Literatura académica sobre el tema "HYBRID OPTIMIZATION MODEL"
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Artículos de revistas sobre el tema "HYBRID OPTIMIZATION MODEL"
Xue, Li-hua y Yong-hua Li. "Hybrid optimization model of product concepts". Journal of Central South University of Technology 13, n.º 1 (febrero de 2006): 105–9. http://dx.doi.org/10.1007/s11771-006-0115-4.
Texto completoGao, Xiaoli, Yangfei Yuan, Jie Li y Weifeng Gao. "A Hybrid Search Model for Constrained Optimization". Discrete Dynamics in Nature and Society 2022 (28 de septiembre de 2022): 1–15. http://dx.doi.org/10.1155/2022/1190174.
Texto completoMiracle, D. Blandina, R. K. Viral, P. M. Tiwari y Mohit Bansal. "Hybrid Metaheuristic Model for Optimal Economic Load Dispatch in Renewable Hybrid Energy System". International Transactions on Electrical Energy Systems 2023 (6 de abril de 2023): 1–25. http://dx.doi.org/10.1155/2023/5395658.
Texto completoStevanović, Dejan, Mirjana Banković, Milica Pešić-Georgiadis y Lazar Stojanović. "Hybrid model for uncertainty assessment in open pit optimization". Tehnika 75, n.º 2 (2020): 161–71. http://dx.doi.org/10.5937/tehnika2002161s.
Texto completoSukheja, Deepak y Umesh Kumar Singh. "Novel Distributed Query Optimization Model and Hybrid Query Optimization Algorithm". International Journal of Computer Applications 75, n.º 17 (23 de agosto de 2013): 22–32. http://dx.doi.org/10.5120/13203-0461.
Texto completoRegitha, M. R., Dr Paul Varghese, Shailesh Sivan y Antony Nijo. "Handoff Delay Optimization Using Hybrid Prediction Model". International Journal of Networked and Distributed Computing 6, n.º 2 (2018): 99. http://dx.doi.org/10.2991/ijndc.2018.6.2.5.
Texto completoCahyandari, R., R. L. Ariany y Sukono. "Optimization of hybrid model on hajj travel". IOP Conference Series: Materials Science and Engineering 332 (marzo de 2018): 012042. http://dx.doi.org/10.1088/1757-899x/332/1/012042.
Texto completoFranco-Lara, E., N. Volk, T. Hertel, V. Galvanauskas y A. Lübbert. "Model-Supported Optimization of Recombinant Protein Production Using Hybrid Models". Chemie Ingenieur Technik 73, n.º 6 (junio de 2001): 654–55. http://dx.doi.org/10.1002/1522-2640(200106)73:6<654::aid-cite6543333>3.0.co;2-8.
Texto completoHe, Jian Feng y Xiao Xiong Jin. "Multiobjective Optimization of Hybrid Electrical Vehicle Powertrain Mounting System Using Hybrid Genetic Algorithm". Applied Mechanics and Materials 87 (agosto de 2011): 30–37. http://dx.doi.org/10.4028/www.scientific.net/amm.87.30.
Texto completoLi, Wenwei y Long Zhu. "Multi-objective Optimization Method for Hybrid Energy Storage Capacity of Wind Farm Based on Source-load Interaction". Journal of Physics: Conference Series 2418, n.º 1 (1 de febrero de 2023): 012054. http://dx.doi.org/10.1088/1742-6596/2418/1/012054.
Texto completoTesis sobre el tema "HYBRID OPTIMIZATION MODEL"
Sachs, Julia [Verfasser]. "Model-Based Optimization of Hybrid Energy Systems / Julia Sachs". Aachen : Shaker, 2016. http://d-nb.info/1101185112/34.
Texto completoWerner, Quentin. "Model-based optimization of electrical system in the early development stage of hybrid drivetrains". Thesis, Université de Lorraine, 2017. http://www.theses.fr/2017LORR0109.
