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Books on the topic 'Optimization-based modeling'

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Published: 10 December 2022
Last updated: 29 January 2023

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1

Koziel, Slawomir, and Leifur Leifsson, eds. Surrogate-Based Modeling and Optimization. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7551-4.

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2

Harik, Vasyl Michael. Optimization of designs for nanotube-based scanning probes. Hampton, VA: ICASE, NASA Langley Research Center, 2002.

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3

Mathematical modeling and optimization: An essay for the design of computer-based modeling tools. Dordrecht: Kluwer Academic, 1999.

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4

Hürlimann, Tony. Mathematical Modeling and Optimization: An Essay for the Design of Computer-Based Modeling Tools. Boston, MA: Springer US, 1999.

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5

Bither, Cheryl Ann. A modeling strategy for large-scale optimization based on analysis and visualization principles. Monterey, Calif: Naval Postgraduate School, 1991.

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6

Efremov, German. Modeling of chemical and technological processes. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1090526.

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In an accessible form, the textbook presents the theoretical foundations of physical and mathematical modeling; considers the modeling of mass, heat and momentum transfer processes, the relationship and analogy between them; studies the theory of similarity, its application in modeling, models of the structure of flows in apparatuses. Experimental-statistical and experimental-analytical modeling methods are also described, which include "black box" methods, planning passive, active full and fractional factor experiments, and adjusting models based on the results of the experiment. At the same time, modeling of chemical reactors, methods of optimization of chemical-technological processes, their selection, comparison and application examples are considered. Examples of modeling and optimization of processes in chemical, petrochemical and biotechnology on a computer in Excel and MathCAD environments are given. The appendices provide the basics of working in the MathCAD environment and elements of matrix algebra. Meets the requirements of the Federal state educational standards of higher education of the latest generation. It is intended for bachelors who are trained for the chemical, petrochemical, food, textile and light industries. It can be useful for specialists and undergraduates, as well as for scientists, engineers and postgraduates dealing with the problem under consideration.
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7

Chemodurov, Vladimir, and Ella Litvinova. Physical and mathematical modeling of building systems. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1014191.

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Physical and mathematical modeling is widely used in scientific research. This is due to the fact that field experiments on real construction sites are often impossible to organize for various reasons. The material included in the textbook is a summary of the authors ' experience in the field of system analysis. In the first section, the regularities of physical modeling of the functioning of objects based on the similarity and dimension theorems are considered. The second section presents modern models and methods for choosing optimal solutions: linear, nonlinear, stochastic, and statistical. The third section deals with experimental methods of system optimization based on the theory of experimental planning. Meets the requirements of the federal state educational standards of higher education of the latest generation. For students of higher educational institutions studying in the direction of training 08.04.01 "Construction", and graduate students of higher educational institutions. It will be useful for specialists in the field of mathematical methods for the study of complex systems and their applications.
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8

de Sousa, Jorge Freire, and Riccardo Rossi, eds. Computer-based Modelling and Optimization in Transportation. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04630-3.

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9

Beulens, Adriaan Jacobus Maria, and Hans-Jürgen Sebastian, eds. Optimization-Based Computer-Aided Modelling and Design. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/bfb0040130.

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10

Vasil'eva, Natal'ya. Mathematical models in the management of copper production: ideas, methods, examples. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1014071.

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Presents the current status in modelling of metallurgical processes considered by the model the mathematical model used in the description of the processes of copper production and their classification. Set out a system of methods and models in the field of mathematical modeling of technological processes, including balance sheet, statistics, optimization models, forecasting models and predictive models. For specific technological processes are developed: the model of the balance of the cycle of pyrometallurgical production of copper, polynomial model for prediction of matte composition on the basis of the passive experiment, predictive model of quantitative estimation of the copper content in the matte based on fuzzy logic. Of interest to students, postgraduates, teachers of technical universities, engineers and research workers who use mathematical methods for processing of data of laboratory and industrial experiments.
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11

Ivanov, Anatoliy. Flexible modular assembly lines on a single structural basis. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1196558.

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The textbook discusses topical issues of automating the assembly of an extensive range of machine and instrument-making products based on highly efficient robotic reconfigurable systems of a new generation built on a single structural basis. The possibility of fast organization of automated assembly of new types of products, which is provided by the presence of a flexible basic set as part of the complex (line), is shown. A complete set of original technical means for basic and service operations of assembly and control of products is described. Analytical conditions of automatic assembly are given, and recommendations on optimization of design solutions and modeling of projected assembly systems are given. It is intended for students studying under the bachelor's degree programs, certified specialists and masters, teachers of technical universities, as well as designers, technologists and scientists dealing with the problem of complex assembly automation.
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12

Bock, Hans Georg. Model Based Parameter Estimation: Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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13

Koziel, Slawomir, and Leifur Leifsson. Surrogate-Based Modeling and Optimization: Applications in Engineering. Springer, 2013.

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14

Koziel, Slawomir, and Leifur Leifsson. Surrogate-Based Modeling and Optimization: Applications in Engineering. Springer, 2016.

