用遗传算法优化的约束背景双线性化方法处理含未知背景组分干扰的色谱二维谱图体系

数值遗传算法是全局优化方法.本文将其引入约束背景双线性化问题的优化求解过程,以避免陷入局部最优.用本方法处理了模拟数据和两个实际含未知背景干扰的色谱二维谱图体系,并探讨了如何提高遗传算法在优化平台区域的寻优速度,结果令人满意.     

基于混合型遗传算法的森林可燃物热解动力学参数优化方法

森林可燃物热解动力学参数的优化计算是构建综合热解模型的关键步骤。传统的基于梯度的优化方法收敛速度快但全局寻优能力不足,基于“生物进化理论”的遗传算法具有全局寻优能力但收敛速度慢。本研究首先探讨了单纯的遗传算法对初始值设置的依赖,发现设定合适的初始值能够稳定计算结果,加快算法的收敛速度。针对初始值未知的情况,本文提出了将单纯的遗传算法与迭代算法相结合构建混合型遗传算法的流程。然后以樟子松松枝为例,采用热重分析仪开展了森林可燃物热解实验。假设可燃物热解失重过程遵循三步一级平行反应模型,通过对比单纯遗传算法和混合型遗传算法的收敛过程,发现混合型遗传算法能够快速地获取全局最优的动力学参数,显著地提高遗传算法的优化性能。     

基于遗传算法优化的约束背景双线性分解算法用于改进高效液相色谱灰色分析体系的校正结果

该文采用约束背景双线性分解算法(CBBL)对以高效液相色谱(HPLC)方法分离分析的灰色分析体系进行了多元校正研究。针对采用包括CBBL在内的矩阵校正方法处理HPLC灰色分析体系的固有缺陷,即在相关组分的色谱保留时间重现性较低的情形下多元校正的结果不理想,对CBBL方法进行了改进,即将待测组分的浓度与组分的色谱保留时间同时作为优化的参量引入CBBL,并采用遗传算法(GA)优化CBBL,对于模拟的组分保留时间飘移严重的HPLC灰色分析体系及保留时间重现性不佳的多种酚类化合物组成的实际HPLC灰色分析体系进行了多元校正分析,成功克服了经典CBBL的固有缺陷,取得了较理想的多元校正结果。另外,该研究所建议的方法的校正结果也显著优于传统的残差双线性分解法(RBL)以及秩消失因子分析法(RAFA)。     

油脂降解培养基优化的遗传算法实验研究

我们运用遗传算法,首次对利用热带假丝酵母降解油脂的培养基优化问题进行了研究。通过5代实验完成了50个实验样本、6种培养基成分、64个浓度水平的优化任务。按照优化后的培养基组成,热带假丝酵母降解油脂的降解率为95．4％,比正交设计法提高了7．63％。实验结果表明：利用遗传算法可优化培养基成分含量,取得更好的效果;遗传算法是一种优于单因素试验法和正交设计法的新型、高效的培养基优化方法。     

遗传算法用于液相分离条件的优化

 在参考传统的优化方法的基础上 ,将遗传算法用于等度反相多元流动相分离条件的优化。详细介绍了基于线杂交和面变异的遗传算法的原理及其用于液相分离条件优化的过程。将此法用于 9种小肽的反相离子对分离条件的优化 ,经过 3次寻优操作 ,确定了最佳分离条件 ,实验保留值与预测值的平均相对偏差为0 75 % ,优化结果比较理想。     

退火遗传算法在液相色谱线性梯度分离条件优化中的应用

对于复杂样品的反相高效液相色谱分离,一般需在不同的流动相洗脱模式下进行。流动相线性梯度淋洗在分离方法发展中得到了广泛的应用。遗传算法作为一种新的全局优化搜索算法,已广泛应用于计算机科学等领域、作者也已成功地将遗传算法应用于液相色谱分离条件优化。本文将模拟退火演化方法引入遗传算法,并将退火遗     

中药指纹图谱的线性梯度分离条件的快速优化方法

提出了一种复杂样品线性梯度分离条件的快速优化方法.先通过4次线性梯度的初始实验,然后利用Excel规划求解工具获得准确的溶质保留方程系数.在此基础上利用网格搜索完成线性梯度的参数优化.整个优化策略通过对中药金银花提取液中各组分的分离得以验证.同时比较了网格搜索、遗传算法、遗传算法与规划求解联用的3种寻优算法.结果表明:3种方法优化结果接近,但运算时间有所差异.     

