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检索条件"任意字段=International Conference on Modeling, Simulation and Applied Optimization"

共 22420 条记录，以下是4871-4880 订阅

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Development of Meta-Heuristic optimization Based Control of Redesigned VW Crafter Hybrid Vehicle

Development of Meta-Heuristic Optimization Based Control of ...

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international (EPE-PEMC) Power Electronics and Motion Control conference

作者： Aminu Babangida Péter Korondi Szabolcs Sándor Diós Péter Tamás Szemes Department of Mechatronics Engineering University of Debrecen Debrecen Hungary

ISBN: (数字)9798350385236

ISBN: (纸本)9798350385243

This paper uses the MATLAB/Simulink/Simscape environment to evaluate the performance of a conventional Volkswagen (VW) Crafter, equipped with a 6-speed manual gearbox and a 2.0 Turbocharged Direct Injection Common Rail Diesel (TDI CR) engine, which is converted into a hybrid vehicle. A parallel hybrid vehicle powered by a Permanent Magnet Synchronous Motor (PMSM) is compared to the conventional version. A genetic algorithm (GA) is applied to tune the classical PID controller to optimize energy consumption. A novel methodology is also introduced based on the hardware-in-the-loop (HIL) method, leveraging an online data acquisition (DAQ) system integrated into the vehicle’s Controller Area Network (CAN Bus) system. The acquired CAN bus data is analyzed using LabVIEW and Net CAN plus 110 hardware. The simulated vehicle demonstrates better performance than the real vehicle based on the comparison between the simulation and experimental results. The transformed hybrid vehicle achieves 75.11% reduction in fuel consumption and an energy efficiency of 84.62%.

关键词： Rails Renewable energy sources Metaheuristics Data acquisition Transforms Fossil fuels Energy efficiency Power electronics Voltage control Genetic algorithms

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Synthetic Dataset Generation for an Electricity Market simulation Game

Synthetic Dataset Generation for an Electricity Market Simul...

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international conference on Smart Energy Systems and Technologies (SEST)

作者： Pyae P. Phyo Koen Kok Nikolaos G. Paterakis Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands

ISBN: (数字)9798350386493

ISBN: (纸本)9798350386509

This paper introduces the Electricity Markets Game (EMGA), an online multiplayer serious game developed to be used in courses on electricity markets at the Eindhoven University of Technology ( $TU/e$ ). The game aims to enhance students' understanding of the structure and dynamics of short-term electricity markets, covering aspects of energy trading and investments in renewable and non-renewable energy sources. Within the game, students are tasked with submitting day-ahead energy offers, utilizing statistical or machine learning (ML) forecasting models and portfolio optimization techniques. To ensure a comprehensive learning experience, each participant engages in energy trading over a full month. Since the game is asynchronous, collusion between students in order to obtain foresight into the future values of the time series data they are supposed to predict cannot be guaranteed if all students are given the same dataset. At the same time, simple slicing of historical data to produce unique datasets can lead to unfairness. Quantities relevant for electricity market participation can be more volatile in certain time periods; therefore, some students can be exposed to more volatile time spans, making prediction tasks more challenging and potentially skewing performance evaluations. To mitigate this, the game incorporates synthetic data generated using a Gaussian Copula (GC) synthesizer. This method ensures that all participants have access to equitable data conditions, fostering fair competition and allowing for an accurate assessment of skills and strategies across uniformly challenging scenarios. The synthesizer is specifically designed to replicate the statistical properties and interdependencies of real-world data, including day-ahead market prices, solar, and wind generation outputs. Comprehensive statistical analysis and ML predictive modeling are conducted to confirm that the synthetic data maintain the essential characteristics and behaviors of actual data.

关键词： Accuracy Synthesizers Time series analysis Games Predictive models Electricity supply industry Data models Forecasting optimization Synthetic data

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Pattern Synthesis of MIMO Radar Based on Immune Differential Evolution Algorithm

Pattern Synthesis of MIMO Radar Based on Immune Differential...