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15

Koziel, Slawomir, and Leifur Leifsson. Surrogate-Based Modeling and Optimization: Applications in Engineering. Springer London, Limited, 2013.

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16

Hürlimann, Tony. Mathematical Modeling and Optimization: An Essay for the Design of Computer-Based Modeling Tools (Applied Optimization). Springer, 1999.

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17

Zhong, Zhixiong. Modeling, Control, Estimation, and Optimization for Microgrids: A Fuzzy-Model-Based Method. Taylor & Francis Group, 2019.

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18

Zhong, Zhixiong. Modeling, Control, Estimation, and Optimization for Microgrids: A Fuzzy-Model-Based Method. Taylor & Francis Group, 2019.

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19

Zhong, Zhixiong. Modeling, Control, Estimation, and Optimization for Microgrids: A Fuzzy-Model-Based Method. Taylor & Francis Group, 2019.

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20

Zhong, Zhixiong. Modeling, Control, Estimation, and Optimization for Microgrids: A Fuzzy-Model-Based Method. Taylor & Francis Group, 2019.

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21

Bian, Linkan. Laser-Based Additive Manufacturing of Metal Parts: Modeling, Optimization, and Control of Mechanical Properties. Taylor & Francis Group, 2022.

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22

Usher, John M., Linkan Bian, and Nima Shamsaei. Laser-Based Additive Manufacturing of Metal Parts: Modeling, Optimization, and Control of Mechanical Properties. Taylor & Francis Group, 2017.

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23

Laser-Based Additive Manufacturing of Metal Parts: Modeling, Optimization, and Control of Mechanical Properties. Taylor & Francis Group, 2017.

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24

Usher, John M., Linkan Bian, and Nima Shamsaei. Laser-Based Additive Manufacturing of Metal Parts: Modeling, Optimization, and Control of Mechanical Properties. Taylor & Francis Group, 2017.

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25

Usher, John M., Linkan Bian, and Nima Shamsaei. Laser-Based Additive Manufacturing of Metal Parts: Modeling, Optimization, and Control of Mechanical Properties. Taylor & Francis Group, 2017.

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26

Usher, John M., Linkan Bian, and Nima Shamsaei. Laser-Based Additive Manufacturing of Metal Parts: Modeling, Optimization, and Control of Mechanical Properties. Taylor & Francis Group, 2017.

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27

Sui, Yunkang, and Xirong Peng. Modeling, Solving and Application for Topology Optimization of Continuum Structures: ICM Method Based on Step Function. Elsevier Science & Technology Books, 2017.

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28

Floudas, Christodoulos A. Nonlinear and Mixed-Integer Optimization. Oxford University Press, 1995. http://dx.doi.org/10.1093/oso/9780195100563.001.0001.

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Filling a void in chemical engineering and optimization literature, this book presents the theory and methods for nonlinear and mixed-integer optimization, and their applications in the important area of process synthesis. Other topics include modeling issues in process synthesis, and optimization-based approaches in the synthesis of heat recovery systems, distillation-based systems, and reactor-based systems. The basics of convex analysis and nonlinear optimization are also covered and the elementary concepts of mixed-integer linear optimization are introduced. All chapters have several illustrations and geometrical interpretations of the material as well as suggested problems. Nonlinear and Mixed-Integer Optimization will prove to be an invaluable source--either as a textbook or a reference--for researchers and graduate students interested in continuous and discrete nonlinear optimization issues in engineering design, process synthesis, process operations, applied mathematics, operations research, industrial management, and systems engineering.
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29

Railsback, Steven F., and Bret C. Harvey. Modeling Populations of Adaptive Individuals. Princeton University Press, 2020. http://dx.doi.org/10.23943/princeton/9780691195285.001.0001.

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Ecologists now recognize that the dynamics of populations, communities, and ecosystems are strongly affected by adaptive individual behaviors. Yet until now, we have lacked effective and flexible methods for modeling such dynamics. Traditional ecological models become impractical with the inclusion of behavior, and the optimization approaches of behavioral ecology cannot be used when future conditions are unpredictable due to feedbacks from the behavior of other individuals. This book provides a comprehensive introduction to state- and prediction-based theory, or SPT, a powerful new approach to modeling trade-off behaviors in contexts such as individual-based population models where feedbacks and variability make optimization impossible. This book features a wealth of examples that range from highly simplified behavior models to complex population models in which individuals make adaptive trade-off decisions about habitat and activity selection in highly heterogeneous environments. The book explains how SPT builds on key concepts from the state-based dynamic modeling theory of behavioral ecology, and how it combines explicit predictions of future conditions with approximations of a fitness measure to represent how individuals make good—not optimal—decisions that they revise as conditions change. The resulting models are realistic, testable, adaptable, and invaluable for answering fundamental questions in ecology and forecasting ecological outcomes of real-world scenarios.
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30

Tuite, Cl´ıodhna, Michael O’Neill, and Anthony Brabazon. Economic and Financial Modeling with Genetic Programming. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.10.

