Готові списки джерел за темами / Optimization criterion

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Добірка наукової літератури з теми "Optimization criterion"

Автор: Grafiati
Опубліковано: 30 травня 2022
Оновлено: 31 травня 2022

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Статті в журналах з теми "Optimization criterion"

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Bengio, Yoshua. "Gradient-Based Optimization of Hyperparameters." Neural Computation 12, no. 8 (August 1, 2000): 1889–900. http://dx.doi.org/10.1162/089976600300015187.

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Many machine learning algorithms can be formulated as the minimization of a training criterion that involves a hyperparameter. This hyperparameter is usually chosen by trial and error with a model selection criterion. In this article we present a methodology to optimize several hyper-parameters, based on the computation of the gradient of a model selection criterion with respect to the hyperparameters. In the case of a quadratic training criterion, the gradient of the selection criterion with respect to the hyperparameters is efficiently computed by backpropagating through a Cholesky decomposition. In the more general case, we show that the implicit function theorem can be used to derive a formula for the hyper-parameter gradient involving second derivatives of the training criterion.
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2

Li, Shun Guo, and Hui Li. "Optimization Method of Hoisting Points Schemes Using Strain Energy Criterion." Applied Mechanics and Materials 88-89 (August 2011): 583–86. http://dx.doi.org/10.4028/www.scientific.net/amm.88-89.583.

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The optimization method of hoisting point’s schemes using strain energy criterion was studied in this paper. Firstly, the finite element model of complex steel truss hoisting was established and optimization analysis of hoisting point’s schemes for complex steel truss hoisting using strain energy criterion was accomplished. The calculation code which can make finite element analysis and optimization analysis of lifting point’s schemes based on strain energy criterion automatically. Then, lifting point’s schemes of complex steel truss hoisting were analyzed with calculation code mentioned above. The results indicate that, the optimization index using strain energy criterion is just strain energy criterion which is a more comprehensive and unidirectional index. Optimization analysis based on strain energy criterion changes optimization analysis of the lifting points schemes for complex steel truss hoisting from multi-target optimization into single-target optimization. The case study shows that this method is practicable and reliable and have good application prospect in hoisting points schemes optimization analysis with application to complex steel truss hoisting.
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3

Aneja, Preety. "Optimization and Efficiency Studies of Heat Engines: A Review." Journal of Advanced Research in Mechanical Engineering and Technology 07, no. 03 (October 7, 2020): 37–58. http://dx.doi.org/10.24321/2454.8650.202006.

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This review aims to study the various theoretical and numerical investigations in the optimization of heat engines. The main focus is to discuss the procedures to derive the efficiency of heat engines under different operating regimes (or optimization criteria) for different models of heat engines such as endreversible models, stochastic models, low-dissipation models, quantum models etc. Both maximum power and maximum efficiency operational regimes are desirable but not economical, so to meet the thermo-ecological considerations, some other compromise-based criteria have been proposed such as Ω criterion (ecological criterion) and efficient power criterion. Thus, heat engines can be optimized to work at an efficiency which may not be the maximum (Carnot) efficiency. The optimization efficiency obtained under each criterion shows a striking universal behaviour in the near-equilibrium regime. We also discussed a multi-parameter combined objective function of heat engines. The optimization efficiency derived from the multi-parameter combined objective function includes a variety of optimization efficiencies, such as the efficiency at the maximum power, efficiency at the maximum efficiency-power state, efficiency at the maximum criterion, and Carnot efficiency. Thus, a comparison of optimization of heat engines under different criteria enables to choose the suitable one for the best performance of heat engine under different conditions.
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4

Yoon, Jong-Min, Youngmyung Lee, Sang-Ok Park, Yong-Ha Han, and Gyung-Jin Park. "Crash optimization considering the head injury criterion." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 11 (October 29, 2018): 2879–90. http://dx.doi.org/10.1177/0954407018809298.

