Littérature scientifique sur le sujet « HYBRID OPTIMIZATION MODEL »
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Articles de revues sur le sujet "HYBRID OPTIMIZATION MODEL"
Xue, Li-hua, et Yong-hua Li. « Hybrid optimization model of product concepts ». Journal of Central South University of Technology 13, no 1 (février 2006) : 105–9. http://dx.doi.org/10.1007/s11771-006-0115-4.
Texte intégralGao, Xiaoli, Yangfei Yuan, Jie Li et Weifeng Gao. « A Hybrid Search Model for Constrained Optimization ». Discrete Dynamics in Nature and Society 2022 (28 septembre 2022) : 1–15. http://dx.doi.org/10.1155/2022/1190174.
Texte intégralMiracle, D. Blandina, R. K. Viral, P. M. Tiwari et Mohit Bansal. « Hybrid Metaheuristic Model for Optimal Economic Load Dispatch in Renewable Hybrid Energy System ». International Transactions on Electrical Energy Systems 2023 (6 avril 2023) : 1–25. http://dx.doi.org/10.1155/2023/5395658.
Texte intégralStevanović, Dejan, Mirjana Banković, Milica Pešić-Georgiadis et Lazar Stojanović. « Hybrid model for uncertainty assessment in open pit optimization ». Tehnika 75, no 2 (2020) : 161–71. http://dx.doi.org/10.5937/tehnika2002161s.
Texte intégralSukheja, Deepak, et Umesh Kumar Singh. « Novel Distributed Query Optimization Model and Hybrid Query Optimization Algorithm ». International Journal of Computer Applications 75, no 17 (23 août 2013) : 22–32. http://dx.doi.org/10.5120/13203-0461.
Texte intégralRegitha, M. R., Dr Paul Varghese, Shailesh Sivan et Antony Nijo. « Handoff Delay Optimization Using Hybrid Prediction Model ». International Journal of Networked and Distributed Computing 6, no 2 (2018) : 99. http://dx.doi.org/10.2991/ijndc.2018.6.2.5.
Texte intégralCahyandari, R., R. L. Ariany et Sukono. « Optimization of hybrid model on hajj travel ». IOP Conference Series : Materials Science and Engineering 332 (mars 2018) : 012042. http://dx.doi.org/10.1088/1757-899x/332/1/012042.
Texte intégralFranco-Lara, E., N. Volk, T. Hertel, V. Galvanauskas et A. Lübbert. « Model-Supported Optimization of Recombinant Protein Production Using Hybrid Models ». Chemie Ingenieur Technik 73, no 6 (juin 2001) : 654–55. http://dx.doi.org/10.1002/1522-2640(200106)73:6<654 ::aid-cite6543333>3.0.co;2-8.
Texte intégralHe, Jian Feng, et Xiao Xiong Jin. « Multiobjective Optimization of Hybrid Electrical Vehicle Powertrain Mounting System Using Hybrid Genetic Algorithm ». Applied Mechanics and Materials 87 (août 2011) : 30–37. http://dx.doi.org/10.4028/www.scientific.net/amm.87.30.
Texte intégralLi, Wenwei, et 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, no 1 (1 février 2023) : 012054. http://dx.doi.org/10.1088/1742-6596/2418/1/012054.
Texte intégralThèses sur le sujet "HYBRID OPTIMIZATION MODEL"
Sachs, Julia [Verfasser]. « Model-Based Optimization of Hybrid Energy Systems / Julia Sachs ». Aachen : Shaker, 2016. http://d-nb.info/1101185112/34.
Texte intégralWerner, 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.
Texte intégralThis 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.
Texte intégralŠandera, Čeněk. « Hybridní model metaheuristických algoritmů ». Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-234259.
Texte intégralThalheimer, 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.
Texte intégralCataloged 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.
Texte intégralPh. 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.
Texte intégralYeung, King-ho, et 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.
Texte intégralShah, 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.
Texte intégralJiang, 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.
Texte intégralLivres sur le sujet "HYBRID OPTIMIZATION MODEL"
Melin, Patricia, Ivette Miramontes et 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.
Texte intégralHybrid Simulation Models of Production Networks. Springer, 2010.
Trouver le texte intégralHybrid Simulation Models of Production Networks. Springer, 2001.
Trouver le texte intégralMelin, Patricia, Ivette Miramontes et German Prado Arechiga. Nature-Inspired Optimization of Type-2 Fuzzy Neural Hybrid Models for Classification in Medical Diagnosis. Springer International Publishing AG, 2021.
Trouver le texte intégralBäck, Thomas. Evolutionary Algorithms in Theory and Practice. Oxford University Press, 1996. http://dx.doi.org/10.1093/oso/9780195099713.001.0001.
Texte intégralChapitres de livres sur le sujet "HYBRID OPTIMIZATION MODEL"
Fontaine, Daniel, Laurent Michel et Pascal Van Hentenryck. « Model Combinators for Hybrid Optimization ». Dans 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.
Texte intégralMargain, Lourdes, Alberto Ochoa, Lissette Martínez Almaguer et Rigoberto Velázquez. « Model on Oil Platform Using Brain Storm Optimization Algorithm ». Dans Hybrid Intelligent Systems, 311–20. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76351-4_32.
