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Relevant bibliographies by topics / Fuzzy simulation

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Academic literature on the topic 'Fuzzy simulation'

Author: Grafiati

Published: 3 June 2025

Last updated: 19 July 2025

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Journal articles on the topic "Fuzzy simulation"

1

Shen, Q., and R. Leitch. "Fuzzy qualitative simulation." IEEE Transactions on Systems, Man, and Cybernetics 23, no. 4 (1993): 1038–61. http://dx.doi.org/10.1109/21.247887.

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Buckley, James J., and Yoichi Hayashi. "Applications of fuzzy chaos to fuzzy simulation." Fuzzy Sets and Systems 99, no. 2 (1998): 151–57. http://dx.doi.org/10.1016/s0165-0114(97)00023-7.

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Alonso-Sanz, Ramón, and Haozhen Situ. "Quantum Fuzzy Game Simulation." Parallel Processing Letters 29, no. 03 (2019): 1950010. http://dx.doi.org/10.1142/s0129626419500105.

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This article studies quantum games with imprecise payoffs simulated by means of fuzzy numbers. Three two-person game-types are scrutinized via the iterated confronting of a large number of players laying in a two-dimensional lattice. In every iteration, every player interacts with his nearest neighbours and adopts the strategy of his best paid mate. Variable degree of quantum entanglement and of optimism in the fuzzy payoffs are taken into consideration in the study.

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Medaglia, Andrés L., Shu-Cherng Fang, and Henry L. W. Nuttle. "Fuzzy controlled simulation optimization." Fuzzy Sets and Systems 127, no. 1 (2002): 65–84. http://dx.doi.org/10.1016/s0165-0114(01)00153-1.

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Zhang, Zhen Sheng, Yong Qian Luo, and He Wei. "Engineering Vehicle ABS Model Reference Self-Adaptive Control Strategy Analysis and Simulation." Applied Mechanics and Materials 328 (June 2013): 526–30. http://dx.doi.org/10.4028/www.scientific.net/amm.328.526.

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Taking the wheel slip-ratio as a control object, the basic theory of fuzzy control is analyzed, the fuzzy controller of ABS is constructed, and the model reference fuzzy adaptive control algorithm is also adopted, the simulation of ABS characteristic is performed under three different road surface conditions. Simulation results show that the simulations to model reference adaptive control are feasible and vehicle can brake at the optimal slip-ratio on different surfaces. The safety performance required by ABS is realized.

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Tian, Jian Wei, Hai Hong Chen, Zhi Zhong Li, and Wei Duan. "A Simulation Framework for Grid-Consumer Interoperability." Advanced Materials Research 860-863 (December 2013): 2481–85. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.2481.

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As distributed energy increasing, grid-consumer interoperability (GCI) is becoming a core characteristic of smart grid. Basically consumers behavior is fuzzy and adaptive, which causes difficulty to simulating interoperability. To deal with the difficulty, a GCI simulation framework and corresponding response algorithm are proposed, and thus consumers adaptive behavior could be simulated by fuzzy inference. Simulation on IEEE-14 bus test system demonstrates the validity of the simulation framework and the response algorithm proposed.

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Shan, Jinjun, and Piotr Wenderski. "Hardware-in-the-Loop Simulation for Spacecraft Formation Flying." Journal of Control Science and Engineering 2010 (2010): 1–13. http://dx.doi.org/10.1155/2010/572526.

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This paper presents a hardware-in-the-loop (HITL) simulation approach for multiple spacecraft formation flying. Considering a leader-follower formation flying configuration, a Fuzzy Logic controller is developed first to maintain the desired formation shape under external perturbations and the initial position offsets. Cold-gas on/off thrusters are developed to be introduced to the simulation loop, and the HITL simulations are conducted to validate the effectiveness of the proposed simulation configuration and Fuzzy Logic control.