新课程背景下化学实验报告的优化设计

新课程背景下化学实验报告的设计重在探究,贵在引导,必须优化实验目的,完善实验教学的“三维”目标;优化实验器材,还学生自主选用的权利;优化实验过程,变验证性实验为探究性实验;优化问题和讨论,加强实验后的归纳和反思。     

遗传算法及其在分析化学中的应用

遗传算法是模拟生物群体遗传滨基本原理解决问题的一种高效优化方法。本文综述了遗传算法的基本原理、基本过程、发展现状及其在分析化学中的应用。     

铅和富里酸化学形态模拟计算方法的比较

在阳极溶出伏安法获限Ｐｂ和富里酸的溶出电流和电位偏移数值的基础上采用一种新的全局优化方法－遗传算法模拟计算了水体中铅和富里酸的化学形态，对３种计算络合常数的方法进行了比较，误差分析的结果表明：对所研究的体系，电流迭代－遗传算法比电位偏移－遗传算法获得的结果更可靠。     

用数值遗传算法计算配合物的稳定常数

提出了一种新的合局优化方法－数值遗传算法，该法可以处理连续变量参数的优化问题，能在很多局部较优中找到全局最优点，特别适合处理复杂的非线性问题，该法通过遗传操作不断改变个体和群体，使之逐渐适应环境，除新设计了交配和突变数值遗传操作外，本文还提出了记忆遗传操作，从而加快了运算的速度，采用这种算法，测定了新型化学发光材料的重要中间体－三氯水杨酸的酸常数及其与铜和铁的配合物的稳定常数。     

用数值遗传算法同时求解配合物稳定常数和各型体的纯光谱

用数值遗传算法同时求解配合物稳定常数和各型体的纯光谱张众杰，李通化，朱仲良，丛培盛，孙云平（同济大学化学系，上海，２０００９２）关键词数值遗传算法，二维数据，稳定常数利用滴定或光度法的测定数据，求解酸的离解常数和配合物的稳定常数是化学工作者十分熟悉并...     

利用减秩因子分析法同时优化确定化学反应级数和速率常数

通过对反应过程中在线测得的动力学谱-光谱二维数据矩阵进行主成分分析，可确定化学反应过程存在的组分数。提出用优化动力学参数-减秩因子分析法解析二维数据矩阵，对未知动力学模型的复杂反应可同时优化求解第一步反应的级数和速率常数。模拟二维数据验证了该方法的可行性。该方法用于高锰酸钾氧化溴化钠的反应过程中测得的二维数据的解析，结果表明：高锰酸钾的还原过程符合0级反应模型。     

A two-dimensional immune algorithm for resolution of overlapping two-way chromatograms

A two-dimensional immune algorithm is proposed for resolving the multicomponent overlapping two-way data matrices. The method is a development of the one-dimensional immune algorithm proposed elsewhere. When the inner product of vectors is expanded to the similar operation on matrices, the 1D immune algorithm can be expanded to the 2D algorithm which is suitable for the analysis of two-way data matrices. Both simulated and experimental two-way data sets were investigated by the method, and the results prove that the 2D immune algorithm is an effective tool for resolving the overlapping two-way signals. The effect of noise on the recoveries is also discussed.     

