Short description: GUI Ant-Miner is a tool for extracting classification rules from data. It is an updated version of a data mining algorithm called Ant-Miner (Ant Colony-based Data Miner), which was proposed in 2002 by Parpinelli, Lopes and Freitas. GUI Ant-Miner differs from the original algorithm as follows: It has a friendly graphical user interface, makes possible the use of ant populations within the Ant Colony OPTIMIZATION (ACO) concept, data input file is standardized with the well-known Weka system, and runs on virtually any operating system since it is written in Java.
标签： classification description extracting Ant-Miner
上传时间： 2013-12-18
上传用户：gonuiln
genetic algorithm (or GA) is a search technique used in computing to find true or approximate solutions to OPTIMIZATION and search problems for function of 2 variable
标签： approximate algorithm computing technique
上传时间： 2017-07-25
上传用户：225588
Click is a modular router toolkit. To use it you ll need to know how to compile and install the software, how to write router configurations, and how to write new elements. Our ACM Transactions on Computer Systems paper, available from the Web site, will give you a feeling for what Click can do. Using the OPTIMIZATION tools under CLICKDIR/tools, you can get even better performance than that paper describes.
标签： compile install modular toolkit
上传时间： 2013-12-20
上传用户：wangchong
单个网页的最优化时搜索引擎优化的(seo)的细致工作，需要一页页的展开，所以，这个工作也是让人感到郁闷和不耐烦的事情，特别是要优化很多页面时，那种心情更是…….. 可是即时非常的郁闷，但，优化工作，每一页的优化都马虎不得，它直接关系到搜索引擎排名是否如意出现，因此，开始这个工作之前，是需要毅力和耐力的。 网站的优化也被称为页面优化（on-page OPTIMIZATION），就是通过改进页面的修饰性的因素，如标题、描述、题头文字等等，就是尽可能的当搜索引擎访问网站时，能让它迅速的抓住网页的要领，完整的将网页所发布的信息带走，而这些改进，都是围绕着关键词的使用来进行的。
标签： SEO
上传时间： 2015-03-01
上传用户：whf 13993638362
Convex OPTIMIZATION problem
标签： Convex OPTIMIZATION
上传时间： 2015-03-23
上传用户：飞来大货车
为工程优化技术的优秀代表，Isight 5.5软件由法国Dassault/Simulia公司出品，能够帮助设计人员、仿真人员完成从简单的零部件参数分析到复杂系统多学科设计优化（MDO, Multi-Disciplinary Design OPTIMIZATION）工作。Isight将四大数学算法（试验设计、近似建模、探索优化和质量设计）融为有机整体，能够让计算机自动化、智能化地驱动数字样机的设计过程，更快、更好、更省地实现产品设计。毫无疑问，以Isight为代表的优化技术必将为中国经济从“中国制造”到“中国创造”的转型做出应有的贡献！
标签： isight参数优化理论 实例
上传时间： 2016-02-27
上传用户：SteveWang0821
Computational models are commonly used in engineering design and scientific discovery activities for simulating complex physical systems in disciplines such as fluid mechanics, structural dynamics, heat transfer, nonlinear structural mechanics, shock physics, and many others. These simulators can be an enormous aid to engineers who want to develop an understanding and/or predictive capability for complex behaviors typically observed in the corresponding physical systems. Simulators often serve as virtual prototypes, where a set of predefined system parameters, such as size or location dimensions and material properties, are adjusted to improve the performance of a system, as defined by one or more system performance objectives. Such OPTIMIZATION or tuning of the virtual prototype requires executing the simulator, evaluating performance objective(s), and adjusting the system parameters in an iterative, automated, and directed way. System performance objectives can be formulated, for example, to minimize weight, cost, or defects; to limit a critical temperature, stress, or vibration response; or to maximize performance, reliability, throughput, agility, or design robustness. In addition, one would often like to design computer experiments, run parameter studies, or perform uncertainty quantification (UQ). These approaches reveal how system performance changes as a design or uncertain input variable changes. Sampling methods are often used in uncertainty quantification to calculate a distribution on system performance measures, and to understand which uncertain inputs contribute most to the variance of the outputs. A primary goal for Dakota development is to provide engineers and other disciplinary scientists with a systematic and rapid means to obtain improved or optimal designs or understand sensitivity or uncertainty using simulationbased models. These capabilities generally lead to improved designs and system performance in earlier design stages, alleviating dependence on physical prototypes and testing, shortening design cycles, and reducing product development costs. In addition to providing this practical environment for answering system performance questions, the Dakota toolkit provides an extensible platform for the research and rapid prototyping of customized methods and meta-algorithms
标签： OPTIMIZATION and Uncertainty Quantification
上传时间： 2016-04-08
上传用户：huhu123456
evolution computing 现在最火的一篇论文 Handling Multiple Objectives With Particle Swarm OPTIMIZATION
上传时间： 2016-07-01
上传用户：白水煮瓜子
蚁群算法（ant colony OPTIMIZATION, ACO），又称蚂蚁算法，是一种用来在图中寻找优化路径的机率型算法。
上传时间： 2016-08-21
上传用户：steveng
We consider the problem of target localization by a network of passive sensors. When an unknown target emits an acoustic or a radio signal, its position can be localized with multiple sensors using the time difference of arrival (TDOA) information. In this paper, we consider the maximum likelihood formulation of this target localization problem and provide efficient convex relaxations for this nonconvex OPTIMIZATION problem.We also propose a formulation for robust target localization in the presence of sensor location errors. Two Cramer-Rao bounds are derived corresponding to situations with and without sensor node location errors. Simulation results confirm the efficiency and superior performance of the convex relaxation approach as compared to the existing least squares based approach when large sensor node location errors are present.
标签： 传感器网络
上传时间： 2016-11-27
上传用户：xxmluo