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In the crashworthiness of the vehicle, the head injury criterion is the most significant factor in the injury rate. Crash optimization has been employed to enhance the head injury criterion value. Since the head injury criterion value is calculated from acceleration, a surrogate-model-based crash optimization method is generally used. However, when the number of design variables increases, the cost of analysis increases extremely. Conceptual design such as topology optimization is difficult to apply since it has many design variables. A crash optimization methodology that considers the head injury criterion value is proposed based on the equivalent static loads method. The proposed method calculates the head injury criterion value using the finite difference method, and the channel frequency classes filter during linear static-response structural optimization with the equivalent static loads. Two practical large-scale problems are solved to validate the proposed method. For the headform impact on the upper interior, size optimization is carried out to satisfy the constraint on the head injury criterion value while the mass is minimized. Topology optimization is performed in the case of the hood headform impact. The material distribution of the inner panel in the hood is determined to minimize the head injury criterion value.
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Noghin, V. D. "Linear scalarization in multi-criterion optimization." Scientific and Technical Information Processing 42, no. 6 (December 2015): 463–69. http://dx.doi.org/10.3103/s014768821506009x.

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Cacho-Pérez, M. "2D frames optimization. Criterion: maximum stability." Applied Mathematical Modelling 46 (June 2017): 591–601. http://dx.doi.org/10.1016/j.apm.2017.02.002.

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Barsky, Eugene. "Conditions Providing Optimum Separation." Physical Separation in Science and Engineering 13, no. 3-4 (January 1, 2004): 153–63. http://dx.doi.org/10.1080/14786470412331328015.

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It is generally accepted in the field of powder technology that the most objective quality criterion for the optimization of separation is the Hancock criterion. In this article, use an analytical procedure to show disadvantages of this criterion. I also apply the same analysis to show the objectivity of the entropy criterion for the optimization of separation processes. A simple objective relationship for the optimization of separation processes of pourable materials is derived on the basis of the entropy criterion.
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Amirov, F. G. "Developing Criterion and Optimization of PAL System." Applied Mechanics and Materials 379 (August 2013): 244–49. http://dx.doi.org/10.4028/www.scientific.net/amm.379.244.

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Estri, Mutia Nur, Siti Rahmah Nurshiami, Rina Reorita, and Muhammad Okky Ibrohim. "PENENTUAN KRITERIA PENGHENTIAN ITERASI PADA ALGORITMA STROBERI." Jurnal Ilmiah Matematika dan Pendidikan Matematika 10, no. 1 (June 29, 2018): 27. http://dx.doi.org/10.20884/1.jmp.2018.10.1.2834.

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This paper discusses the application of two types of stopping criterion on the strawberry algorithm, which are stopping criteria based on iterative error and Cauchy criterion. Furthermore, the strawberry algorithm program is simulated on the optimization problem with the objective function is quadratic function. The simulation results on optimization problem with the objective function is quadratic function show that strawberry algorithm with stopping criterion based on Cauchy criterion has the best performance, when compared with stopping criterion based on iterative error and without stopping criterion
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10

Kukharchyk, A. G. "TRANSPORT TASK OF OPTIMIZATION OF COSTS WITH MULTIMODAL TRANSPORTATION." Economic innovations 19, no. 2(64) (July 7, 2017): 157–63. http://dx.doi.org/10.31520/ei.2017.19.2(64).157-163.

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In the article, the questions of cost optimization in solving the transport problem using mathematical models are considered. A group of criteria that have the greatest influence in solving the transport problem is determined. The mathematical model of the transport problem allows us to describe a multitude of situations that arise in multimodal transport. The formulation of the goal is optimization - a task more economical, on the other - knowledge of economic and mathematical methods can more effectively solve this problem. The rationale for choosing an optimization criterion is a procedure that cannot be fully formalized, it must be performed taking into account the performance of transport and the interrelationship between them. The common approach to choosing and justifying an optimization criterion is usually based on the following circumstance: as a criterion, only a measure that can be quantified is chosen. Most often, the justification of one indicator is taken as a criterion (characteristic) of the process, less often - a group of criteria, depending on which one speaks of tasks with one criterion or multicriteria. As can be seen from the above, each criterion of optimality has advantages and disadvantages, which most often result from the measure of the synthetic criterion, the difficulty of preparing information in the form an array of coefficients for unknowns in the target function, the narrower or broader scope of its application. The selection and justification of the optimization criterion are performed taking into account all these circumstances in each particular case. In conclusion, it should be noted that all of these criteria have meaning in such tasks, where the volume of traffic is predetermined.
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Дисертації з теми "Optimization criterion"

1

Song, Qiang. "Non-euler-lagrangian pareto-optimality conditions for dynamic multiple-criterion decision problems." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/24920.

