Vieweg+teubner Verlag
Shape Optimization Under Uncertainty from a Stochastic Programming Point of View (English, Harald Held)
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Specifications
| Publisher | Vieweg+teubner Verlag |
| Language | English |
| ISBN-13 | 9783834809094 |
| ISBN-10 | 3834809098 |
| Author | Harald Held |
Product Description
About the Book
he author applies a gradient method using the shape derivative and the topological gradient to minimize, e.g., the compliance and shows that the obtained solutions strongly depend on the initial guess, in particular its topology. The stochastic programming perspective also allows incorporating risk measures into the model which might be a more appropriate objective in many practical applications.
ISBN: 9783834809094
Book Insights
What You'll Learn
- ·In-depth exploration of topics covered in Shape Optimization Under Uncertainty from a Stochastic Programming Point of View
- ·Key concepts explained with clarity and practical examples
- ·Insights valuable for anyone studying or working in Vieweg+teubner Verlag
Who Should Read This
Students and professionals interested in Vieweg+teubner Verlag, as well as general readers looking to expand their knowledge.
Key Highlights
- ·Brand new physical book delivered across India
- ·15-day hassle-free return policy
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Shape Optimization Under Uncertainty from a Stochastic Programming Point of View is available in English on GlowMirror.
Who is the author of Shape Optimization Under Uncertainty from a Stochastic Programming Point of View?
Shape Optimization Under Uncertainty from a Stochastic Programming Point of View is authored by Harald Held.
Who published Shape Optimization Under Uncertainty from a Stochastic Programming Point of View?
Shape Optimization Under Uncertainty from a Stochastic Programming Point of View is published by Vieweg+teubner Verlag.
How many pages does Shape Optimization Under Uncertainty from a Stochastic Programming Point of View have?
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What is Shape Optimization Under Uncertainty from a Stochastic Programming Point of View about?
About the Book
he author applies a gradient method using the shape derivative and the topological gradient to minimize, e.g., the compliance and shows that the obtained solutions strongly depend on the initial guess, in particular its topology. The stochastic programming perspective also allows in...
Is Shape Optimization Under Uncertainty from a Stochastic Programming Point of View suitable for beginners?
Whether Shape Optimization Under Uncertainty from a Stochastic Programming Point of View is suitable for beginners depends on your background in Vieweg+teubner Verlag. Review the product description and specifications above for details on the target audience and difficulty level.
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