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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/response-surfaces-mixtures-model-building
课程评论：没有评论
课程名称：响应曲面、混合和模型构建 课程概述： 本课程深入探讨因子实验在因子筛选中的应用，旨在识别对响应具有主要影响的重要因子。一旦确定了这些重要因子，课程将着重于优化，即找出这些因子的最佳水平以获得最佳响应值。本课程提供了设计和优化工具，通过响应曲面框架来解答这些问题。相关主题还包括计算机实验的设计与分析、混合实验以及减少无法控制因素对响应中不希望变化的影响的实验策略。 课程大纲：
单元1：因子和分数因子设计的其他设计与分析主题
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单元2：回归模型
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单元3：响应曲面方法和设计
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单元4：稳健参数设计和过程鲁棒性研究
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Name:Unit 1: Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs
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Name:Unit 2: Regression Models
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Name:Unit 3: Response Surface Methods and Designs
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Name:Unit 4: Robust Parameter Design and Process Robustness Studies
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Factorial experiments are often used in factor screening.; that is, identify the subset of factors in a process or system that are of primary important to the response. Once the set of important factors are identified interest then usually turns to optimization; that is, what levels of the important factors produce the best values of the response. This course provides design and optimization tools to answer that questions using the response surface framework. Other related topics include design and analysis of computer experiments, experiments with mixtures, and experimental strategies to reduce the effect of uncontrollable factors on unwanted variability in the response.