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Liu, Baoding, and Kakuzo Iwamura. "Fuzzy programming with fuzzy decisions and fuzzy simulation-based genetic algorithm." Fuzzy Sets and Systems 122, no. 2 (2001): 253–62. http://dx.doi.org/10.1016/s0165-0114(00)00035-x.

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Li, Sheng Qian, and Xiao Jing Yang. "Design and Simulation for Control System of Tobacco Leaf Roasting Based on Fuzzy-PID Control." Advanced Materials Research 328-330 (September 2011): 2055–58. http://dx.doi.org/10.4028/www.scientific.net/amr.328-330.2055.

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This paper aimed at the characteristics of the control system of baking in different period of tobacco leaf roasting process, intelligent control system of tobacco leaf roast control tactics based on fuzzy-PID is proposed. A designing method and Implementation algorithm of fuzzy-PID is given. For the difficulty of traditional PID controller parameters adjusting, the PID parameters were adjusted online by using fuzzy reasoning method. It can combine the advantages of general fuzzy control and traditional PID control in this method, and it is simulated and compared with general PID control on th

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Stankovic, Marko, Miroslav Ciric, and Jelena Ignjatovic. "Simulations and bisimulations for fuzzy multimodal logics over Heyting algebras." Filomat 37, no. 3 (2023): 711–43. http://dx.doi.org/10.2298/fil2303711s.

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In the present paper, we study fuzzy multimodal logics over complete Heyting algebras and Kripke models for these logics. We introduce two types of simulations (forward and backward) and five types of bisimulations (forward, backward, forward-backward, backward-forward and regular) between Kripke models, as well as the corresponding presimulations and prebisimulations, which are simulations and bisimulations with relaxed conditions. For each type of simulations and bisimulations an efficient algorithm has been provided that works as follows: it computes the greatest presimulation/prebisimulati

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Dissertations / Theses on the topic "Fuzzy simulation"

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Shen, Qiang. "Fuzzy qualitative simulation and diagnosis of continuous dynamic systems." Thesis, Heriot-Watt University, 1991. http://hdl.handle.net/10399/829.

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Van, Den Bosch Magali Marie. "Simulation of ion exchange processes using neuro-fuzzy reasoning." Thesis, Cape Peninsula University of Technology, 2009. http://hdl.handle.net/20.500.11838/2161.

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Thesis (MTech (Chemical Engineering))--Cape Peninsula University of Technology, 2009.<br>Neuro-fuzzy computing techniques have been approached and evaluated in areas of process control; researchers have recently begun to evaluate its potential in pattern recognition. Multi-component ion exchange is a non-linear process, which is difficult to model and simulate as there are many factors influencing the chemical process which are not well understood. In the past, empirical isotherm equations were used but there were definite shortcomings resulting in unreliable simulations. In this work,

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Matthews, Chris, and mikewood@deakin edu au. "Fuzzy concepts and formal methods." Deakin University. School of Management Information Systems, 2001. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20051201.154843.

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It has been recognised that formal methods are useful as a modelling tool in requirements engineering. Specification languages such as Z permit the precise and unambiguous modelling of system properties and behaviour. However some system problems, particularly those drawn from the information systems problem domain, may be difficult to model in crisp or precise terms. It may also be desirable that formal modelling should commence as early as possible, even when our understanding of parts of the problem domain is only approximate. This thesis suggests fuzzy set theory as a possible representati

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Gauger, Ute. "Methoden zur Simulation und Analyse fuzzy-parametrisierter Systeme insbesondere mit zweidimensionalen Ergebnisgrössen." Tönning Lübeck Marburg Der Andere Verl, 2007. http://d-nb.info/985320346/04.

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Marhefka, Duane Winfield. "Fuzzy control and dynamic simulation of a quadruped galloping machine /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488202171197262.

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SPOLAOR, SIMONE. "Fuzzy logic for the modeling and simulation of complex systems." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2020. http://hdl.handle.net/10281/263538.