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This chapter focuses on genetic programming (GP), a stochastic optimization and model induction technique. An advantage of GP is that the modeler need not select the exact parameters to be used in the model beforehand. Rather, GP can effectively search a complex model space defined by a set of building blocks specified by the modeler. This flexibility has allowed GP to be used for many applications. The chapter reviews some of the most significant developments using GP: forecasting, stock selection, derivative pricing and trading, bankruptcy and credit risk assessment, and agent-based and economic modeling. Conclusions reached by studies investigating similar problems do not always agree; however, GP has proved useful across a wide range of problem areas. Recent and future work is increasingly concerned with adapting genetic programming to more dynamic environments and ensuring that solutions generalize robustly to out-of-sample data, to further improve model performance.
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31

Rossi, Riccardo, and Jorge Freire Sousa. Computer-based Modelling and Optimization in Transportation. Springer, 2014.

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32

Rossi, Riccardo, and Jorge Freire Sousa. Computer-Based Modelling and Optimization in Transportation. Springer London, Limited, 2014.

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33

Zaheer Ul-Haq and Angela K. Wilson, eds. Frontiers in Computational Chemistry: Volume 6. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150368481220601.

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Frontiers in Computational Chemistry presents contemporary research on molecular modeling techniques used in drug discovery and the drug development process: computer aided molecular design, drug discovery and development, lead generation, lead optimization, database management, computer and molecular graphics, and the development of new computational methods or efficient algorithms for the simulation of chemical phenomena including analyses of biological activity. The sixth volume of this series features these six different perspectives on the application of computational chemistry in rational drug design: 1. Computer-aided molecular design in computational chemistry 2. The role of ensemble conformational sampling using molecular docking & dynamics in drug discovery 3. Molecular dynamics applied to discover antiviral agents 4. Pharmacophore modeling approach in drug discovery against the tropical infectious disease malaria 5. Advances in computational network pharmacology for Traditional Chinese Medicine (TCM) research 6. Progress in electronic-structure based computational methods: from small molecules to large molecular systems of biological significance
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34

Sui, Yunkang, and Xirong Peng. Modelling, Solving and Application for Topology Optimization of Continuum Structures: ICM Method Based on Step Function. Elsevier Science & Technology Books, 2017.

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35

LAND.TECHNIK 2022. VDI Verlag, 2022. http://dx.doi.org/10.51202/9783181023952.

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INHALT Electrical Agricultural Machines Structuring of electrified agricultural machine systems – Diversity of solutions and analysis methods .....1 GridCON2 – Development of a Cable Drum Vehicle Concept to Power 1MW Fully Electric Agricultural Swarms ..... 11 GridCON Swarm – Development of a Grid Connected Fully Autonomous Agricultural Production System ..... 17 Fully electric Tractor with 1000 kWh battery capacity ..... 23 Soil and Modelling The Integration of a Scientific Soil Compaction Risk Indicator (TERRANIMO) into a Holistic Tractor and Implement Optimization System (CEMOS) .....29 Identification of draft force characteristics for a tillage tine with variable geometry ..... 37 Calibration of soil models within the Discrete Element Method (DEM) ..... 45 Automation and Optimization of Working Speed and Depth in Agricultural Soil Tillage with a Model Predictive Control based on Machine Learning ..... 55 Synchronising machine adjustments of combine harvesters for higher fleet performance ..... 65 A generic approach to bridge the gap between route optimization and motion planning for specific guidance points o...
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36

Jäger, Willi, Hans Georg Bock, and Thomas Carraro. Model Based Parameter Estimation: Theory and Applications. Springer, 2013.

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37

Rannacher, Rolf, Willi Jäger, Hans Georg Bock, Thomas Carraro, Johannes P. Schlöder, and Stefan Körkel. Model Based Parameter Estimation: Theory and Applications. Springer, 2015.

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38

Optimization-based computer-aided modelling and design: Proceedings of the second working conference of the IFIP TC 7.6 Working Group, Dagstuhl, Germany, 1992. Leidschendam, The Netherlands: Lansa Publishing BV, 1994.

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39

M, Beulens A. J., Sebastian H. -J, and IFIP TC 7.6 Working Group. Working Conference,, eds. Optimization-based computer-aided modelling and design: Proceedings of the First Working Conference of the IFIP TC 7.6 Working Group, The Hague, The Netherlands, 1991. Berlin: Springer-Verlag, 1992.

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40

1948-, Beulens A. J., Sebastian H. J. (Hans-Jürgen), and IFIP TC 7.6 Working Group. Working Conference, eds. Optimization-based computer-aided modelling and design: Proceedings of the first working conference of the new IFIP TC 7.6 Working Group,The Hague, The Netherlands, 1991. Berlin: Springer-Verlag, 1992.

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41

Beulens, A. J. M. Optimization-Based Computer-Aided Modelling and Design: Proceedings of the First Working Conference of the Ifip Tc 7.6 Working Group the Hague, the (Lecture Notes in Control and Information Sciences). Springer, 1992.

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