Texto completoThis work analyses the challenges faced by the electric components for traction purpose in hybrid drivetrains. It investigates the components and their interactions as an independent entity in order to refine the scope of investigation and to find the best combinations of components instead of the best components combinations. Hybrid vehicle is currently a topic of high interest because it stands for a suitable short-term solution towards zero emission vehicle. Despite its advantages, it is a challenging topic because the components need to be integrated in a conventional drivetrain architecture. Therefore, the focus of this work is set on the determination of the right methods to investigate only the electric components for traction purpose. The aim and the contributions of this work lies thereby in the resolution of the following statement: Determine the sufficient level of details in modeling electric components at the system level and develop models and tools to perform dynamic simulations of these components and their interactions in a global system analysis to identify ideal designs of various drivetrain electric components during the design process. To address these challenges, this work is divided in four main parts within six chapters. First the current status of the hybrid vehicle, the electric components and the associated optimization methods and simulation are presented (first chapter). Then for each component, the right modeling approach is defined in order to investigate the electrical, mechanical and thermal behavior of the components as well as methods to evaluate their integration in the drivetrain (second to fourth chapter). After this, a suitable method is defined to evaluate the global system and to investigate the interactions between the components based on the review of relevant previous works (chapter five). Finally, the last chapter presents the optimization approach considered in this work and the results by analyzing different system and cases (chapter six). Thanks to the analysis of the current status, previous works and the development of the simulations tools, this work investigates the relationships between the voltage, the current and the power in different cases. The results enable, under the considered assumptions of the work, to determine the influence of these parameters on the components and of the industrial environment on the optimization results. Considering the current legislative frame, all the results converge toward the same observation referred to the reference systems: a reduction of the voltage and an increase of the current leads to an improvement of the integration and the performance of the system. These observations are linked with the considered architecture, driving cycle and development environment but the developed methods and approaches have set the basis to extend the knowledge for the optimization of the electric system for traction purpose. Beside the main optimization, special cases are investigated to show the influence of additional parameters (increase of the power, 48V-system, machine technology, boost-converter…) In order to conclude, this work have set the basis for further investigations about the electric components for traction purpose in more electrified vehicle. Due to the constantly changing environment, the new technologies and the various legislative frame, this topic remains of high interest and the following challenges still need to be deeper investigated: * Application of the methods for other drivetrain architecture (series hybrid, power-split hybrid, fuel-cell vehicle, full electric vehicle), * Investigation of new technologies such as silicon-carbide for the power electronics, lithium–sulfur battery or switch reluctance machine, * Investigation of other driving cycle, legislative frame, * Integration of additional power electronics structure, * Further validation of the modeling approaches with additional components
Bertini, Lorenzo. "Modeling and Optimization of a Fuel Cell Hybrid System". Thesis, KTH, Skolan för kemivetenskap (CHE), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-51143.
Texto completoŠandera, Čeněk. "Hybridní model metaheuristických algoritmů". Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-234259.
Texto completoThalheimer, William Cooper. "Structural analysis and optimization with a locally-Cartesian Hybrid Shell Model". Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107054.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (pages 131-133).
The Hybrid Shell Model (HSM) is presented as an intermediate-fidelity structural model well suited for conceptual design of aerospace vehicles. Although significantly simpler and more economical than full 3D elasticity models, it can still capture full 3D geometries, large deformations, and anisotropic materials. HSM is formulated from the full 3D equilibrium and compatibility equations all projected onto local bases defined on the 2D shell manifold. General anisotropic constitutive equations are also formulated in the local 2D shell manifold bases. The resulting continuous HSM formulation is discretized in weak form with a Galerkin finite element method (FEM), with spherical interpolation used for the local basis vectors. Displacements, basis rotations, and stress resultants are the primary unknowns. A fully adjoint-consistent plane-stress HSM version (HSM2D) is developed for the purpose of model verification and demonstration of order-of-accuracy convergence. The Method of Exact Solutions (MES) is applied to the case of a uniform plate hanging under its own weight. The effectiveness of the adjoint model for structural optimization is also demonstrated for a simplified rotor blade in a centrifugal force field, featuring non-uniform forcing, non-zero Poisson ratio, large deflection, and optimization of multiple parameters. The suitability of HSM as an intermediate fidelity conceptual aircraft design tool is thus demonstrated.
by William Cooper Thalheimer.
