《分析性写作》，介绍言简意赅： The popular, brief rhetoric that treats writing as thinking, WRITING ANALYTICALLY, Sixth Edition, offers a series of prompts that lead you through the process of analysis and synthesis and help you to generate original and well-developed ideas. The book's overall point is that learning to write well means learning to use writing as a way of thinking well. To that end, the strategies of this book describe thinking skills that employ writing. As you will see, this book treats writing as a tool of thought--a means of undertaking sustained acts of inquiry and reflection.
上传时间： 2015-08-22
上传用户：东大寺的
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
主要针对图像处理的opencv开源库应用
上传时间： 2017-02-12
上传用户：xiaojiwei98
EEMD代码学习，互相学习，共同进步。 EEMD代码学习，互相学习，共同进步。
上传时间： 2017-05-08
上传用户：1044109363@qq.com
CCS样式选择符，初学者，设计，DW，网页制作，大一作业 部分预览： <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> <title>CSS样式选择符</title> <style type="text/css"> body { background-image:url(images/%E8%83%8C%E6%99%AF%E5%9B%BE%E7%89%87.jpg); background-repeat:repeat; } .class1 { text-align:center; font-weight:bolder; } .class2 { font-family:"仿宋"; text-indent:8em; } .class3 { font-size:18px; font-family:"宋体"; text-indent:4em; } #id1 { font-family:Zombie, Verdana, "Comic Sans MS"; font-style:oblique; font-size:64px; } #id2 { font-family:"黑体"; font-size:36px; } #id3 { color:#F69; font-weight:bolder; text-shadow:#FCC; } </style> </head> <body> <table width="780" height="1555" border="0" cellspacing="0" align="center" bgcolor="#FFFFFF"> <tr height="30"> <td align="center"><img src="images/顶部图片.jpg" /></td> </tr>
上传时间： 2017-12-07
上传用户：圈圈Ace
DEEP learning paper DEEP learning paper DEEP learning paper DEEP learning paper DEEP learning paper DEEP learning paper DEEP learning paper DEEP learning paper
上传时间： 2018-06-13
上传用户：1203955829@qq.com
学习Vim的电子书。此书深浅适中，适合初学者循序渐进地入门，并逐步进入能力飞升的境界，可充分运用Vim制作脚本，搭建开发环境，以至可以完成相当种类的代码生成和数据处理。
标签： Learning Editors the and Vim vi
上传时间： 2018-11-23
上传用户：milo
深度学习，神经网络，卷积神经网络 Analysis of Deep Learning Models using CNN Techniques
上传时间： 2020-01-02
上传用户：wzy2020
Evolutionary Computation (EC) deals with problem solving, optimization, and machine learning techniques inspired by principles of natural evolution and ge- netics. Just from this basic definition, it is clear that one of the main features of the research community involved in the study of its theory and in its applications is multidisciplinarity. For this reason, EC has been able to draw the attention of an ever-increasing number of researchers and practitioners in several fields.
标签： Applications Evolutionary Computing of
上传时间： 2020-05-26
上传用户：shancjb
This introduction takes a visionary look at ideal cognitive radios (CRs) that inte- grate advanced software-defined radios (SDR) with CR techniques to arrive at radios that learn to help their user using computer vision, high-performance speech understanding, global positioning system (GPS) navigation, sophisticated adaptive networking, adaptive physical layer radio waveforms, and a wide range of machine learning processes.
标签： Technology Cognitive Radio
上传时间： 2020-05-26
上传用户：shancjb