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2020 international conference on modeling, Big Data Analytics and simulation, MBDAS 2020

作者： Jiang, Ling Jiang, Yi Chen, Guangfu Shi, Guimin Cheng, Qi School of Mathematics and Computer Wuyi University Wuyishan354300 China Key Lab. of Cogn. Computing and Intelligent Information Processing of Fujian Education Institutions Wuyishan354300 China Big Data Development Administration of Anji County Huzhou313000 China

In order to optimize the pattern synthesis of multiple input and multiple output (MIMO) radar, immune mechanism is adopted to overcome the premature risk of differential evolution (DE) algorithm, namely immune differential evolution (IDE). Firstly, the modeling of MIMO radar is introduced by encoding the position of array in the binary. Secondly, the immune mechanism is employed to improve the DE. In IDE, two parameters are self-adapted for the mutation operator by immune mechanism to enhance the convergence ability of DE, including scaling factor and crossover rate. Several experiments are conducted to analysis the performance of IDE. The simulation results show that the IDE with variable parameters can get optimal results in MIMO radar with lower the peak side-lobe level (PSLL) and maintain the diversity with stronger convergence ability and shorter calculation speed. © Published under licence by IOP Publishing Ltd.

关键词： optimization

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DEVELOPMENT OF A DESIGN APPROACH FOR THE optimization OF STEAM TURBINE EXHAUST SYSTEM PERFORMANCE THROUGH CFD MODELLING

DEVELOPMENT OF A DESIGN APPROACH FOR THE OPTIMIZATION OF STE...

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ASME Turbomachinery Technical conference and Exposition (Turbo Expo) - Sustainable Energy - Accelerating the Transition by Advancing Turbine Technology

作者： Diurno, Tommaso Tomasello, Stella Grazia Fondelli, Tommaso Andreini, Antonio Facchini, Bruno Nettis, Leonardo Arcangeli, Lorenzo Univ Florence Dept Ind Engn Florence Italy Baker Hughes Florence Italy

ISBN: (纸本)9780791885017

Nowadays, the ever-increasing world electricity generation by renewable energy sources has brought about changes in conventional power plants, especially in those ones where large steam turbines work, which were widely used to meet the world's energy needs by operating mostly at fixed conditions. Now, instead, they have to be capable to operate with greater flexibility, including rapid load changes and quick starts as well, in order to make the most of the renewable resources while guaranteeing the coverage of any shortcomings of the latter with traditional fossil fuel systems. Such service conditions are particularly challenging for the exhaust hoods, which have a great influence on the overall turbine performance, especially at off-design conditions. In fact, the complex and high rotational 3D flow generated within the diffuser and the exhaust hood outer casing can cause an increase in aerodynamic losses along with the detriment of the hood recovery performance. For these reasons, an optimized design and adequate prediction of the exhaust hood performance under all the machine operating conditions is mandatory. Since it has been widely proven that the exhaust hood flow strongly interacts with the turbine rear stage, the necessity to model this as well into a CFD modeling becomes crucial, requiring a remarkable computational effort, especially for full transient simulations. Even if adopting simplified approaches to model the last stage and exhaust hood interfaces, such as the so-called Frozen Rotor and the Mixing Plane ones, helps to keep the computational cost low, it can be not for an exhaust hood optimization process, which requires a significant number of CFD simulations to identify the most performing geometry configuration. For these reasons, a simplified model of the exhaust hood must be adopted to analyse all the possible design variants within a feasible time. The purpose of this work is to present a strategy for the exhaust hood design based on the defin

关键词： modeling optimization Computational fluid dynamics Design Exhaust systems Steam turbines Geometry Engineering simulation Turbines Flow (Dynamics) simulation Diffusers Three-dimensional models Stress Transients (Dynamics) Fluids Machinery Power stations Rotors Approximation Electric power generation Renewable energy sources Response surface methodology Fossil fuels

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Car Service optimization Based on simulation 14

Car Service Optimization Based on Simulation

引用

14th international Scientific and Technical conference on applied Mechanics and Systems Dynamics, AMSD 2020

作者： Revina, I.V. Trifonova, E.N. Omsk State Technical University 11 Mira ave. Omsk644050 Russia

The article presents the results of optimizing the service center operation. The IDEF3 notation was used to analyze the logical sequence of processes performed in the car center divisions. The developed discrete-event simulation model "AS-IS"made it possible to identify "bottlenecks"in the work of the car center. The involvement of experts and the use of the method of apriori ranking of factors allowed determining the impact of a number of factors on the work of the service center and the directions for improving the work. Changes in organizational, material and technical factors and the development of "TO-BE"simulation model allowed determining the optimal parameters for the service center operation. As a result of the business process reengineering, the following changes were made: staff schedule and assignment of employees to work;the number of service posts;an electronic queue and document management system. These changes allowed increasing the profit of the service center by 1.9 times. © Published under licence by IOP Publishing Ltd.