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I sistemi complessi generalmente mostrano comportamenti emergenti dinamici, che non possono essere spiegati da una mera descrizione delle parti che li costituiscono. Tali sistemi sono ubiquitari in contesti sia naturali che artificiali, spaziando dalla biologia alla fisica, dall’ingegneria all’economia, e suscitano l’interesse di molti scienziati appartenenti a diversi campi di ricerca. Per ottenere una più chiara comprensione del loro funzionamento, i sistemi complessi sono studiati tramite l’uso di metodi computazionali, che permettono di riprodurne il comportamento in silico. Di conseguenza

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Adewunmi, Adrian. "Selection of simulation variance reduction techniques through a fuzzy expert system." Thesis, University of Nottingham, 2010. http://eprints.nottingham.ac.uk/11260/.

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In this thesis, the design and development of a decision support system for the selection of a variance reduction technique for discrete event simulation studies is presented. In addition, the performance of variance reduction techniques as stand alone and combined application has been investigated. The aim of this research is to mimic the process of human decision making through an expert system and also handle the ambiguity associated with representing human expert knowledge through fuzzy logic. The result is a fuzzy expert system which was subjected to three different validation tests, the

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Uzunsoy, Erdem. "Application of fuzzy control in vehicle handling simulation and path planning." Thesis, University of Birmingham, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.411876.

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Gabrys, Bogdan. "Neural network based decision support : modelling and simulation of water distribution networks." Thesis, Nottingham Trent University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.387534.

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Keller, Uwe E. "Qualitative model reference adaptive control." Thesis, Heriot-Watt University, 1999. http://hdl.handle.net/10399/592.

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Books on the topic "Fuzzy simulation"

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Scherer, Rafał. Multiple Fuzzy Classification Systems. Springer Berlin Heidelberg, 2012.

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A, Ralescu D., ed. Simulation, knowledge-based computing, and fuzzy statistics. Van Nostrand Reinhold, 1987.

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N, Chorafas Dimitris. Financial models and simulation. St. Martins, 1995.

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Chorafas, Dimitris N. Financial models and simulation. Macmillan, 1995.

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Taylor, Cynthia E. Simulation testing of a fuzzy neural ramp metering algorithm. Washington State Dept. of Transportation, 1995.

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Rotshtein, Alexander P. Fuzzy Evidence in Identification, Forecasting and Diagnosis. Springer Berlin Heidelberg, 2012.

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Kacprzyk, Janusz, and Oscar Castillo. Evolutionary design of intelligent systems in modeling, simulation and control. Springer, 2009.

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United States. National Aeronautics and Space Administration., ed. NASA grant NCC2-275: Final progress report. National Aeronautics and Space Administration, 1998.

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9

Starczewski, Janusz T. Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty. Springer Berlin Heidelberg, 2013.

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10

S, Teichrow Jon, University of Houston--Clear Lake. Research Institute for Computing and Information Systems., and Lyndon B. Johnson Space Center. Information Technology Division., eds. Real-time fuzzy inference based robot path planning: Final report. Research Institute for Computing and Information Systems, University of Houston-Clear Lake, 1990.

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Book chapters on the topic "Fuzzy simulation"

1

J. Buckley, James. "Simulation." In Simulating Fuzzy Systems. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-32375-4_6.

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J. Buckley, James. "Simulation Programs." In Simulating Fuzzy Systems. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-32375-4_28.

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J. Buckley, James. "Simulation Optimization." In Simulating Fuzzy Systems. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-32375-4_8.

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Kraslawski, A., and A. Gorak. "Fuzzy Simulation thermischer Trennverfahren." In Fuzzy Logic. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78023-3_8.

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Ester, J., and Karl-Marx-Stadt. "Multicriteria Fuzzy Decisions." In Advances in Simulation. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-6389-7_44.

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Mahmoud, Magdi S. "Simulation Tools." In Fuzzy Control, Estimation and Diagnosis. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54954-5_12.

