Levent Aydin, Melih Savran
An Integrated Approach to Modeling and Optimization in Engineering and Science
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Levent Aydin, Melih Savran
An Integrated Approach to Modeling and Optimization in Engineering and Science
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An Integrated Approach to Modeling and Optimization in Engineering and Science is a technical book written with the aim to evaluate the modeling and design processes of engineering systems with an integrated approach.
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An Integrated Approach to Modeling and Optimization in Engineering and Science is a technical book written with the aim to evaluate the modeling and design processes of engineering systems with an integrated approach.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 280
- Erscheinungstermin: 24. Dezember 2024
- Englisch
- Abmessung: 229mm x 152mm
- ISBN-13: 9781032782799
- ISBN-10: 103278279X
- Artikelnr.: 71237575
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 280
- Erscheinungstermin: 24. Dezember 2024
- Englisch
- Abmessung: 229mm x 152mm
- ISBN-13: 9781032782799
- ISBN-10: 103278279X
- Artikelnr.: 71237575
Melih Savran received the B.S. degree in mechanical engineering from Manisa Celal Bayar University in 2013. He received the M.S. and Ph.D. degrees in mechanical engineering from ¿zmir Katip Çelebi University in 2017 and 2023, respectively. He continues to work as a researcher at the same university. His research areas include mechanics of solids, design and mathematical modeling, machine learning, stochastic optimization, and hybrid natural/synthetic composites. He has international publications on stochastic optimization and modeling in engineering, including book chapters, journal articles and conference papers. Levent AYDIN is an associate professor of mechanical engineering at ¿zmir Katip Çelebi University. He received his PhD degree in Mechanical Engineering from ¿zmir Institute of Technology in 2011. His main research interests are stochastic optimization, mechanics of solids, biocomposites, biosensors, advanced engineering mathematics, hybrid neuro-regression and artificial intelligence modeling. He has more than 100 international publications on stochastic optimization and modeling in engineering, including book chapters, journal articles and conference papers. He is also a consultant for many industrial R&D projects of international engineering firms. Dr. Ayd¿n is the founder of "optimization, modeling and applied math research group" (OMA-RG). Below are some examples of books that Dr. Ayd¿n is the editor and/or author of. * Designing Engineering Structures Using Stochastic Optimization Methods * Bioelectrochemical Interface Engineering * Hybrid Natural Fiber Composites * Vegetable Fiber Composites and their Technological Applications * Fiber Technology for Fiber-Reinforced Composites
Chapter 1. Introduction
Chapter 2. Design of Experiment, Mathematical Modeling, and Optimization
Chapter 3. Comparison of ANN and Neuro Regression Methods in Mathematical
Modeling
Chapter 4. Evaluation of R2 as Model Assessment Criteria
Chapter 5. Questioning The Adequacy Of Using Polynomial Structures
Chapter 6. The Effect of Using the Taguchi Method in Experimental Design on
Mathematical Modeling
Chapter 7. Comparison of Different Test and Validation Methods Used in
Mathematical Modeling
Chatper 8. Comparison of Different Model Assessment Criteria used in
Mathematical Modeling
Chapter 9. Comparison of the Effects of Experimental Design Methods on
Mathematical Modeling
Chapter 10.Special Functions in Mathematical Modeling
Chapter 2. Design of Experiment, Mathematical Modeling, and Optimization
Chapter 3. Comparison of ANN and Neuro Regression Methods in Mathematical
Modeling
Chapter 4. Evaluation of R2 as Model Assessment Criteria
Chapter 5. Questioning The Adequacy Of Using Polynomial Structures
Chapter 6. The Effect of Using the Taguchi Method in Experimental Design on
Mathematical Modeling
Chapter 7. Comparison of Different Test and Validation Methods Used in
Mathematical Modeling
Chatper 8. Comparison of Different Model Assessment Criteria used in
Mathematical Modeling
Chapter 9. Comparison of the Effects of Experimental Design Methods on
Mathematical Modeling
Chapter 10.Special Functions in Mathematical Modeling
Chapter 1. Introduction
Chapter 2. Design of Experiment, Mathematical Modeling, and Optimization
Chapter 3. Comparison of ANN and Neuro Regression Methods in Mathematical
Modeling
Chapter 4. Evaluation of R2 as Model Assessment Criteria
Chapter 5. Questioning The Adequacy Of Using Polynomial Structures
Chapter 6. The Effect of Using the Taguchi Method in Experimental Design on
Mathematical Modeling
Chapter 7. Comparison of Different Test and Validation Methods Used in
Mathematical Modeling
Chatper 8. Comparison of Different Model Assessment Criteria used in
Mathematical Modeling
Chapter 9. Comparison of the Effects of Experimental Design Methods on
Mathematical Modeling
Chapter 10.Special Functions in Mathematical Modeling
Chapter 2. Design of Experiment, Mathematical Modeling, and Optimization
Chapter 3. Comparison of ANN and Neuro Regression Methods in Mathematical
Modeling
Chapter 4. Evaluation of R2 as Model Assessment Criteria
Chapter 5. Questioning The Adequacy Of Using Polynomial Structures
Chapter 6. The Effect of Using the Taguchi Method in Experimental Design on
Mathematical Modeling
Chapter 7. Comparison of Different Test and Validation Methods Used in
Mathematical Modeling
Chatper 8. Comparison of Different Model Assessment Criteria used in
Mathematical Modeling
Chapter 9. Comparison of the Effects of Experimental Design Methods on
Mathematical Modeling
Chapter 10.Special Functions in Mathematical Modeling