Stochastic Optimization Methods
ዲሴም 2005 · Springer Science & Business Media
ኢ-መጽሐፍ
314
ገጾች
reportየተሰጡት ደረጃዎች እና ግምገማዎች የተረጋገጡ አይደሉም የበለጠ ለመረዳት
ስለዚህ ኢ-መጽሐፍ
Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.
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እንደ Kobo ኢ-አንባቢዎች ባሉ ኢ-ቀለም መሣሪያዎች ላይ ለማንበብ ፋይል አውርደው ወደ መሣሪያዎ ማስተላለፍ ይኖርብዎታል። ፋይሎቹን ወደሚደገፉ ኢ-አንባቢዎች ለማስተላለፍ ዝርዝር የእገዛ ማዕከል መመሪያዎቹን ይከተሉ።
