生态金字塔粒子群优化算法及其在蛋壳薄膜胶原蛋白提取中的应用

发布时间：2018-01-13 02:06

本文关键词：生态金字塔粒子群优化算法及其在蛋壳薄膜胶原蛋白提取中的应用　出处：《太原理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：粒子群优化算法(Particle Swarm Optimization,PSO)最早由Eberhart和Kennedy在1995年提出,是一种在解决多种优化问题中得到广泛应用和发展的群智能算法。在粒子群优化算法中,优化问题的可能解被视为鸟群的食物目标,群体中的粒子通过信息共享和互助机制,引导整个群体朝着可能解的位置运动,在该过程中逐渐找到更好的全局最优解。PSO算法因具备结构简单、收敛迅速和易于编程实现的特性,获得研究者们的广泛关注,短短二十几年里迅速发展成进化算法的一个重要分支,在多个领域得到广泛应用。虽然学者们从不同方面对粒子群优化算法进行了改进,提出多种改进算法,并已经取得了一定的成果。但在解决高维复杂函数时仍然存在问题,如容易陷入局部最优、过早收敛以及低精度等,因此,在求解此类问题时,粒子群优化算法的性能仍有待改进和提高。针对上述问题,本文对粒子群算法的结构特点和搜索过程进行了深入分析和探讨,为克服粒子群优化算法处理高维复杂函数容易陷入局部最优和过早收敛的问题,提出了生态金字塔粒子群优化算法(EP-PSO),并将EP-PSO算法应用于蛋壳薄膜胶原蛋白的提取工艺中,优化响应面回归模型,确定最优的实验因素和水平。主要研究内容如下:1.为克服粒子群优化算法处理高维复杂函数容易陷入局部最优和早熟收敛的问题,本文提出生态金字塔粒子群优化算法(EP-PSO)。该算法引入生态金字塔系统,使粒子在搜索空间分等级、分子群寻优,有效提高了群体多样性;为增强算法的全局搜索能力,对处于停滞状态的个体极值和全局极值进行动态变异,达到扩大种群潜在搜索空间的效果。并选取了9种经典粒子群改进算法和15个标准测试函数对生态金字塔粒子群算法进行了对比试验分析,结果表明EP-PSO有着良好的寻优性能,能够得到较高精度解,具有较高的效率和可信度。2.随着生物科学发展进程的不断推进,胶原蛋白越来越受到大家的关注,本文将EP-PSO应用于蛋壳薄膜胶原蛋白提取工艺的优化中,通过仿真试验验证了EP-PSO的有效性,证明了氢氧化钠浓度、碱处理时间、酶浓度和水解时间四因素为影响从蛋壳薄膜中提取胶原蛋白的主要因素,得到四因素的适宜取值范围分别为:氢氧化钠浓度(A):0.7mol/L~0.8mol/L、碱处理时间(B):12h~20h、酶浓度(C):25U/mg~60U/mg和水解时间(D):36h~48h。
[Abstract]:Particle swarm optimization algorithm (Particle Swarm Optimization, PSO) first by Eberhart and Kennedy in 1995, is a kind of swarm intelligence algorithm to solve the application and development of a variety of optimization problems. In the particle swarm optimization algorithm, the optimization solution of the problem is regarded as the bird food, in the group the particle through information sharing and mutual assistance mechanism, guide the population toward the position of moving the possible solutions, and gradually find a better global optimal in the process solution for.PSO algorithm has the advantages of simple structure, fast convergence and easy programming features, received wide attention of researchers, only more than 20 years of rapid development into a an important branch of the evolutionary algorithm, is widely used in many fields. Although scholars from different aspects of the particle swarm optimization algorithm, proposed improved algorithm, and has achieved a The results. But there are still problems in solving high dimension complex functions, such as easy to fall into local optimum, premature convergence and low precision, therefore, in solving these problems, the performance of particle swarm optimization still needs to be improved. Aiming at the above problems, the structure characteristics and the search process of particle swarm algorithm the in-depth analysis and discussion, in order to overcome the particle swarm optimization algorithm for complex functions with high dimension is easy to fall into local optimum and premature convergence problem, put forward the ecological Pyramid particle swarm optimization algorithm (EP-PSO), and the EP-PSO algorithm is applied to the extraction process of eggshell thin film of collagen, optimization of response surface regression model, determine the experimental factors and the optimal level. The main contents are as follows: 1. in order to overcome the particle swarm optimization algorithm for complex functions with high dimension is easy to fall into local optimum and premature convergence problem, is proposed in this paper. Pyramid ecological particle swarm optimization (EP-PSO) algorithm is introduced. The ecological system of Pyramid, the particles in the search space level, molecular swarm optimization, to improve the population diversity; to enhance the global search capability of the algorithm, the dynamic variation of individual extremum and global extremum in a state of stagnation, to expand the population of potential search the effects of space. And select 9 kinds of classical particle swarm algorithm and 15 standard test functions are analyzed in comparison to the ecological Pyramid particle swarm algorithm, the results show that EP-PSO has a good optimization, we can get high precision solution with high efficiency and reliability of.2. with the progress of the development of biological science collagen, has attracted more and more attention, this article will optimize the application of EP-PSO in the eggshell film collagen extraction process, through simulation and experimental verification of the EP-P The effectiveness of SO, proved that the concentration of sodium hydroxide, alkali treatment time, enzyme concentration and hydrolysis time four factors as the main factors affecting the extraction of collagen from eggshell membrane, get the appropriate range of the four factors were: the concentration of sodium hydroxide (A): 0.7mol/L~0.8mol/L, alkali treatment time (B): 12h~20h (C, enzyme concentration: 25U/mg~60U/mg) and hydrolysis time (D): 36h~48h.

【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TQ936.2;TP18

【参考文献】