共查询到20条相似文献,搜索用时 93 毫秒
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应用Matlab优化工具箱求解可靠度问题 总被引:2,自引:0,他引:2
根据可靠度指标的几何意义,将求解可靠度指标问题转化为求极小值的优化问题,利用Matlab优化工具箱求解,介绍了Matlab优化工具箱的使用,结合几个算例,计算了其可靠度指标,并与JC法进行了比较。 相似文献
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李奇 《电脑编程技巧与维护》2018,(7):120-122
Matlab凭借其出众的计算能力和丰富成熟的工具箱在研究领域被广泛使用.随着大数据时代待解决问题复杂性增加,智能优化方法广泛应用到数据处理中.介绍了几种智能算法以及Matlab内置的相应工具箱,并结合大数据时代数据处理所面临的问题阐述了群体智能算法的优越性. 相似文献
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基于Matlab遗传算法工具箱的函数优化问题求解 总被引:3,自引:0,他引:3
介绍了遗传算法的基本原理和求解流程,详细阐述了Matlab遗传算法工具箱的使用方法,并通过使用遗传算法工具箱对一个典型的函数优化问题进行求解,验证了该工具箱在解决函数优化问题上的有效性和实用性 相似文献
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本文介绍了遗传算法的基本原理,并重点分析了Matlab遗传算法工具箱的使用方法。在此基础上,给出了一个函数优化问题的实例,以验证Matlab遗传算法工具箱在解决基于遗传算法的函数优化问题上的有效性和实用性。 相似文献
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讨论了使用Excel Link插件链接Matlab与Excel的方法。利用这种方法,可以保证两个工作环境中数据的交换和同步更新。在实际应用中,配合Matlab的Financial工具箱,可简便迅速地进行金融分析领域的风险计算,回报率计算和最佳投资方案分析等工作。 相似文献
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基于MATLAB遗传算法优化工具箱的优化计算 总被引:24,自引:0,他引:24
采用Matlab语言编制的遗传算法工具箱(GAOT)可实现二进制编码和真值编码的模拟进化计算,此工具箱在遗传操作方面非常灵活。介绍了用遗传算法工具箱解决了连续优化问题和旅行商问题,并给出了两个实例。 相似文献
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数字滤波器可靠性与精确度高,使用简单方便,与模拟设备相比具有许多其所没有的诸多优点,已经被泛地应用于各个科学技术领域。Matlab具有强大的数据处理功能,丰富的工具箱为工程计算提供的极大的方便,也已被广泛地应用于工程计算中。该文基于Matlab提出了IIR滤波器的设计方案与相关应用。 相似文献
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Global derivative-free deterministic algorithms are particularly suitable for simulation-based optimization, where often the existence of multiple local optima cannot be excluded a priori, the derivatives of the objective functions are not available, and the evaluation of the objectives is computationally expensive, thus a statistical analysis of the optimization outcomes is not practicable. Among these algorithms, particle swarm optimization (PSO) is advantageous for the ease of implementation and the capability of providing good approximate solutions to the optimization problem at a reasonable computational cost. PSO has been introduced for single-objective problems and several extension to multi-objective optimization are available in the literature. The objective of the present work is the systematic assessment and selection of the most promising formulation and setup parameters of multi-objective deterministic particle swarm optimization (MODPSO) for simulation-based problems. A comparative study of six formulations (varying the definition of cognitive and social attractors) and three setting parameters (number of particles, initialization method, and coefficient set) is performed using 66 analytical test problems. The number of objective functions range from two to three and the number of variables from two to eight, as often encountered in simulation-based engineering problems. The desired Pareto fronts are convex, concave, continuous, and discontinuous. A full-factorial combination of formulations and parameters is investigated, leading to more than 60,000 optimization runs, and assessed by three performance metrics. The most promising MODPSO formulation/parameter is identified and applied to the hull-form optimization of a high-speed catamaran in realistic ocean conditions. Its performance is finally compared with four stochastic algorithms, namely three versions of multi-objective PSO and the genetic algorithm NSGA-II. 相似文献
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In this paper a methodology for designing and implementing a real-time optimizing controller for batch processes is proposed. The controller is used to optimize a user-defined cost function subject to a parameterization of the input trajectories, a nominal model of the process and general state and input constraints. An interior point method with penalty function is used to incorporate constraints into a modified cost functional, and a Lyapunov based extremum seeking approach is used to compute the trajectory parameters. The technique is applicable to general nonlinear systems. A precise statement of the numerical implementation of the optimization routine is provided. It is shown how one can take into account the effect of sampling and discretization of the parameter update law in practical situations. A simulation example demonstrates the applicability of the technique. 相似文献
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Multiobjective optimization of trusses using genetic algorithms 总被引:8,自引:0,他引:8
In this paper we propose the use of the genetic algorithm (GA) as a tool to solve multiobjective optimization problems in structures. Using the concept of min–max optimum, a new GA-based multiobjective optimization technique is proposed and two truss design problems are solved using it. The results produced by this new approach are compared to those produced by other mathematical programming techniques and GA-based approaches, proving that this technique generates better trade-offs and that the genetic algorithm can be used as a reliable numerical optimization tool. 相似文献