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Rew, Dong-Won. "New feedback design methodologies for large space structures: a multi-criterion optimization approach." Diss., Virginia Polytechnic Institute and State University, 1987. http://hdl.handle.net/10919/49875.

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A few problems of designing structural control systems are addressed, considering optimization of three design objectives: state error energy, control energy and stability robustness. Tradeoff relationships among these selected design objectives are investigated by solving multiple objective optimization problems. Various measures of robustness (tolerance of model errors and disturbances) are also reviewed carefully in the present study and throughout the dissertation, robust control design methodologies are emphasized. Presented in the first part of the dissertation are three new feedback design algorithms: 1) a generalized linear-quadratic regulator (LQR) formulation, 11) a generalized LQR formulation based on Lyapunov stability theorem, and 111) an eigenstructure assignment method using Sylvester's equation. The performance of these algorithms for multi-criterion optimizations are compared by generating three dimensional surfaces of wh1ch d1splay the tradeoff among the three design objectives. In the second part, a noniterative robust e1genstructure assignment algorithm via a projection method is introduced. This algorithm produces a fairly well-conditioned eigenvector matrix and provides an excellent starting solution for optimizations of various design criteria. We also present a specialized version of the projection method for second order differential equatlons, wh1ch offers useful insights to design strategies in regards to conditioning (robustness) of the eigenvectors. Finally, to illustrate the ideas presented in this study, we adopt numerical examples in two sets: 1) 6th order mass-spring systems and 11) various reduced order models of a flexible system. The numerical results confirm that multi-criterion optimizations by using a minimum correction homotopy technique is a useful tool with significant potential for enhanced computer—aided design of control systems. The proposed robust eigenstructure assignment algorithm is successfully implemented and tested for a 24th reduced order model, which establishes the approach to be applicable to systems of at least moderate dimensionality. We show analytically and computationally that constraining closed—loop eigenvectors to equal open-loop eigenvectors generally does not lead to either optimal conditioning (robustness) of the closed-loop eigenvectors or minimum gain norm.
Ph. D.
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Abreu, Jean Faber Ferreira de. "Quantum games from biophysical Hamiltonians and a sub-neuronal optimization criterion of the information." Laboratório Nacional de Computação Científica, 2006. http://www.lncc.br/tdmc/tde_busca/arquivo.php?codArquivo=108.

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The Theory of Games is a mathematical formalism used to analyze conflicts between two or more parts. In those conflicts, each part has a group of actions (strategies) that aids them in the optimization of their objectives. The objectives of the players are the rewards (payoffs) given according to their chosen strategy. By quantizing a game, advantages in operational efficiency and in the stability of the game solutions are demonstrated. In a quantum game, the strategies are operators that act on an isolated system. A natural issue is to consider a game in an open system. In this case the strategies are changed by Kraus operators which represent a natural measurement of the environment. We want to find the necessary physical conditions to model a quantum open system as a game. To analyze this issue we applied the formalism of Quantum Operations on the Fröhlich system and we described it as a model of Quantum Game. The interpretation is a conflict among different configurations of the environment which, by inserting noise in the main system exhibits regimes of minimum loss of information. On the other hand, the model of Fröhlich has been used to describe the biophysical dynamics of the neuronal microtubules. By describing the model of Fröhlich in the Quantum Game formalism, we have shown that regimes of stability may exist even under physiological conditions. From the evolutionary point of view, the Theory of Games can be the key to describe the natural optimization at sub-neuronal levels.
A Teoria de Jogos (TJs) é um formalismo matemático usado para analisar situações de conflitos entre duas ou mais partes. Nesses conflitos, cada parte possui um conjunto de ações (estratégias) que auxilia na otimização de seus objetivos. Os objetivos dos jogadres são as recompensas (payoffs) que cada um recebe de acordo com a estratégia adotada. Ao se quantizar um jogo, mostra-se ganhos em eficiência operacional e ganhos na estabilidade das soluções. Em um jogo quântico (JQ), as estratégias são operadores que atuam num sistema isolado. Uma questão natural é considerar um jogo num sistema aberto. Nesta situação as estratégias são trocadas por operadores de Kraus que representam uma medida natural do ambiente. Nosso interesse é encontrar as condições físicas necessáriaas para modelarmos um sistema quântico aberto como um jogo. Para analisar essa questão aplicamos o formalismo de Operações Quânticas (OQs) sobre o sistema de Fröhlich e o apresentamos como um modelo de JQ. A interpretação é um conflito entre diferentes configurações do ambiente que, ao inserirem ruído no sistema principal, exibem regiões de mínima perda de informação. O modelo de Fröhlich vem sendo usado para descrever a dinâmica biofísica dos microtúbulos neuronais. Ao estruturamos o modelo de Fröhlich nos JQs, mostramos que as regiões de estabilidade podem existir sob condições fisiológicas. Usando o aspecto evolucionista, a TJs pode ser a chave para a descrição de processos de otimização da informação em nível sub-neuronal.
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Atutey, Olivia Abena. "Linear Mixed Model Selection via Minimum Approximated Information Criterion." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1594910831256966.