Texte intégralBen Younes, Hajer, Ameni Azzouz et Meriem Ennigrou. « Solving Flexible Job Shop Scheduling Problem Using Hybrid Bilevel Optimization Model ». Dans Hybrid Intelligent Systems, 340–49. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14347-3_33.
Texte intégralSun, Zhan-Li, Nan Wang, Ru-Xia Ban et Xia Chen. « Facial Age Estimation with a Hybrid Model ». Dans 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.
Texte intégralKhorram, Mahsa, Pedro Faria, Omid Abrishambaf et Zita Vale. « Economic Impact of an Optimization-Based SCADA Model for an Office Building ». Dans Hybrid Intelligent Systems, 166–75. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14347-3_17.
Texte intégralChanda, Anupama, R. N. Mukherjee et Bijan Sarkar. « Performance Evaluation of Management Faculty Using Hybrid Model of Logic—AHP ». Dans Operations Research and Optimization, 365–75. Singapore : Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7814-9_25.
Texte intégralNagaraju, Vidhyashree, et Lance Fiondella. « A Hybrid Model Fitting Framework Considering Accuracy and Performance ». Dans Reliability and Maintenance Modeling with Optimization, 257–78. Boca Raton : CRC Press, 2023. http://dx.doi.org/10.1201/9781003095231-14.
Texte intégralMajed, Hadeer, Samaher Al-Janabi et Saif Mahmood. « Hybridized Deep Learning Model with Optimization Algorithm : A Novel Methodology for Prediction of Natural Gas ». Dans Hybrid Intelligent Systems, 79–95. Cham : Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_8.
Texte intégralChen, Benhui, et Jinglu Hu. « Protein Structure Prediction Based on HP Model Using an Improved Hybrid EDA ». Dans Evolutionary Learning and Optimization, 193–214. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12834-9_9.
Texte intégralMelin, Patricia, Ivette Miramontes et German Prado Arechiga. « Conclusions of the Hybrid Medical Model ». Dans 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.
Texte intégralActes de conférences sur le sujet "HYBRID OPTIMIZATION MODEL"
Horng, Ming-Huwi, Jin-Yi Chen et Ren-Jean Liou. « Honey Bee Mating Optimization Scheme for Active Contour Model ». Dans 2009 Ninth International Conference on Hybrid Intelligent Systems. IEEE, 2009. http://dx.doi.org/10.1109/his.2009.42.
Texte intégralZhang, Zhijie. « A new Hybrid Infection model optimization Algorithm ». Dans 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.
Texte intégralDe Souza, Bruno, Andre De Carvalho, Rodrigo Calvo et Renato Ishii. « Multiclass SVM Model Selection Using Particle Swarm Optimization ». Dans 2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06). IEEE, 2006. http://dx.doi.org/10.1109/his.2006.264914.
Texte intégralNenashev, Alexey V. « Mathematical Model of Billing for TheOoL DAO ». Dans International Workshop “Hybrid methods of modeling and optimization in complex systems”. European Publisher, 2023. http://dx.doi.org/10.15405/epct.23021.2.
Texte intégralPokushko, M. « Slack Based Model for Enterprises’ Efficiency Improvement ». Dans International Workshop “Hybrid methods of modeling and optimization in complex systems”. European Publisher, 2023. http://dx.doi.org/10.15405/epct.23021.43.
Texte intégralKhurana, Rahul, et Himanshu Gupta. « A hybrid model on cloud security ». Dans 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.
Texte intégralBansal, Mani, et D. K. Lobiyal. « Word-Character Hybrid Machine Translation Model ». Dans 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.
Texte intégralJianfang, Wang, et Li Weihua. « Optimization Algorithm Based on T-S Fuzzy Model of Self-Adaptive Disturbed Particle Swarm Optimization and Neural Network ». Dans 2009 Ninth International Conference on Hybrid Intelligent Systems. IEEE, 2009. http://dx.doi.org/10.1109/his.2009.94.
Texte intégralRocha, Lucio A., et Eleri Cardozo. « A Hybrid Optimization Model for Green Cloud Computing ». Dans 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC). IEEE, 2014. http://dx.doi.org/10.1109/ucc.2014.9.
Texte intégralChanyuan Liu et Jinpeng Lu. « A hybrid optimization model for hotel yield management ». Dans 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.
Texte intégralRapports d'organisations sur le sujet "HYBRID OPTIMIZATION MODEL"
Hough, Patricia Diane, Genetha Anne Gray, Joseph Pete Jr Castro, .) et Anthony Andrew Giunta. Developing a computationally efficient dynamic multilevel hybrid optimization scheme using multifidelity model interactions. Office of Scientific and Technical Information (OSTI), janvier 2006. http://dx.doi.org/10.2172/877137.
Texte intégralLi, Yan, Yuhao Luo et Xin Lu. PHEV Energy Management Optimization Based on Multi-Island Genetic Algorithm. SAE International, mars 2022. http://dx.doi.org/10.4271/2022-01-0739.
Texte intégralEngel, Bernard, Yael Edan, James Simon, Hanoch Pasternak et Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, juillet 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
Texte intégralAn Input Linearized Powertrain Model for the Optimal Control of Hybrid Electric Vehicles. SAE International, mars 2022. http://dx.doi.org/10.4271/2022-01-0741.
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