S.M.
Wu, Zheng. "Hybrid Multi-Objective Optimization Models for Managing Pavement Assets". Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/26092.
Texto completoPh. D.
Meyer, Danielle L. "Energy Optimization of a Hybrid Unmanned Aerial Vehicle (UAV)". The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523493111005807.
Texto completoYeung, King-ho y 楊景豪. "An optimization model for a solar hybrid water heating and adsorption ice-making system". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29632432.
Texto completoShah, Kshitij P. "Calibration and Validation of a Hybrid Vehicle Model for its Implementation inOptimization Routines for Model-Based Fuel Economy Optimization". The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1501183963696296.
Texto completoJiang, Siyu. "A Comparison of PSO, GA and PSO-GA Hybrid Algorithms for Model-based Fuel Economy Optimization of a Hybrid-Electric Vehicle". The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu156612591067731.
Texto completoLibros sobre el tema "HYBRID OPTIMIZATION MODEL"
Melin, Patricia, Ivette Miramontes y German Prado Arechiga. Nature-inspired Optimization of Type-2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-82219-4.
Texto completoHybrid Simulation Models of Production Networks. Springer, 2010.
Buscar texto completoHybrid Simulation Models of Production Networks. Springer, 2001.
Buscar texto completoMelin, Patricia, Ivette Miramontes y German Prado Arechiga. Nature-Inspired Optimization of Type-2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis. Springer International Publishing AG, 2021.
Buscar texto completoBäck, Thomas. Evolutionary Algorithms in Theory and Practice. Oxford University Press, 1996. http://dx.doi.org/10.1093/oso/9780195099713.001.0001.
Texto completoCapítulos de libros sobre el tema "HYBRID OPTIMIZATION MODEL"
Fontaine, Daniel, Laurent Michel y Pascal Van Hentenryck. "Model Combinators for Hybrid Optimization". En Lecture Notes in Computer Science, 299–314. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40627-0_25.
Texto completoMargain, Lourdes, Alberto Ochoa, Lissette Martínez Almaguer y Rigoberto Velázquez. "Model on Oil Platform Using Brain Storm Optimization Algorithm". En Hybrid Intelligent Systems, 311–20. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76351-4_32.
Texto completoBen Younes, Hajer, Ameni Azzouz y Meriem Ennigrou. "Solving Flexible Job Shop Scheduling Problem Using Hybrid Bilevel Optimization Model". En Hybrid Intelligent Systems, 340–49. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14347-3_33.
Texto completoSun, Zhan-Li, Nan Wang, Ru-Xia Ban y Xia Chen. "Facial Age Estimation with a Hybrid Model". En Proceedings in Adaptation, Learning and Optimization, 262–70. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01520-6_24.
Texto completoKhorram, Mahsa, Pedro Faria, Omid Abrishambaf y Zita Vale. "Economic Impact of an Optimization-Based SCADA Model for an Office Building". En Hybrid Intelligent Systems, 166–75. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14347-3_17.
Texto completoChanda, Anupama, R. N. Mukherjee y Bijan Sarkar. "Performance Evaluation of Management Faculty Using Hybrid Model of Logic—AHP". En Operations Research and Optimization, 365–75. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7814-9_25.
Texto completoNagaraju, Vidhyashree y Lance Fiondella. "A Hybrid Model Fitting Framework Considering Accuracy and Performance". En Reliability and Maintenance Modeling with Optimization, 257–78. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003095231-14.
Texto completoMajed, Hadeer, Samaher Al-Janabi y Saif Mahmood. "Hybridized Deep Learning Model with Optimization Algorithm: A Novel Methodology for Prediction of Natural Gas". En Hybrid Intelligent Systems, 79–95. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_8.
Texto completoChen, Benhui y Jinglu Hu. "Protein Structure Prediction Based on HP Model Using an Improved Hybrid EDA". En Evolutionary Learning and Optimization, 193–214. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12834-9_9.