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Wang, Pei. "Simultaneously solving process selection, machining parameter optimization and tolerance design problems: A bi-criterion approach." Thesis, University of Ottawa (Canada), 2003. http://hdl.handle.net/10393/26544.

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The selection of right process, use of optimal machining parameters and specification of best tolerance parameters have been recognized by industry as key issues to ensure product quality and reduce production cost. The three issues have thus attracted a great deal of attention over last several decades. However, they are often addressed separately in existing publications. In reality, the three issues are closely interrelated. Analyzing the three issues in isolation will inevitably lead to inconsistent, infeasible, or conflicting decisions. To avoid the drawbacks, an integrated approach is proposed to jointly solve process selection, machining parameter optimization, and tolerance design problems. The integrated problem is formulated as a bi-criterion model to handle both tangible and intangible costs. The model is solved using a modified Chebyshev goal programming method to achieve a preferred compromise between the two conflicting criteria. The application of the proposed bi-criterion approach has been demonstrated by first using the single component single part feature case. The integrated approach is then extended to the multiple components multiple part features case (the assembly case). Examples are provided to illustrate the application of the two models and the solution procedure. The results have shown that the decisions on process selection, machining parameter selection and tolerance design can be made simultaneously using the models.
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Gorsky, Daniel A. "Niyama Based Taper Optimizations in Steel Alloy Castings." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1316191746.

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FIETE, ROBERT DEAN. "THE HOTELLING TRACE CRITERION USED FOR SYSTEM OPTIMIZATION AND FEATURE ENHANCEMENT IN NUCLEAR MEDICINE (PATTERN RECOGNITION)." Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/184160.

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The Hotelling trace criterion (HTC) is a measure of class separability used in pattern recognition to find a set of linear features that optimally separate two classes of objects. In this dissertation we use the HTC not as a figure of merit for features, but as a figure of merit for characterizing imaging systems and designing filters for feature enhancement in nuclear medicine. If the HTC is to be used to optimize systems, then it must correlate with human observer performance. In our first study, a set of images, created by overlapping ellipses, was used to simulate images of livers. Two classes were created, livers with and without tumors, with noise and blur added to each image to simulate nine different imaging systems. Using the ROC parameter dₐ as our measure, we found that the HTC has a correlation of 0.988 with the ability of humans to separate these two classes of objects. A second study was performed to demonstrate the use of the HTC for system optimization in a realistic task. For this study we used a mathematical model of normal and diseased livers and of the imaging system to generate a realistic set of liver images from nuclear medicine. A method of adaptive, nonlinear filtering which enhances the features that separate two sets of images has also been developed. The method uses the HTC to find the optimal linear feature operator for the Fourier moduli of the images, and uses this operator as a filter so that the features that separate the two classes of objects are enhanced. We demonstrate the use of this filtering method to enhance texture features in simulated liver images from nuclear medicine, after using a training set of images to obtain the filter. We also demonstrate how this method of filtering can be used to reconstruct an object from a single photon-starved image of it, when the object contains a repetitive feature. When power spectrums for real liver scans from nuclear medicine are calculated, we find that the three classifications that a physician uses, normal, patchy, and focal, can be described by the fractal dimension of the texture in the liver. This fractal dimension can be calculated even for images that suffer from much noise and blur. Given a simulated image of a liver that has been blurred and imaged with only 5000 photons, a texture with the same fractal dimension as the liver can be reconstructed.
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8

Strömberg, Eric. "Applied Adaptive Optimal Design and Novel Optimization Algorithms for Practical Use." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-308452.