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Zolotukhin, A. B. "Fuzzy Simulation of Waterflooding." In Computational Methods for Flow and Transport in Porous Media. Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-017-1114-2_9.

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Astudillo, Leslie, Patricia Melin, and Oscar Castillo. "Simulation Results." In Chemical Optimization Algorithm for Fuzzy Controller Design. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05245-8_6.

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Kejak, Michal. "Simulation of Fuzzy System Dynamics Models." In Advances in Simulation. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-6389-7_43.

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Liu, Jinkun. "Fuzzy Logic Control." In Intelligent Control Design and MATLAB Simulation. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5263-7_4.

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Conference papers on the topic "Fuzzy simulation"

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Pang, Wei, and George M. Coghill. "Fuzzy qualitative simulation with multivariate constraints." In 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2014. http://dx.doi.org/10.1109/fuzz-ieee.2014.6891702.

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Bisgambiglia, Paul-Antoine, Emmanuelle de Gentili, Paul Bisgambiglia, and Jean-Francois Santucci. "Fuzzy simulation for discrete events systems." In 2008 IEEE 16th International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2008. http://dx.doi.org/10.1109/fuzzy.2008.4630444.

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Lopez, Cristina, Jose L. Salmeron, and Sebastian Lozano. "Software maintenance scenarios simulation with Fuzzy Cognitive Maps." In 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2011. http://dx.doi.org/10.1109/fuzzy.2011.6007668.

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Anagnostopoulos, Georgios C., and Michael Georgiopoulos. "New geometrical perspective of fuzzy ART and fuzzy ARTMAP learning." In Aerospace/Defense Sensing, Simulation, and Controls, edited by Kevin L. Priddy, Paul E. Keller, and Peter J. Angeline. SPIE, 2001. http://dx.doi.org/10.1117/12.421172.

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Pedrycz, Witold. "Fuzzy modeling and simulation." In Optical Tools for Manufacturing and Advanced Automation, edited by Bruno Bosacchi and James C. Bezdek. SPIE, 1993. http://dx.doi.org/10.1117/12.165032.

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Menghal, P. M., and A. Jaya Laxmi. "Adaptive Neuro Fuzzy based dynamic simulation of induction motor drives." In 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2013. http://dx.doi.org/10.1109/fuzz-ieee.2013.6622452.

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Nasir, Mojdeh, Saeid Nahavandi, and Douglas Creighton. "Fuzzy simulation of pedestrian walking path considering local environmental stimuli." In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2012. http://dx.doi.org/10.1109/fuzz-ieee.2012.6251245.

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"Fuzzy representation and aggregration of Fuzzy Cognitive Maps." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2013. http://dx.doi.org/10.36334/modsim.2013.c2.obiedat.

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Bisgambiglia, Paul-Antoine, Paul Antoine Bisgambiglia, and Jean-Sebastien Gualtieri. "Cognitive simulation-based on knowledge evolution in fuzzy discrete event systems." In 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2011. http://dx.doi.org/10.1109/fuzzy.2011.6007443.

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Napoles, Gonzalo, Isel Grau, Rafael Bello, Maikel Leoon, Koen Vahoof, and Elpiniki Papageorgiou. "A computational tool for simulation and learning of Fuzzy Cognitive Maps." In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2015. http://dx.doi.org/10.1109/fuzz-ieee.2015.7337859.

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Reports on the topic "Fuzzy simulation"

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Tsidylo, Ivan M., Serhiy O. Semerikov, Tetiana I. Gargula, Hanna V. Solonetska, Yaroslav P. Zamora, and Andrey V. Pikilnyak. Simulation of intellectual system for evaluation of multilevel test tasks on the basis of fuzzy logic. CEUR Workshop Proceedings, 2021. http://dx.doi.org/10.31812/123456789/4370.