关键词： Information services

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Calibration of a biophysical model to replicate evoked compound action potentials in the swine vagus nerve

Calibration of a biophysical model to replicate evoked compo...

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Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Claudio Verardo Ciro Zinno Simone Romeni Filippo Agnesi Fabio Bernini Anar Dushpanova Valentina Casieri Vincenzo Lionetti Silvestro Micera Department of Excellence in Robotics & AI The BioRobotics Institute Scuola Superiore Sant’Anna Pisa Italy Bertarelli Foundation Chair in Translational NeuroEngineering Neuro-X Institute EPFL Genève Switzerland BioMedLab Interdisciplinary Research Center “Health Science” Scuola Superiore Sant’Anna Pisa Italy Unit of Translational Critical Care Medicine Laboratory of Basic and Applied Medical Sciences Interdisciplinary Research Center “Health Science” Scuola Superiore Sant’Anna Pisa Italy Al-Farabi Kazakh National University Almaty Kazakhstan Fondazione Toscana "G. Monasterio" Pisa Italy

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Vagus nerve stimulation (VNS) is a promising application of bioelectronic medicine to treat many pathologies, ranging from epilepsy and depression to cardiovascular diseases. Conventional VNS is not optimized taking into account the topographic organization of the vagus nerve, resulting in suboptimal stimulation protocols, which can lead to severe adverse effects. The development of in vivo methods to determine topographic organization would allow more selective stimulation protocols and is thus pivotal in the development of future therapies. Here, we show that it may be possible to reverse-engineer vagus nerve topographic organization starting from experimental evoked compound action potentials (ECAPs). The parameters of a biophysical model of ECAP generation are varied until the optimal matching between synthetic and experimental ECAPs is determined. In the present work, we managed to match an experimental ECAP obtained from swine VNS, and to replicate the shape of an unseen experimental ECAP through the optimized parameters. This work paves the way to the automatic optimization of selective VNS protocols, opening to new important therapeutic opportunities.

关键词： In vivo Pathology Protocols Action potentials Shape Biological system modeling Organizations Recording Compounds optimization

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An optimization Method for Accelerating Convolutional Neural Networks Based on FPGA

An Optimization Method for Accelerating Convolutional Neural...

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Information and Communication Technology (ICTech), international conference of

作者： Dongji Li Zhenyu Yin Wei Gao MingZhi Hu Jianglin Du Liaoning Key Laboratory of Domestic Industrial Control Platform Technology on Basic Hardware & Software Shenyang University of Chemical Technology Shenyang China Liaoning Key Laboratory of Domestic Industrial Control Platform Technology on Basic Hardware & Software Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China Shenyang University of Chemical Technology Shenyang China

ISBN: (数字)9798350376258

ISBN: (纸本)9798350376265

Aiming at the problems of slow deployment of convolutional neural networks in the central processing unit (CPU) and high power consumption in the graphics processing unit (GPU), the convolutional neural network (CNN) developed based on the field programmable gate array (FPGA) platform is adopted. ) recognition system, which can achieve the effect of improving the operation speed of the algorithm. FPGA is a reconfigurable hardware device that can be programmed to implement various logic functions and can be optimized according to specific applications. Through the design optimization of LeNet5, this paper designs a LeNet_Min network model with fewer parameters. Considering that the calculation amount of the algorithm and the consumption of logic resources are mainly concentrated in the convolution and pooling layers, a pipeline-based dual-channel data model is proposed. Comparison methods. In the pooling layer and activation function of convolutional neural network, flow pooling is designed, and the design method of activation function and pooling layer isomorphism is proposed. The test results show that the recognition speed of Letnet_Min is about 13 times that of the same network model realized by the CPU on the computer side, and higher than that of the GPU, and the system power consumption is only 1.96w. In addition, the system has high versatility and low resource occupation, and can be applied to other neural network models.