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The costs of developing new pharmaceuticals have increased dramatically during the past decades. Contributing to these increased expenses are the increasingly extensive and more complex clinical trials required to generate sufficient evidence regarding the safety and efficacy of the drugs.  It is therefore of great importance to improve the effectiveness of the clinical phases by increasing the information gained throughout the process so the correct decision may be made as early as possible.   Optimal Design (OD) methodology using the Fisher Information Matrix (FIM) based on Nonlinear Mixed Effect Models (NLMEM) has been proven to serve as a useful tool for making more informed decisions throughout the clinical investigation. The calculation of the FIM for NLMEM does however lack an analytic solution and is commonly approximated by linearization of the NLMEM. Furthermore, two structural assumptions of the FIM is available; a full FIM and a block-diagonal FIM which assumes that the fixed effects are independent of the random effects in the NLMEM. Once the FIM has been derived, it can be transformed into a scalar optimality criterion for comparing designs. The optimality criterion may be considered local, if the criterion is based on singe point values of the parameters or global (robust), where the criterion is formed for a prior distribution of the parameters.  Regardless of design criterion, FIM approximation or structural assumption, the design will be based on the prior information regarding the model and parameters, and is thus sensitive to misspecification in the design stage.  Model based adaptive optimal design (MBAOD) has however been shown to be less sensitive to misspecification in the design stage.   The aim of this thesis is to further the understanding and practicality when performing standard and MBAOD. This is to be achieved by: (i) investigating how two common FIM approximations and the structural assumptions may affect the optimized design, (ii) reducing runtimes complex design optimization by implementing a low level parallelization of the FIM calculation, (iii) further develop and demonstrate a framework for performing MBAOD, (vi) and investigate the potential advantages of using a global optimality criterion in the already robust MBAOD.
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9

Wong, Steven. "Alternative Electricity Market Systems for Energy and Reserves using Stochastic Optimization." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/932.

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This thesis presents a model that simulates and solves power system dispatch problems utilizing stochastic linear programming. The model features the ability to handle single period, multiple bus, linear DC approximated systems. It determines capacity, energy, and reserve quantities while accounting for N-1 contingency scenarios (single loss of either generator or line) on the network. Market systems applying to this model are also proposed, covering multiple real-time, day-ahead, and hybrid versions of consumer costing, transmission operator payment, and generator remuneration schemes. The model and its market schemes are applied to two test systems to verify its viability: a small 6-bus system and a larger 66-bus system representing the Ontario electricity network.
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Xu, Rongxin. "Optimal design of a composite wing structure for a flying-wing aircraft subject to multi-constraint." Thesis, Cranfield University, 2012. http://dspace.lib.cranfield.ac.uk/handle/1826/7290.

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This thesis presents a research project and results of design and optimization of a composite wing structure for a large aircraft in flying wing configuration. The design process started from conceptual design and preliminary design, which includes initial sizing and stressing followed by numerical modelling and analysis of the wing structure. The research was then focused on the minimum weight optimization of the /composite wing structure /subject to multiple design /constraints. The modelling, analysis and optimization process has been performed by using the NASTRAN code. The methodology and technique not only make the modelling in high accuracy, but also keep the whole process within one commercial package for practical application. The example aircraft, called FW-11, is a 250-seat commercial airliner of flying wing configuration designed through our MSc students Group Design Project (GDP) in Cranfield University. Started from conceptual design in the GDP, a high-aspect-ratio and large sweepback angle flying wing configuration has been adopted. During the GDP, the author was responsible for the structural layout design and material selection. Composite material has been chosen as the preferable material for both the inner and outer wing components. Based on the derivation of structural design data in the conceptual phase, the author continued with the preliminary design of the outer wing airframe and then focused on the optimization of the composite wing structure. Cont/d.
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Книги з теми "Optimization criterion"

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Fonseca, Carlos M., Peter J. Fleming, Eckart Zitzler, Lothar Thiele, and Kalyanmoy Deb, eds. Evolutionary Multi-Criterion Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36970-8.

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Gaspar-Cunha, António, Carlos Henggeler Antunes, and Carlos Coello Coello, eds. Evolutionary Multi-Criterion Optimization. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15892-1.