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The article describes the stages of modeling an intelligent system for evaluating multilevel test tasks based on fuzzy logic in the MATLAB application package, namely the Fuzzy Logic Toolbox. The analysis of existing approaches to fuzzy assessment of test methods, their advantages and disadvantages is given. The considered methods for assessing students are presented in the general case by two methods: using fuzzy sets and corresponding membership functions; fuzzy estimation method and generalized fuzzy estimation method. In the present work, the Sugeno production model is used as the closest

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Smith, James F., and III. A Fuzzy Logic Multisensor Association Algorithm: Theory and Simulation. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada330176.

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Li, Yan, Yuhao Luo, and Xin Lu. PHEV Energy Management Optimization Based on Multi-Island Genetic Algorithm. SAE International, 2022. http://dx.doi.org/10.4271/2022-01-0739.

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The plug-in hybrid electric vehicle (PHEV) gradually moves into the mainstream market with its excellent power and energy consumption control, and has become the research target of many researchers. The energy management strategy of plug-in hybrid vehicles is more complicated than conventional gasoline vehicles. Therefore, there are still many problems to be solved in terms of power source distribution and energy saving and emission reduction. This research proposes a new solution and realizes it through simulation optimization, which improves the energy consumption and emission problems of PH

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Lavrentieva, Olena O., Ihor O. Arkhypov, Olexander I. Kuchma, and Aleksandr D. Uchitel. Use of simulators together with virtual and augmented reality in the system of welders’ vocational training: past, present, and future. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3748.

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The article discusses the theory and methods of simulation training, its significance in the context of training specialists for areas where the lack of primary qualification is critical. The most widespread hardware and software solutions for the organization welders' simulation training that use VR- and AR- technologies have been analyzed. A review of the technological infrastructure and software tools for the virtual teaching-and-production laboratory of electric welding has been made on the example of the achievements of Fronius, MIMBUS, Seabery. The features of creating a virtual simulati

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Paule, Bernard, Flourentzos Flourentzou, Tristan de KERCHOVE d’EXAERDE, Julien BOUTILLIER, and Nicolo Ferrari. PRELUDE Roadmap for Building Renovation: set of rules for renovation actions to optimize building energy performance. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541614638.

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In the context of climate change and the environmental and energy constraints we face, it is essential to develop methods to encourage the implementation of efficient solutions for building renovation. One of the objectives of the European PRELUDE project [1] is to develop a "Building Renovation Roadmap"(BRR) aimed at facilitating decision-making to foster the most efficient refurbishment actions, the implementation of innovative solutions and the promotion of renewable energy sources in the renovation process of existing buildings. In this context, Estia is working on the development of infer

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Matthews, Lisa, Guanming Wu, Robin Haw, et al. Illuminating Dark Proteins using Reactome Pathways. Reactome, 2022. http://dx.doi.org/10.3180/poster/20221027matthews.

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Diseases are often the consequence of proteins or protein complexes that are non-functional or that function improperly. An active area of research has focused on the identification of molecules that can interact with defective proteins and restore their function. While 22% percent of human proteins are estimated to be druggable, less than fifteen percent are targeted by FDA-approved drugs, and the vast majority of untargeted proteins are understudied or so-called "dark" proteins. Elucidation of the function of these dark proteins, particularly those in commonly drug-targeted protein families,

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Event-Triggered Adaptive Robust Control for Lateral Stability of Steer-by-Wire Vehicles with Abrupt Nonlinear Faults. SAE International, 2022. http://dx.doi.org/10.4271/2022-01-5056.

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Because autonomous vehicles (AVs) equipped with active front steering have the features of time varying, uncertainties, high rate of fault, and high burden on the in-vehicle networks, this article studies the adaptive robust control problem for improving lateral stability in steer-by-wire (SBW) vehicles in the presence of abrupt nonlinear faults. First, an upper-level robust H∞ controller is designed to obtain the desired front-wheel steering angle for driving both the yaw rate and the sideslip angle to reach their correct values. Takagi-Sugeno (T-S) fuzzy modeling method, which has shown the

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