关键词： Multiplexing Power demand Computational modeling Graphics processing units Programmable logic arrays Logic gates Hardware Central Processing Unit Convolutional neural networks Field programmable gate arrays

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simulation and Parameter optimization of Pilot Internal Flow Overflow Valve 7

Simulation and Parameter Optimization of Pilot Internal Flow...

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2021 7th international conference on Manufacturing Technology and applied Materials, ICAMMT 2021

作者： Li, Guanghui Wang, Lipeng Qiao, Jing Wei, Guanju Han, Xinmiao Hou, Dingqi Guo, Jungang Beijing Institute of Precision Electromechanical Control Equipment Beijing100076 China

Aiming at the pilot internal overflow valve, the working principle is introduced, and the simulation model is established by AMESim. The pre-compression force of pilot spring is calculated by NLPQL. The influence on the dynamic characteristics of the pilot spring stiffness, damping hole diameter, the diameter of main valve core is analyzed by batch processing. Then the Genetic Algorithm(GA) is used to obtain optimal valve of structural parameters, which can provide a theoretical basis for dynamic characteristics. © Published under licence by IOP Publishing Ltd.

关键词： Genetic algorithms

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Prediction of Construction Delays in Road Projects Using a Particle Swarm optimization (PSO) –Artificial Neural Network (ANN) Model

Prediction of Construction Delays in Road Projects Using a P...

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international conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

作者： Kent Ray F. Aduca Dante L. Silva Russell L. Diona School of Graduate Studies Mapua University Manila Philippines School of Civil Environmental and Geological Engineering Mapua University Manila Philippines Information Technology Department University of Technology and Applied Sciences –Muscat Sultanate of Oman Muscat Oman

ISBN: (数字)9798350381177

ISBN: (纸本)9798350381184

Due to the rise in the infrastructure projects in the Philippines, road project delay is considered a crucial challenge experienced by the construction industry nowadays. This research exhibited the findings of the application of an integrated PSO-ANN approach in predicting slippage or construction delay in road projects. A collection of road construction projects (RCP) was obtained from the Department of Public Works and Highways (DPWH) Regional Office (RO) XII to build the record to be employed in the network establishment. Several factors were used as the predictors in determining the slippage or construction delay including the road length, original duration, unworkable days, time extension, and revised amount of the project. Established on the simulation findings using the PSO-ANN approach, it was observed that the optimized model was obtained using 25,310 iterations and have an excellent value for the performance metrices measured in this study. Moreover, the analysis of the connection weights revealed that the time extension is the most significant predictor to the road construction delay. As compared to the other modeling tools, the PSO-ANN approach provided the superior prediction capabilities appropriate for determining the slippage in road projects. Furthermore, the findings of this work provided the evidence in the capabilities of machine learning tools particularly the PSO-ANN approach in its application to construction management area.

关键词： Roads Neural networks Humanoid robots Machine learning Predictive models Prediction algorithms Delays

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Housing Assignment optimization of Warehouse Breeding 7th

Housing Assignment Optimization of Warehouse Breeding

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7th international conference on Life System modeling and simulation, LSMS 2021, and the 7th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021

作者： Yang, Wenqiang Yang, Zhile Peng, Zhanlei Chen, Yonggang School of Mechanical and Electrical Engineering Henan Institute of Science and Technology Xinxiang453003 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9789811672125

This paper aims at optimizing the housing assignment of warehouse breeding. A model of the housing assignment for minimizing the total completion time of feeding in cycle of slaughter is established, and a Gaussian social spider algorithm (GSSO) is proposed. By introducing the subpopulation reconstruction mechanism, Gaussian mating radius and multi-mating operator, GSSO can balance the global exploration and the local exploitation. simulation results demonstrate that compared with other algorithms, the proposed algorithm achieves higher accuracy and quicker convergence, meanwhile obtains a more satisfactory solution in a shorter period of time. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Housing

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