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Gaspar-Cunha, António, Carlos Henggeler Antunes, and Carlos Coello Coello, eds. Evolutionary Multi-Criterion Optimization. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15934-8.

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Trautmann, Heike, Günter Rudolph, Kathrin Klamroth, Oliver Schütze, Margaret Wiecek, Yaochu Jin, and Christian Grimme, eds. Evolutionary Multi-Criterion Optimization. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54157-0.

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Takahashi, Ricardo H. C., Kalyanmoy Deb, Elizabeth F. Wanner, and Salvatore Greco, eds. Evolutionary Multi-Criterion Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19893-9.

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Purshouse, Robin C., Peter J. Fleming, Carlos M. Fonseca, Salvatore Greco, and Jane Shaw, eds. Evolutionary Multi-Criterion Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37140-0.

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Obayashi, Shigeru, Kalyanmoy Deb, Carlo Poloni, Tomoyuki Hiroyasu, and Tadahiko Murata, eds. Evolutionary Multi-Criterion Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-70928-2.

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Coello Coello, Carlos A., Arturo Hernández Aguirre, and Eckart Zitzler, eds. Evolutionary Multi-Criterion Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b106458.

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Deb, Kalyanmoy, Erik Goodman, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, and Patrick Reed, eds. Evolutionary Multi-Criterion Optimization. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12598-1.

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Ehrgott, Matthias, Carlos M. Fonseca, Xavier Gandibleux, Jin-Kao Hao, and Marc Sevaux, eds. Evolutionary Multi-Criterion Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01020-0.

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Частини книг з теми "Optimization criterion"

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Hemp, W. S. "A Michell Type Criterion for Shells." In Structural Optimization, 117–23. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1413-1_16.

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Barsky, Eugene. "Entropy of Composition: Optimization Criterion." In Critical Regimes of Two-Phase Flows with a Polydisperse Solid Phase, 169–95. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8838-3_9.

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Grafarend, E. W. "Criterion Matrices for Deforming Networks." In Optimization and Design of Geodetic Networks, 363–428. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-70659-2_15.

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Grierson, Donald E. "An Optimality Criterion Method for Structural Optimization." In Guide to Structural Optimization, 303–214. New York, NY: American Society of Civil Engineers, 1997. http://dx.doi.org/10.1061/9780784402207.apc.

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Lee, Hyei Kyung, Eric Paillet, and Werner Peeters. "A Consistency Criterion for Optimizing Defuzzification in Fuzzy Control." In Foundations of Generic Optimization, 403–31. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6668-9_12.

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Ziemba, William T., and Leonard C. MacLean. "Using the Kelly Criterion for Investing." In Stochastic Optimization Methods in Finance and Energy, 3–20. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9586-5_1.

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Lee, Hyei Kyung, Eric Paillet, and Werner Peeters. "An Asymptotic Consistency Criterion for Optimizing Defuzzification in Fuzzy Control." In Foundations of Generic Optimization, 433–56. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6668-9_13.

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8

Kowalewski, Adam. "On Some Optimization Problem with Non-Quadratic Criterion." In Analysis and Optimization of Differential Systems, 227–34. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-0-387-35690-7_23.

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Roy, Bernard. "Coherent Criterion Family and Decision Aiding in the Description Problematic." In Nonconvex Optimization and Its Applications, 215–35. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4757-2500-1_10.

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Bendsøe, Martin P., and Aharon Ben-Tal. "Truss Topology Optimization by a Displacements Based Optimality Criterion Approach." In Optimization of Large Structural Systems, 139–55. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-010-9577-8_6.

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Тези доповідей конференцій з теми "Optimization criterion"

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Deb, Kalyanmoy. "Evolutionary multi-criterion optimization." In the 12th annual conference comp. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1830761.1830909.

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Zalunina, Olga, Alla Kasych, Vita Ogar, Andrii Perekrest, Serhii Serhiienko, and Mykhailo Kushch-Zhyrko. "Energy System Control Optimization Criterion Development." In 2020 IEEE Problems of Automated Electrodrive. Theory and Practice (PAEP). IEEE, 2020. http://dx.doi.org/10.1109/paep49887.2020.9240869.

