Titlebook: Applied Data Analysis and Modeling for Energy Engineers and Scientists; T. Agami Reddy,Gregor P. Henze Textbook 2023Latest edition The Edi

Adulterate

Applied Data Analysis and Modeling for Energy Engineers and Scientists978-3-031-34869-3

進(jìn)步

粗俗人

Mathematical Models and Data Analysis, Next, the distinction between simulation or forward (or well-defined or well-specified) problems, and inverse (or data-driven or ill-defined) problems is highlighted. This chapter introduces analysis approaches relevant to the latter which include calibrated forward models and statistical models id

TOXIN

審問

Paraplegia

VAN

Linear Regression Analysis Using Least Squares,ches, such as stepwise regression to automatically select the appropriate subset of regressors, called . or . are described. Subsequently, the inherent assumptions/conditions under which OLS is an optimal estimator are discussed. This is followed by an in-depth treatment of how model . can provide d

brother

Design of Physical and Simulation Experiments,ns and executing the test sequence where one variable is varied at a time, analyzing the data collected to verify (or refute) statistical hypotheses, and then drawing meaningful conclusions. Selected experimental design methods are discussed such as full and fractional factorial designs, and complet

寄生蟲

languor

Analysis of Time Series Data,rns using . with the time variable appearing as a regressor. Its strength lies in its ability to model the deterministic or structural components of the data in a relatively simple manner, and to provide reasonably accurate forecasts along with their confidence intervals. The . modeling approach is