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Topology optimization has become very popular in industrial applications, and most FEM codes have implemented certain capabilities of topology optimization. However, most codes do not allow simultaneous treatment of sizing and shape optimization during the topology optimization phase. This poses a limitation on the design space and therefore prevents finding possible better designs since the interaction of sizing and shape variables with topology modification is excluded. In this paper, an integrated approach is developed to provide the user with the freedom of combining sizing, shape, and topology optimization in a single process. 相似文献
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Bio-inspired computation is one of the emerging soft computing techniques of the past decade. Although they do not guarantee optimality, the underlying reasons that make such algorithms become popular are indeed simplicity in implementation and being open to various improvements. Grey Wolf Optimizer (GWO), which derives inspiration from the hierarchical order and hunting behaviours of grey wolves in nature, is one of the new generation bio-inspired metaheuristics. GWO is first introduced to solve global optimization and mechanical design problems. Next, it has been applied to a variety of problems. As reported in numerous publications, GWO is shown to be a promising algorithm, however, the effects of characteristic mechanisms of GWO on solution quality has not been sufficiently discussed in the related literature. Accordingly, the present study analyses the effects of dominant wolves, which clearly have crucial effects on search capability of GWO and introduces new extensions, which are based on the variations of dominant wolves. In the first extension, three dominant wolves in GWO are evaluated first. Thus, an implicit local search without an additional computational cost is conducted at the beginning of each iteration. Only after repositioning of wolf council of higher-ranks, the rest of the pack is allowed to reposition. Secondarily, dominant wolves are exposed to learning curves so that the hierarchy amongst the leading wolves is established throughout generations. In the final modification, the procedures of the previous extensions are adopted simultaneously. The performances of all developed algorithms are tested on both constrained and unconstrained optimization problems including combinatorial problems such as uncapacitated facility location problem and 0-1 knapsack problem, which have numerous possible real-life applications. The proposed modifications are compared to the standard GWO, some other metaheuristic algorithms taken from the literature and Particle Swarm Optimization, which can be considered as a fundamental algorithm commonly employed in comparative studies. Finally, proposed algorithms are implemented on real-life cases of which the data are taken from the related publications. Statistically verified results point out significant improvements achieved by proposed modifications. In this regard, the results of the present study demonstrate that the dominant wolves have crucial effects on the performance of GWO. 相似文献
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本文介绍一种多元插值逼近和动态搜索轨迹相结合的全局优化算法.该算法大大减少了目标函数计算次数,寻优收敛速度快,算法稳定,且可获得全局极小,有效地解决了大规模非线性复杂动态系统的参数优化问题.一个具有8个控制参数的电力系统优化控制问题,采用该算法仅访问目标函数78次,便可求得最优控制器参数。 相似文献
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Sanjeev Kalanidhi 《Information Systems Frontiers》2001,3(4):465-470
The Internet has created a virtual upheaval in the structural features of the supply and demand chains for most businesses. New agents and marketplaces have surfaced. The potential to create value and enhance profitable opportunities has attracted both buyers and sellers to the Internet. Yet, the Internet has proven to be more complex than originally thought. With information comes complexity: the more the information in real time, the greater the difficulty in interpretation and absorption. How can the value-creating potential of the Internet still be realized, its complexity notwithstanding? This paper argues that with the emergence of innovative tools, the expectations of the Internet as a medium for enhanced profit opportunities can still be realized. Creating value on a continuing basis is central to sustaining profitable opportunities. This paper provides an overview of the value creation process in electronic networks, the emergence of the Internet as a viable business communication and collaboration medium, the proclamation by many that the future of the Internet resides in “embedded intelligence”, and the perspectives of pragmatists who point out the other facet of the Internet—its complexity. The paper then reviews some recent new tools that have emerged to address this complexity. In particular, the promise of Pricing and Revenue Optimization (PRO) and Enterprise Profit OptimizationTM (EPO) tools is discussed. The paper suggests that as buyers and sellers adopt EPO, the market will see the emergence of a truly intelligent network—a virtual network—of private and semi-public profitable communities. 相似文献
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SEO技术研究 总被引:4,自引:0,他引:4
范彦忠 《计算机应用与软件》2010,27(1):160-164
为了利用搜索引擎优化SEO(Search Engine Optimization)技术给网站带来高质量的流量并将其转化为商业利益,理解搜索引擎的算法和排名原理十分必要。通过对网站的结构优化、关键词优化、单页优化、防止被搜索引擎惩罚和挽救被惩罚网站等技术的研究,达到提高网站排名,实现网站的价值目的。 相似文献