57 resultados para GENETIC ALGORITHM


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In this paper, common criterions about residual strength evaluation at home and abroad are generalized and seven methods are acquired, namely ASME-B31G, DM, Wes-2805-97, CVDA-84, Burdekin, Irwin and J integral methods. BP neural network are Combined with Genetic Algorithm (GA) named by modified BP-GA methods to successfully predict residual strength and critical pressure of injecting water, corrosion pipelines. Examples are shown that calculation results of every kind of method have great difference and calculating values of Wes-2805-97 criterion, ASME-B31G criterion, CVDA-84 criterion and Irwin fracture mechanics model are conservative and higher than, those of J integral methods while calculating values of Burdiken model and DM fracture mechanics model are dangerous and less than those of J integral methods and calculating values of modified BP-GA methods are close and moderate to those of J integral methods. Therefore modified BP-GA methods and J integral methods are considered better methods to calculate residual strength and critical pressure of injecting water corrosion pipelines

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An optimal feedback control of broadband frequency up-conversion in BBO crystal is experimentally demonstrated by shaping femto-second laser pulses based on genetic algorithm, and the frequency up-conversion efficiency can be enhanced by similar to 16%. SPIDER results show that the optimal laser pulses have shorter pulse-width with the little negative chirp than the original pulse with the little positive chirp. By modulating the fundamental spectral phase with periodic square distribution on SLM-256, the frequency up-conversion can be effectively controlled by the factor of about 17%. The experimental results indicate that the broadband frequency up-conversion efficiency is related to both of second harmonic generation (SHG) and sum frequency generation (SFG), where the former depends on the fundamental pulse intensity, and the latter depends on not only the fundamental pulse intensity but also the fundamental pulse spectral phase. (c) 2006 Elsevier B.V. All rights reserved.

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杜鹃属(Rhododendron L.)是中国种子植物中最大的属,其现代分布和分化中心是我国西南部的横断山区和东喜马拉雅地区。我国西部、西南部的云南、四川、西藏等地共有杜鹃达450种,仅特有种就有约300种。对杜鹃属分布的深入研究是横断山区生物多样性保护不可缺少的重要部分。 由于物种分布与环境因子之间存在着紧密的联系,利用环境因子作为预测物种分布模型的变量是当前最普遍的建模思路。但是绝大多数物种分布预测模型都遇到了难以解决的“高维小样本”问题――模型在标本数据不足时无法给出合理的预测,或者模型无法处理大量的环境变量。机器学习领域的理论和实践已经证明,基于结构风险最小化原理的支持向量机(Support Vector Machine, SVM)算法非常适合“高维小样本”的分类问题。为了探索其应用在物种分布预测问题上的可能性,本文创新性的实现了基于SVM算法的物种分布预测系统。然后,本文以30个杜鹃属(Rhododendron L.)物种为检验对象,利用其标本数据和11个1km的栅格环境变量图层作为模型变量,预测其在中国的潜在分布区。本文通过全面的模型评估——专家评估,ROC (Receiver Operator Characteristic)曲线和曲线下方面积AUC (Area Under the Curve)——来比较模型的性能。试验结果表明,我们所实现的以SVM为核心的物种分布预测系统无论在计算速度还是预测效果上都远远优于当前广泛使用的GARP (Genetic Algorithm for Rule-Set Prediction)预测系统。 之后,本文进一步探讨了SVM预测系统预测效果与环境变量维数和标本点个数的关系。试验结果表明,对于只有少量标本点的物种SVM的预测结果仍然具有相当的合理性。由此可见, SVM预测系统很好的解决了以前众多模型无法克服的稀有种和标本点稀少的物种的潜在分布区模拟问题。同时本文发现大的环境维数(高维)对于物种潜在分布区的预测有着决定性的作用,因此模型处理高维问题的能力显得至关重要。 最后,我们使用中国所有可获取的杜鹃属标本数据,以及83个1km的栅格环境变量图层,对400种杜鹃属物种的潜在分布区进行预测。根据预测出来的物种潜在分布区,我们得到了中国杜鹃属物种潜在多样性分布格局,特有物种潜在多样性分布格局,濒危杜物种潜在的分布格局,各亚属物种潜在分布格局,以及不同生活型物种潜在多样性分布格局。这些分布区图不仅可以对杜鹃属起源研究提供分析验证的条件,还能为其引种、保护和新种的搜寻提供有利的空间依据。