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Svejda, Martin. "New kinetostatic criterion for robot parametric optimization." In 2017 IEEE 4th International Conference on Soft Computing & Machine Intelligence (ISCMI). IEEE, 2017. http://dx.doi.org/10.1109/iscmi.2017.8279599.

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Atkeson, Christopher G., and Benjamin Stephens. "Multiple balance strategies from one optimization criterion." In 2007 7th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2007). IEEE, 2007. http://dx.doi.org/10.1109/ichr.2007.4813849.

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REW, D., and J. JUNKINS. "Multi-criterion approaches to optimization of linear regulators." In Astrodynamics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1986. http://dx.doi.org/10.2514/6.1986-2198.

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Ben Messaoud, Abdennacer, Samia Talmoudi Ben Aoun, and Moufida Lahmari Ksouri. "Multimodel approach: Validities' computation by local criterion optimization." In 2017 International Conference on Advanced Systems and Electric Technologies (IC_ASET). IEEE, 2017. http://dx.doi.org/10.1109/aset.2017.7983722.

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KIM, YOUNG JIN, and BYUNG RAE CHO. "A GLOBAL CRITERION APPROACH TO MULTIPLE RESPONSE OPTIMIZATION." In Proceedings of the 2nd International Workshop (AIWARM 2006). WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812773760_0087.

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Deb, Kalyanmoy. "Recent advances in evolutionary multi-criterion optimization (EMO)." In GECCO '17: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3067695.3067697.

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Armashova-Telnik, G. S. "Digitalization Of The Economy: Multi-Criterion Subsystem Optimization." In II International Conference on Economic and Social Trends for Sustainability of Modern Society. European Publisher, 2021. http://dx.doi.org/10.15405/epsbs.2021.09.02.187.

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Rawat, Anuj, and Shyama Kant Jha. "Analysis of model order reduction based on Mikhailov criterion." In 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT). IEEE, 2016. http://dx.doi.org/10.1109/iceeot.2016.7755377.

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Звіти організацій з теми "Optimization criterion"

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Stepanović, Milica, Dragoljub Bajić, and Dušan Polomši. Multicriteria Analysis and Optimization of Groundwater Control Systems with Variable Values of Criterion over Predefined Time Points. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, August 2021. http://dx.doi.org/10.7546/crabs.2021.08.09.

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Engau, A., and M. M. Wiecek. 2D Decision-Making for Multi-Criteria Design Optimization. Fort Belvoir, VA: Defense Technical Information Center, May 2006. http://dx.doi.org/10.21236/ada462566.

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Wiecek, Margaret M., Vijay Singh, and Vincent Blouin. Multi-Scenario Multi-Criteria Optimization in Engineering Design. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada462600.

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Pin, Francois G. Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning. Office of Scientific and Technical Information (OSTI), June 2003. http://dx.doi.org/10.2172/835388.

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Pin, Francois G. Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning. Office of Scientific and Technical Information (OSTI), June 2002. http://dx.doi.org/10.2172/835385.

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Pin, Grancois G. Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning. Office of Scientific and Technical Information (OSTI), June 2004. http://dx.doi.org/10.2172/839107.

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Rosocha, L. A., and R. A. Korzekwa. First report on non-thermal plasma reactor scaling criteria and optimization models. Office of Scientific and Technical Information (OSTI), January 1998. http://dx.doi.org/10.2172/658275.

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Knapp, Adam C., and Kevin J. Johnson. Using Fisher Information Criteria for Chemical Sensor Selection via Convex Optimization Methods. Fort Belvoir, VA: Defense Technical Information Center, November 2016. http://dx.doi.org/10.21236/ada640843.

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Zeng, Dajun, and Katia Sycara. Using Case-Based Reasoning as a Reinforcement Learning Framework for Optimization with Changing Criteria. Fort Belvoir, VA: Defense Technical Information Center, March 1995. http://dx.doi.org/10.21236/ada293602.

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Khayrullo, B., B. R. Akhmadov, N. I. Dzhabborov, and P. N. Dzhabborov. SUBSTANTIATION OF CRITERIA FOR ESTIMATING EFFICIENCY AND OPTIMIZATION PARAMETERS OF CULTIVATOR UNIT OPERATION MODES. Kishovarz, 2019. http://dx.doi.org/10.18411/0131-5226-2019-11118.

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