显而易见
发表于 2025-3-23 10:38:50
Design of Experiments,ted. Selected experimental design methods are discussed such as randomized block, Latin Squares and 2. factorial designs. The parallel between model building in a DOE framework and linear multiple regression is illustrated. Finally, this chapter addresses response surface methods (RSM) which allow a
毗邻
发表于 2025-3-23 16:38:29
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tenuous
发表于 2025-3-23 19:23:09
Classification and Clustering Methods,(s). In general, the number of clusters is not predefined and has to be gleaned from the data set. This and the fact that one does not have a training data set to build a model make clustering a much more difficult problem than classification. Two types of clustering techniques, namely partitional a
有常识
发表于 2025-3-23 23:14:43
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VEST
发表于 2025-3-24 03:41:43
Parameter Estimation Methods,ariables are large. Subsequently, another powerful and widely used estimation method, namely maximum likelihood estimation (MLE) is described, and its application to parameter estimation of probability functions and logistic models is presented. Also covered is parameter estimation of models non-lin
nostrum
发表于 2025-3-24 08:24:29
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Impugn
发表于 2025-3-24 14:23:29
Risk Analysis and Decision-Making, are clouded by uncertainty, and/or by having to meet multiple objectives; this chapter also presents basic concepts of multi-attribute modeling. The role of risk analysis and its various aspects are covered along with applications from various fields. General principles are presented in somewhat id
Gesture
发表于 2025-3-24 16:44:51
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Control-Group
发表于 2025-3-24 21:43:41
ed case studies from the author’s own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the “processes”along with the tools.978-1-4899-8636-8978-1-4419-9613-8
Nefarious
发表于 2025-3-25 02:08:26
The Social Study of Family Farmingbuildings. Next, it reviews fundamental notions of mathematical models illustrates them in terms of sensor response, and differentiates between forward or simulation models and inverse models. Subsequently, various issues pertinent to data analysis and associated uncertainty are described, and the d