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地址: Chinese Acad Sci, Inst Semicond, State Key Lab Integrated Optoelect, Beijing 100083, Peoples R China

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结构性测试是标识测试用例的基本方法之一.由于程序语言的复杂性以及被测程序的多样性,自动生成结构测试数据的一种有效方法是根据程序运行结果指导生成过程,通过不断迭代,生成符合要求的测试数据集.提出一种基于Messy GA的结构测试数据自动生成方法,将测试覆盖率表示为测试输入集X的函数F(X),并利用Messy GA不需要染色体模式排列的先验知识即可进行优化求解的性质对F(X)的进行迭代寻优,进一步提高了搜索的并行性,并最终提高测试覆盖率.对一组标准测试程序和若干实际应用程序的实验结果表明,较之现有基于遗传算法的生成方法,该方法能够以更高的效率生成更高质量的测试数据,并适用于较大规模的程序.

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遗传算法是一种解决TSP问题的有效算法。文章提出了一种基于路径共同顺序的新型遗传操作方法,即首先寻找父辈的共有路径信息,然后构建后代,该方法缩小了搜索优解的范围,加快了优化过程的收敛速度。在此基础上针对TSP实例,实现了基于共同顺序的优化方法来解决小规模TSP问题,以及更有效的基于共同顺序的循环优化方法来解决大规模TSP问题。实验结果验证了该方法的有效性。

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在连续手写中文中,有偏旁部首离得较远的单字,单字之间可能会存在粘连、重叠。针对这种情况给出了一种基于识别得分提取单字的演化方法。对行笔划序列进行二进制编码,采用改进的遗传算法实现演化过程。染色体中连续0或1对应的笔划组成候选单字。用汉王手写单字识别器获取它们的识别得分,以单字个数较少和总的识别得分较大为优化目标。遗传算法中的变异概率和交叉概率自适应生成。测试结果表明该方法对连续手写中文具有较好的分割效果。

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Solutions for fiber-optical parametric amplifiers (FOPAs) with dispersion fluctuations are derived using matrix operators. On the basis of the propagation matrix product and the hybrid genetic algorithm, we have optimized and compared single- and dual-pump FOPAs with zero-dispersion-wavelength variations. The simulations prove that the design of FOPAs involves multimodal function optimization problems. The numerical results show that dual-pump FOPAs are highly sensitive to dispersion fluctuations whereas dispersion variations have less impact on the gain of single-pump FOPAs. To increase signal gain and reduce ripple, dual-pump FOPAs, instead of single-pump FOPAs, have to be carefully optimized with a suitable multisegment fiber structure rather than a one-segment fiber structure. The different combinations of multisegment fibers can provide highly different gain properties. The increase in gain is at the cost of the ripple.

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红发夫酵母分离于北美西部高山地区和日本一些岛屿上落叶树的渗出液中,因其所产主要色素为在水产养殖、食品和医药工业有广阔应用前景的虾青素而成为研究的热点。本论文对红发夫酵母Phaffia rhodozyma 的生长特性、培养参数与培养基组分对生长和虾青素积累的影响及其优化、虾青素合成的调节控制、虾青素的提取测定及红发夫酵母耐高温菌种的诱变进行了系统的研究。 虾青素是红发夫酵母的胞内色素,要对其进行分析首先要对红发夫酵母进行破壁处理,实验发现二甲亚砜是最有效的破壁溶剂,用氯仿和丙酮可以有效地把类胡萝卜素从二甲亚砜破壁后的红发夫酵母细胞中提取出来。 在固定摇床转速为200 rpm,温度为20 ℃的条件下,当种龄为36 h,以10%的接种量接入装液量为30 mL的250 mL三角瓶,初始pH为5.5时最有利于红发夫酵母的生长及类胡萝卜素的合成。 本实验中红发夫酵母最佳利用碳、氮源分别为蔗糖和蛋白胨,但蛋白胨价格昂贵,不适宜作单一氮源,因此使用硫酸铵和酵母膏作为复合氮源。 本论文采用了BP神经网络结合遗传算法的方法来优化红发夫酵母的发酵培养基,得到红发夫酵母发酵培养基的最佳配比为:蔗糖45.10 g/L、硫酸铵3.00 g/L、硫酸镁0.80 g/L、磷酸二氢钾1.40 g/L、酵母膏3.00 g/L、氯化钙0.50 g/L,使用优化后的培养基发酵类胡萝卜素产量达到8.20 mg/L,干重达到9.47 g/L,类胡萝卜素的产量比起始培养基提高了95.90%,干重提高了89.40%。 从代谢途径出发对红发夫酵母合成虾青素调控调控,选择谷氨酸、乙醇、VB1作为添加剂,通过正交试验设计得出三者添加水平分别为0.2 g/L,0.1% (V/V),10 mg/L时,类胡萝卜素产量提高了25.73%,达到了10.31mg/L。 通过上述优化培养,本论文中红发夫酵母的虾青素产量从1.33 mg/L提高到9.12 mg/L,产量提高了6.86倍;总类胡萝卜素产量从4.23 mg/L提高到10.31 mg/L,产量提高了2.44倍;细胞干重从5.00 g/L提高到11.35 g/L,提高了2.27倍,总体提高效果显著。 红发夫酵母属于中低温菌,本论文采用紫外复合诱变的方式,通过高温筛选,得到一株能在35 ℃下能生长的突变株,但所产类胡萝卜素中虾青素所占比例很小,可能是诱变改变了红发夫酵母的代谢途径,阻断了虾青素的合成。 Phaffia rhodozyma is a heterobasidiomyceteous yeast that was originally isolated from the slime fluxes of brich tree wounds in mountain regions of northern Japan and southern Alaska. Phaffia rhodozyma produces astaxanthin as its principal carotenoid pigment, which has potential applications in acquaculture, food and pharmaceutical industry. This paper researched ways to break cell, analysis of astaxanthin, characteristics of growth, culture parameters and the effects of components of medium on growth and astaxanthin formation , optimization of culture medium, control of astaxanthin synthesis and mutagenesis of Phaffia rhodozyma. It is necessary to disrupt the yeast cell for extracting astaxanthin considering the yeast accumulating carotenoids in cell. Dimethyisulphoxide was the most effective solvent for breaking the yeast cell; acetone and chloroform were effective to extract carotenoids out of the disrupted cell. The optimum pH for growth and carotenoids synthesis is 5.5, the optimum medium volume is 30 mL (in 250 mL flask), the optimum culture time of inoculum is 36 h, the optimum inoculum concentration is 10%. The research on culture medium showed: sucrose is the best one of 6 carbon sources for growth and astaxanthin synthesis. Peptone is the best nitrogen source for growth and astaxanthin synthesis. Uniform Design was used for trial design of the formula medium components, then back-propagation neural network was established to modeling the relationships between the carotenoid yield and the concentration of medium components. Genetic algorithm (GA) was used for global optimization of the model. The optimum combination of the medium was obtained: sucrose 45.10 g/L, ammonium sulfate 3.00 g/L, magnesium sulfate 0.80 g/L, potassium dihydrogen phosphate 1.40 g/L, yeast extract 3.00 g/L, calcium chloride 0.50 g/L. The yield of carotenoid reached 8.20 mg/L, which was 95.90% higher than that of the original medium. Glu, VB1 and ethanol were selected as fermentation addictives, after Orthogonal Test, the carotenoid contents increased by 25.73% when adding 0.16 g/L Glu, VB1 10 mg/L and ethanol 0.1% (V/V). After the above optimization, the astaxanthin content increased 6.86 folds, which is 9.12 mg/L. The carotenoids content increased 2.44 folds, which is 10.31 mg/L. The biomass increased 2.27 folds, which is 11.35 g/L. Phaffia rhodozyma grows in the mild temperature range of 0 to 27 ℃, in this work, a thermotolerant mutant was selected through UV-irradiation. It can grows at 35 ℃, and showed increased carotenoid content. The optimal growth temperature for this mutant is 30 ℃. But the mutant can only produce carotenoids with little astaxanthin accumulation.

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A linear accelerator as a new injector for the SSC (Separated Sector Cyclotron) of the HIRFL (Heavy ton Research Facility Lanzhou) is being designed. The DTL (Drift-Tube-Linac) has been designed to accelerate U-238(34+) from 0.140 MeV/u to 0.97 MeV/u. To the first accelerating tank which accelerates U-238(34+) to 0.54 MeV/u, the approach of Alternating-Phase-Focusing (APF) is applied. The phase array is obtained by coupling optimization software Dakota and beam optics code LINREV. With the hybrid of Multi-objective Genetic Algorithm (MOGA) and a pattern search method, an optimum array of asynchronous phases is determined. The final growth, both transversely and longitudinally, can meet the design requirements. In this paper, the deign optimization of the APF DTL is presented.

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The explicit expression between composition and mechanical properties of silicone rubber was derived from the physics of polymer elasticity, the implicit expression among material composition, reaction conditions and reaction efficiency was obtained from chemical thermodynamics and kinetics, and then an implicit multi-objective optimization model was constructed. Genetic algorithm was applied to optimize material composition and reaction conditions, and the finite element method of cross-linking reaction processes was used to solve multi-objective functions, on the basis of which a new optimization methodology of crosslinking reaction processes was established. Using this methodology, rubber materials can be designed according to pre-specified requirements.

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The A(m) index and molecular connectivity index were used for studying the photoionization sensitivity of some organic compounds in gas chromatography. The analysis of structure-property relationship between the photoionization sensitivity of the compounds and the A(m) indices or molecular connectivity indices has been carried out. The genetic algorighm was used to build the correlation model in this field. The results demonstrate that the property of compounds can be described by both A(m) indices and molecular connectivity indices, and the mathematical model obtained by the genetic algorithm was better than that by multivariate regression analysis.

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In chemistry for chemical analysis of a multi-component sample or quantitative structure-activity/property relationship (QSAR/QSPR) studies, variable selection is a key step. In this study, comparisons between different methods were performed. These methods include three classical methods such as forward selection, backward elimination and stepwise regression; orthogonal descriptors; leaps-and-bounds regression and genetic algorithm. Thirty-five nitrobenzenes were taken as the data set. From these structures quantum chemical parameters, topological indices and indicator variable were extracted as the descriptors for the comparisons of variable selections. The interesting results have been obtained. (C) 2001 Elsevier Science B.V. All rights reserved.

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针对传统机器人加工路径规划采用示教再现方法很难适应复杂变化任务的问题 ,提出了基于遗传算法的路径规划方法 ,研究了遗传算法中的编码方式、交叉算子和变异算子的改进方法 .仿真实验表明 ,采用遗传算法进行机器人加工路径规划是可行的和有效的 .

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提出一种基于遗传算法的三维动态环境下的路径规划方法,通过对机器人的运动行为进行编码,将各种约束条件融入到遗传算法当中,规划出可实际应用的避障路径,仿真研究表明该方法是简单有效的。