to the setting of the control parameters based on their experiments. The value of control parameters depends on the characteristics of each objective function, therefore, we have to tune their value in each problem that mean it will take too long time to perform. In the new manner, we present a new version of the DE algorithm for obtaining self-adaptive control parameter settings. Some modifications are imposed on DE to improve its capability and efficiency while being hybridized with Nelder-Mead simplex method. To valid the robustness of new hybrid algorithm, we apply it to solve some examples of structural optimization constraints.

基于平纵组合的山区高速公路连续下坡路段行车安全评价方法

受制于地理和经济条件,山区高速公路在建设中不可避免会存在连续下坡路段,其中平纵组合路段对车辆稳定性和安全性提出了更高的要求。为分析山区高速公路连续下坡平纵组合路段的行车安全,利用西南山区高速公路数据,以80 km/h的设计速度,在连续下坡路段的不同位置、不同平纵组合工况构建了驾驶仿真实验。根据驾驶者的心理数据、车辆速度变化数据和横向偏移数据推出综合评价指标;将综合评价指标与平曲线半径和纵坡进行相关性分析;再通过累计频率图划分评价阈值;提出了基于平纵组合的连续下坡路段行车安全评价方法,并依托评价方法提出了连续下坡路段坡顶、坡中和坡底位置的平纵组合设计建议值;并以西南山区某高速公路为例对该评价方法进行了应用与验证。研究结果表明:该方法能为高速公路连续下坡路段的行车安全评价提供有效的参考依据。

融合历史记忆的单纯形引导鲸鱼优化算法

针对鲸鱼优化算法存在易陷入局部最优、收敛速度慢等缺点,提出一种融合历史记忆的单纯形引导鲸鱼优化算法。首先,为了避免初始化种群过于集中而陷入局部最优,提出了使用混沌映射对初始化种群进行改进,增加了种群多样性;其次,为了解决算法收敛精度低和收敛速度慢的问题,提出了融合历史记忆的单纯形引导策略,利用单纯形法和构建的历史记忆表求解出一个虚拟最优解作为下次随机搜索阶段的引导者,帮助种群在前期的勘探过程中进行细致地搜索;最后提出一种新的非线性参数策略,平衡算法的开发和勘探能力。将算法应用于12个典型的复杂函数优化问题,并与其他5种智能算法比较,实验结果表明,改进后的算法在收敛精度与速度方面均为第一,具有良好的全局搜索能力和局部开发能力。

单纯形法的复杂性与计算效率

给出了三个线性规划例子,及用单纯形法求解的过程,解释了求解线性规划的单纯形法为什么属于指数算法.

改进麻雀搜索算法的入侵检测特征选择

针对网络入侵检测所处理数据存在特征维数高、检测效率低、准确率不高的问题,提出一种改进麻雀搜索算法的特征选择方法,旨在减少特征冗余的同时提高分类准确率。利用改进Circle映射初始化种群;结合秃鹰搜索算法中的螺旋搜索方式更新发现者位置;采用单纯形法和小孔成像法优化适应度较差和最优麻雀的位置,提升算法的寻优能力。将该算法与其它算法在6个经典基准函数上进行对比测试,其在收敛速度、精度等方面均有提升。使用数据集CIC-IDS2017进行特征选择实验,平均保留了7.6个特征,准确率达到了99.5%,结果表明,该算法可以在保证准确率的同时有效降低特征维度。

基于谱方法和单纯形算法的一类偏微分方程参数反演研究

根据观测数据反演偏微分方程参数具有重要的应用价值。通过基于快速傅立叶变换的谱方法实现对偏微分方程快速高精度求解,与观测数据结合建立待优化的目标函数,再用带边界约束的Nelder-Mead单纯形优化方法进行参数反演。通过算例证实了算法的有效性。

Optimal pivot path of the simplex method for linear programming based on reinforcement learning

Based on the existing pivot rules,the simplex method for linear programming is not polynomial in the worst case.Therefore,the optimal pivot of the simplex method is crucial.In this paper,we propose the optimal rule to find all the shortest pivot paths of the simplex method for linear programming problems based on Monte Carlo tree search.Specifically,we first propose the SimplexPseudoTree to transfer the simplex method into tree search mode while avoiding repeated basis variables.Secondly,we propose four reinforcement learning models with two actions and two rewards to make the Monte Carlo tree search suitable for the simplex method.Thirdly,we set a new action selection criterion to ameliorate the inaccurate evaluation in the initial exploration.It is proved that when the number of vertices in the feasible region is C_(n)^(m),our method can generate all the shortest pivot paths,which is the polynomial of the number of variables.In addition,we experimentally validate that the proposed schedule can avoid unnecessary search and provide the optimal pivot path.Furthermore,this method can provide the best pivot labels for all kinds of supervised learning methods to solve linear programming problems.

THREE-DIMENSIONAL TRAJECTORY OPTIMIZATION WITH DIRECT METHOD

The principle of direct method used in optimal control problem is introduced. Details of applying this method to flight trajectory generation are presented including calculation of velocity and controls histories. And capabilities of flight and propulsion systems are considered also. Combined with digital terrain map technique, the direct method is applied to the three dimensional trajectory optimization for low altitude penetration, and simplex algorithm is used to solve the parameters in optimization. For the small number of parameters, the trajectory can be optimized in real time on board.