A two-dimensional immune algorithm for resolution of overlapping two-way chromatograms

A two-dimensional immune algorithm is proposed for resolving the multicomponent overlapping two-way data matrices. The method is a development of the one-dimensional immune algorithm proposed elsewhere. When the inner product of vectors is expanded to the similar operation on matrices, the 1D immune algorithm can be expanded to the 2D algorithm which is suitable for the analysis of two-way data matrices. Both simulated and experimental two-way data sets were investigated by the method, and the results prove that the 2D immune algorithm is an effective tool for resolving the overlapping two-way signals. The effect of noise on the recoveries is also discussed.     

New method for parallel computation of Hessian matrix of conformational energy function in internal coordinates

A new algorithm for parallel calculation of the second derivatives (Hessian) of the conformational energy function of biomolecules in internal coordinates is proposed. The basic scheme of this algorithm is the division of the entire calculation of the Hessian matrix (called "task") into subtasks and the optimization of the assignment of processors to each subtask by considering both the load balancing and reduction of the communication cost. A genetic algorithm is used for this optimization considering the dependencies between subtasks. We applied this method to a glutaminyl transfer RNA (Gln-tRNA) molecule for which the scalability of our previously developed parallel algorithm was significantly decreased when the large number of processors was used. The speedup for the calculation was 32.6 times with 60 processors, which is considerably better than the speedup for our previously reported parallel algorithm. The elapsed time for the calculation of subtasks, data sending, and data receiving was analyzed, and the effect of the optimization using the genetic algorithm is discussed.     

用数值遗传算法改进非线性PLS法进行构效关系研究

将数值遗传算法同非线性ＰＬＳ结合，改进和完善了非线性ＰＬＳ，推导了指数，对数，倒数和Ｓｉｇｍｏｉｄ函数的公式，构造了可以处理多种非线性函数关系的算法，可用于解决复杂的结构与性能相互关系。     

A Novel Preprocessing Algorithm for Three-Way HPLC Data

Orthogonal signal correction (OSC) was a data preprocessing algorithm. It ensured that the filtered information was irrelevant to concentration data while using it to filter the noise from the original data. This paper extended the OSC application range from two-way data to three-way data. Two drug data sets, Enoxacin, Norfloxacin, Ciprofloxacin and Betamethasone, cortisone acetate, prednisone acetate, showed that the application of the OSC algorithm to three-way HPLC data was feasible and needed further research.     

Resolution of the Embedded Chromatographic Peaks by Modified Orthogonal Projection Resolution and Entropy Maximization Method

ABSTRACT

The embedded chromatographic peaks usually can not be completely resolved by conventional multivariate resolution methods. The resolution condition of a certain component in two-way data is first reviewed. A modified orthogonal projection resolution (OPR) algorithm and new entropy maximization (EM) method are then proposed to resolve embedded chromatographic peaks in this paper. The modified OPR algorithm performs more precisely than conventional orthogonal projection resolution algorithm in resolving the chromatography of minor peak. The entropy criterion defined on the differential chromatography could obtain an approximate solution in resolution of the major chromatographic peak. Simulated and real data show that the modified OPR and entropy maximization (EM) methods perform well in solving the embedded problem.     

The role of CH/pi interaction in the stabilization of less-soluble diastereomeric salt crystals

Enantiopure 2-naphthylglycolic acid (NGA) and cis-1-aminobenz[f]indan-2-ol (ABI) were rationally designed as new resolving agents on the model of mandelic acid (MA) and cis-1-aminoindan-2-ol (AI), respectively. As expected, NGA and ABI showed superior chiral recognition ability to racemates, compared with MA and AI. In order to clarify any factors governing the chiral recognition abilities of NGA and ABI, the crystal structures of their less- and more-soluble diastereomeric salts were determined by X-ray crystallographic analyses and revealed that CH/pi interactions play an intrinsic role in chiral recognitions. A theoretical investigation was also performed with the periodic ab initio method by using the X-ray crystal structures of the less-soluble salt crystals with AI and ABI to find the unique properties of CH/pi interaction in the crystalline state, which largely contributed to the stabilization of the crystals.