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检索条件"任意字段=International Conference on Computer Modeling and Simulation"

共 35208 条记录，以下是211-220 订阅

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A Projection-Based Framework for Integrating Machine Learning into Macro finance Models

A Projection-Based Framework for Integrating Machine Learnin...

引用

Data Science, Agents & Artificial Intelligence (ICDSAAI), international conference on

作者： Akash S Sindhu V Pavithra S Department of Computer Science and Engineering Chennai Institute of Technology Chennai India

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

This research introduces a supervised machine learning projection method to approximate expectations in the optimality conditions of economic models. Building upon the parameterized expectations algorithm (PEA) with stochastic simulation, the proposed neural network-based method efficiently addresses challenges such as multicollinearity and the curse of dimensionality. The study extends existing optimal debt management models to include four maturities, uncovering insights about medium-term maturities’ role in fiscal policy. Our findings demonstrate that the optimal policy actively leverages medium-term maturities to stabilize financial income during economic shocks without increasing total debt.

关键词： Economics Machine learning algorithms High dimensional data Biological system modeling Computational modeling Electric shock Buildings Stochastic processes Finance Unsupervised learning

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Design and simulation of Broken Gate TFET and its RF Applications

Design and Simulation of Broken Gate TFET and its RF Applica...

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international ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering (ECTI-NCON)

作者： Kh. Alisha Singha Aditya Singha Swrang Brahma Karapallav Chutia Bijoy Goswami Dept. of Electronics and Telecommunication(B.Tech) Assam Engineering College JalukbariGuwahati(ASTU) Guwahati Assam India

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

In this study, we introduce a novel Broken-Gate Tunnel Field-Effect Transistor (BG-TFET) architecture based on silicon. The structure has been refined and analytically characterized. The device showcases an enhanced subthreshold slope (SS) of 19 mV/dec, minimal bidirectional current, and ON-current values on par with contemporary designs of similar dimensions. The findings of the device parameters are corroborated through the simulations of SILVACO employing the methodology of Nonlocal tunneling.

关键词： Performance evaluation Accuracy TFETs Sensitivity Tunneling Predictive models Logic gates Silicon Semiconductor process modeling Transistors

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ARMS: Activity-Resource Modelling Simulator 16th

ARMS: Activity-Resource Modelling Simulator

引用

16th EAI international conference on simulation Tools and Techniques, SIMUTools 2024

作者： Di Iorio, Angelo Ferrati, Marco Rossi, Davide Department of Computer Science and Engineering University of Bologna Bologna Italy

ISBN: (纸本)9783031873447

Activity-based process modeling languages, such as Business Process Model and Notation (BPMN), face challenges in accurately representing manufacturing processes, limiting their effectiveness for simulation purposes. In contrast, specialized manufacturing process simulation tools typically adopt a resource-based approach which, while effective in certain aspects, often lacks robust process modeling capabilities and requires custom coding to define detailed system behaviors. Although prior research has explored extending BPMN to better support manufacturing scenarios, there is still a lack of tools that integrate both activity-centric and resource-centric approaches for comprehensive modeling and simulation. In this work, we address this gap by proposing a novel metamodel that extends BPMN with enhanced resource capabilities. We present a process modeler that allows users to design manufacturing processes and a corresponding simulator that uses these models to generate insightful information about the process performance through simulation. The solution proposed is then validated using both made-up and real-world manufacturing scenarios. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Forming

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Integrated modeling and Feasibility Study of a Rooftop Solar System on Academic Buildings: A Case Study in Bangladesh

Integrated Modeling and Feasibility Study of a Rooftop Solar...

引用

international conference on Electrical, computer and Communication Engineering (ECCE)

作者： Rahat Redwan Mehnaz Hossain Awatif Nadia Rahbaar Yeassin Mahmudul Hasan Nahid-Ur-Rahman Chowdhury Dept. of EEE Ahsanullah University of Science & Technology (AUST) Dhaka Bangladesh Dept. of EEE Northern University Bangladesh (NUB) Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

The uses of solar photovoltaic (PV) systems have increased significantly as the world moves towards renewable energy sources (RESs). Rooftop solar systems (RSSs) are particularly popular due to their environmental advantages. This study explores the integrated modeling and feasibility analysis of rooftop solar system for Rangamati Science and Technology University (RMSTU), located in Rangamati district, Bangladesh. Established to advance higher education and research in science and technology in the Chittagong Hill Tracts (CHTs) region, the university requires a thorough feasibility assessment before installing a grid-connected RSS. This paper presents a detailed methodology for evaluating a grid-connected RSS, considering performance, economic factors, losses, and environmental impact. A test system with a 125 kWp capacity is implemented in academic buildings 1 and 2 on the university campus using PVsyst and the System Advisor Model (SAM) software. simulation results show an annual energy output of 185.86 MWh and a payback period of 4.8 years. The results indicate a performance ratio of 80.2%, a marginal levelized cost of energy (LCOE) of 6.468 Bangladeshi Taka (BDT) (equivalent to $0.055), and a reduction in CO 2 emissions by 86.243 tons per year.

关键词： Photovoltaic systems Renewable energy sources Analytical models simulation Buildings Production Power grids Solar system Software tools Optimization

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Design and simulation of an Intelligent Traffic Management System Using Vehicular Networks

Design and Simulation of an Intelligent Traffic Management S...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： P. Tapan Datta D.Lalith Kumar S. Tanoj Shinu M Rajagopal Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

In this study , the reasearch is focused on the simulation of vehicular communication networks, especially intelligent traffic systems, to enhance dependability, safety, and optimality in communication. The simulation is performed using the OMNeT++ simulator and is integrated with the Veins framework that uses the IEEE 802.11p protocol for V2V and V2I communications. Importing real-world traffic scenarios into the framework is obtained via the use of SUMO through TraCIScenarioManager. