15 resultados para Genetic algorithms

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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Plasma equilibrium geometry has a great influence on the confinement and magnetohydrodynamic stability in tokamaks. The poloidal field (PF) system of a tokamak should be optimized to support the prescribed plasma equilibrium geometry. In this paper, a genetic algorithm-based method is applied to solve the optimization of the positions and currents of tokamak PF coils. To achieve this goal, we first describe the free-boundary code EQT Based on the EQT code, a genetic algorithm-based method is introduced to the optimization. We apply this new method to the PF system design of the fusion-driven subcritical system and plasma equilibrium geometry optimization of the Experimental Advanced Superconducting Tokamak (EAST). The results indicate that the optimization of the plasma equilibrium geometry can be improved by using this method.

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Genetic Algorithms (GAs) were used to design triangular lattice photonic crystals with large absolute band-gap. Considering fabricating issues, the algorithms represented the unit cell with large pixels and took the largest absolute band-gap under the fifth band as the objective function. By integrating Fourier transform data storage mechanism, the algorithms ran efficiently and effectively and optimized a triangular lattice photonic crystal with scatters in the shape of 'dielectric-air rod'. It had a large absolute band gap with relative width (ratio of gap width to midgap) 23.8%.

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We used Plane Wave Expansion Method and a Rapid Genetic Algorithm to design two-dimensional photonic crystals with a large absolute band gap. A filling fraction controlling operator and Fourier transform data storage mechanism had been integrated into the genetic operators to get desired photonic crystals effectively and efficiently. Starting from randomly generated photonic crystals, the proposed RGA evolved toward the best objectives and yielded a square lattice photonic crystal with the band gap (defined as the gap to mid-gap ratio) as large as 13.25%. Furthermore, the evolutionary objective was modified and resulted in a satisfactory PC for better application to slab system.

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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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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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According to the specific property of respective phases in copper ore, optimal extracting condition for, tour phases of copper with five infusion was examined. After a series of experiments, for example, different weight Of sample, artificial mixed single phases sample and repeated experiment, the extracting ratio constants foil all phases in different infusions were obtained. The mathematical model which is on the basis of the stable extracting constant is established. Based on the purpose-control genetic algorithms, we only need to determine the total copper in the sample in different infusions under the selected condition, then the value of respective phase could be calculated. The-relative standard deviation are (%) free oxidized copper phase:1.5, conjunction oxidized copper phase: 17.6,, secondary copper sulfide phase: 1.9, primary copper sulfide phase : 2.7,total copper: 0.8.

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为提高理性遗传算法遗传信息的完备性、算法全局收敛性以及算法的整体结构,给出了一个更一般化的理性算子和算法结构,证明了算法的全局收敛性.理论分析和在运动规划问题中的应用结果验证了理性遗传算法的有效性.

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以模糊推理和遗传算法为基础,提出了一种新的具有不完全微分的最优PID控制器的设计方法,该控制器由离线和在线两部分组成,在离线部分,以系统响应的超调量、上升时间以及调整时间为性能指标,利用遗传算法搜索出一组最优的PID参数Kp^*、Ti^*和Td^*,作为在线部分调整的初始值,在在线部分,一个专用的PID参数优化程序以离线部分获得Kp^*、Ti^*和Td^*为基础,根据系统当前的误差e和误差变化率e^.,通过一个模糊推理系统在线调整系统瞬态响应的PID参数,以确保系统的响应具有最优的动态和稳态性能.该控制器已被用来控制由作者设计的智能仿生人工腿中的执行电机.计算机仿真结果表明,该控制器具有良好的控制性能和鲁棒性能。

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提出了一种基于模糊推理与遗传算法的最优PID控制器的设计方法,该控制器由离线和在线2部分组成,在离线部分,以系统响应的超调量、上升时间及调速时间为性能指标,利用遗传算法搜索出一组最优的PID参数Kp^*,Ti^*及Td^*,为在线部分调节的初始值,在在线部分,采用一个专用的PID参数优化程序,以离线部分获得的Kp^*,Ti^*及Td^*为基础,根据系统当前的误差e和误差变化率·↑e,通过模糊推理在线调整系统瞬态响应的PID参数,以确保系统的响应具有最优的动态和稳态性能,计算机仿真结果表明,与传统的PID控制器相比,这种最优PID控制器具有良好的控制性能和鲁棒性能,可用于控制不同的对象和过程。

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采用改进GAs算法建立了求解大规模规划的资源分配模型.针对大规模资源分配问题的具体特点,设计了合适的GAs算子,并以实例验证了算法的合理性及有效性。

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许多问题最终可以归结为求解一个组合优化问题,GA是求解组合优化问题的一个强有力的工具,但遗传算法在应用中常出现收敛过慢和封闭竞争问题,本文提出贪心遗传算法。该算法的初始种群建立、交叉和变异等过程,都引入贪心选择策略指导搜索;移民操作向种群引进新的遗传物质,克服了封闭竞争缺点。贪心遗传算法可以避免早熟收敛并改进算法的性能,算法搜索起步阶段的效率是非常高的,本文通过TSP问题仿真试验证明了算法的有效性,在较少的计算量下,得到令人满意的结果。

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研究资源受限系统动态调度问题,针对时序约束问题提出一种并行遗传算法(PGA)。给出满足排序优先次序约束的一种基因编码方法;采用不破坏优先级可行性的交叉操作,并予以证明;建立一种并行处理机制,使搜索避免出现局优现象。在技术允许情况下,单机动态调度引入抢占式加工方式,会一定程度上提高系统的性能。通过仿真试验验证,并行GA算法可兼顾优化效果和计算效率,解决单机动态调度问题。

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As an important part of petroleum exploration areas in the west of China, the north part of Qaidam basin is very promising in making great progress for petroleum discovery. But there are still many obstacles to overcome in understanding the process of petroleum formation and evaluation of oil & gas potential because of the complexity of geological evolution in the study area. Based upon the petroleum system theory, the process of petroleum formation is analyzed and the potential of oil & gas is evaluated in different petroleum systems by means of the modeling approach. The geological background for the formation of petroleum systems and the consisting elements of petroleum systems are described in detail. The thickness of strata eroded is estimated by means of vitrinite reflectance modeling, compaction parameter calculating and thickness extrapolating. The buried histories are reconstructed using the transient compaction model, which combines of forward and reverse modeling. The geo-history evolution consists of four stages - sedimentation in different rates with different areas and slow subsidence during Jurassic, uplifting and erosion during Cretaceous, fast subsidence during the early and middle periods of Tertiary, subsidence and uplifting in alternation during the late period of Tertiary and Quaternary. The thermal gradients in the study area are from 2.0 ℃/100m to 2.6 ℃/100m, and the average of heat flow is 50.6 mW/m~2. From the vitrinite reflectance and apatite fission track data, a new approach based up Adaptive Genetic Algorithms for thermal history reconstruction is presented and used to estimate the plaeo-heat flow. The results of modeling show that the heat flow decreased and the basin got cooler from Jurassic to now. Oil generation from kerogens, gas generation from kerogens and gas cracked from oil are modeled by kinetic models. The kinetic parameters are calculated from the data obtained from laboratory experiments. The evolution of source rock maturation is modeled by means of Easy %Ro method. With the reconstruction of geo-histories and thermal histories and hydrocarbon generation, the oil and gas generation intensities for lower and middle Jurassic source rocks in different time are calculated. The results suggest that the source rocks got into maturation during the time of Xiaganchaigou sedimentation. The oil & gas generation centers for lower Jurassic source rocks locate in Yikeyawuru sag, Kunteyi sag and Eboliang area. The centers of generation for middle Jurassic source rocks locate in Saishenteng faulted sag and Yuka faulted sag. With the evidence of bio-markers and isotopes of carbonates, the oil or gas in Lenghusihao, Lenghuwuhao, Nanbaxian and Mahai oilfields is from lower Jurassic source rocks, and the oil or gas in Yuka is from middle Jurassic source rocks. Based up the results of the modeling, the distribution of source rocks and occurrence of oil and gas, there should be two petroleum systems in the study area. The key moments for these two petroleum, J_1-R(!) and J_2-J_3, are at the stages of Xiaganchaigou-Shangyoushashan sedimentation and Xiayoushashan-Shizigou sedimentation. With the kinetic midels for oil generated from kerogen, gas generated from kerogen and oil cracked to gas, the amount of oil and gas generated at different time in the two petroleum systems is calculated. The cumulative amount of oil generated from kerogen, gas generated from kerogen and gas cracked from oil is 409.78 * 10~8t, 360518.40 * 10~8m~3, and 186.50 * 10~8t in J_1-R(!). The amount of oil and gas generated for accumulation is 223.28 * 10~8t and 606692.99 * 10~8m~3 in J_1-R(!). The cumulative amount of oil generated from kerogen, gas generated from kerogen and gas cracked from oil is 29.05 * 10~8t, 23025.29 * 10~8m~3 and 14.42 * 10~8t in J_2-J_3 (!). The amount of oil and gas generated for accumulation is 14.63 * 10~8t and 42055.44 * 10~8m~3 in J_2-J_3 (!). The total oil and gas potential is 9.52 * 10~8t and 1946.25 * 10~8m~3.