000 03193nam a22004575i 4500
001 978-1-4419-9613-8
003 DE-He213
005 20140220083729.0
007 cr nn 008mamaa
008 110729s2011 xxu| s |||| 0|eng d
020 _a9781441996138
_9978-1-4419-9613-8
024 7 _a10.1007/978-1-4419-9613-8
_2doi
050 4 _aT58.8
072 7 _aTH
_2bicssc
072 7 _aTEC031000
_2bisacsh
072 7 _aTEC009020
_2bisacsh
082 0 4 _a658.26
_223
100 1 _aReddy, T. Agami.
_eauthor.
245 1 0 _aApplied Data Analysis and Modeling for Energy Engineers and Scientists
_h[electronic resource] /
_cby T. Agami Reddy.
264 1 _aBoston, MA :
_bSpringer US,
_c2011.
300 _aX, 660p. 313 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aModels, data analysis and decision making -- Probability concepts and probability distributions -- Data collection and preliminary data analysis -- Making statistical inferences from samples -- Estimation of linear model parameters using least squares -- Designed experiments and analysis of non-intrusive data -- Time series models -- Topics in optimization, parameter estimation and clustering methods -- Inverse problems and illustrative examples -- Decision analysis and risk modeling.
520 _aApplied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability,statistics, experimental design, regression, model building, optimization, risk analysis and decision-making to actual engineering processes and systems. The text provides a formal structure that offers a basic, broad and unified perspective,while imparting the knowledge, skills and confidence to work in data analysis and modeling. This volume uses numerous solved examples, published 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. Applied Data Analysis and Modeling for Energy Engineers and Scientists is an ideal volume for researchers, practitioners, and senior level or graduate students working in energy engineering, mathematical modeling and other related areas.  
650 0 _aDistribution (Probability theory).
650 0 _aEngineering.
650 1 4 _aEnergy.
650 2 4 _aEnergy Efficiency (incl. Buildings).
650 2 4 _aEngineering Thermodynamics, Heat and Mass Transfer.
650 2 4 _aProbability Theory and Stochastic Processes.
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781441996121
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4419-9613-8
912 _aZDB-2-ENG
999 _c106082
_d106082