Texto completoMelin, Patricia, Ivette Miramontes y German Prado Arechiga. "Conclusions of the Hybrid Medical Model". En Nature-inspired Optimization of Type-2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis, 111–12. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82219-4_5.
Texto completoActas de conferencias sobre el tema "HYBRID OPTIMIZATION MODEL"
Horng, Ming-Huwi, Jin-Yi Chen y Ren-Jean Liou. "Honey Bee Mating Optimization Scheme for Active Contour Model". En 2009 Ninth International Conference on Hybrid Intelligent Systems. IEEE, 2009. http://dx.doi.org/10.1109/his.2009.42.
Texto completoZhang, Zhijie. "A new Hybrid Infection model optimization Algorithm". En 3rd International Conference on Material, Mechanical and Manufacturing Engineering (IC3ME 2015). Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/ic3me-15.2015.202.
Texto completoDe Souza, Bruno, Andre De Carvalho, Rodrigo Calvo y Renato Ishii. "Multiclass SVM Model Selection Using Particle Swarm Optimization". En 2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06). IEEE, 2006. http://dx.doi.org/10.1109/his.2006.264914.
Texto completoNenashev, Alexey V. "Mathematical Model of Billing for TheOoL DAO". En International Workshop “Hybrid methods of modeling and optimization in complex systems”. European Publisher, 2023. http://dx.doi.org/10.15405/epct.23021.2.
Texto completoPokushko, M. "Slack Based Model for Enterprises’ Efficiency Improvement". En International Workshop “Hybrid methods of modeling and optimization in complex systems”. European Publisher, 2023. http://dx.doi.org/10.15405/epct.23021.43.
Texto completoKhurana, Rahul y Himanshu Gupta. "A hybrid model on cloud security". En 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). IEEE, 2016. http://dx.doi.org/10.1109/icrito.2016.7784979.
Texto completoBansal, Mani y D. K. Lobiyal. "Word-Character Hybrid Machine Translation Model". En 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). IEEE, 2020. http://dx.doi.org/10.1109/icrito48877.2020.9197865.
Texto completoJianfang, Wang y Li Weihua. "Optimization Algorithm Based on T-S Fuzzy Model of Self-Adaptive Disturbed Particle Swarm Optimization and Neural Network". En 2009 Ninth International Conference on Hybrid Intelligent Systems. IEEE, 2009. http://dx.doi.org/10.1109/his.2009.94.
Texto completoRocha, Lucio A. y Eleri Cardozo. "A Hybrid Optimization Model for Green Cloud Computing". En 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC). IEEE, 2014. http://dx.doi.org/10.1109/ucc.2014.9.
Texto completoChanyuan Liu y Jinpeng Lu. "A hybrid optimization model for hotel yield management". En Proceedings of ICSSSM '05. 2005 International Conference on Services Systems and Services Management, 2005. IEEE, 2005. http://dx.doi.org/10.1109/icsssm.2005.1499473.
Texto completoInformes sobre el tema "HYBRID OPTIMIZATION MODEL"
Hough, Patricia Diane, Genetha Anne Gray, Joseph Pete Jr Castro, .) y Anthony Andrew Giunta. Developing a computationally efficient dynamic multilevel hybrid optimization scheme using multifidelity model interactions. Office of Scientific and Technical Information (OSTI), enero de 2006. http://dx.doi.org/10.2172/877137.
Texto completoLi, Yan, Yuhao Luo y Xin Lu. PHEV Energy Management Optimization Based on Multi-Island Genetic Algorithm. SAE International, marzo de 2022. http://dx.doi.org/10.4271/2022-01-0739.
Texto completoEngel, Bernard, Yael Edan, James Simon, Hanoch Pasternak y Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, julio de 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
Texto completoAn Input Linearized Powertrain Model for the Optimal Control of Hybrid Electric Vehicles. SAE International, marzo de 2022. http://dx.doi.org/10.4271/2022-01-0741.
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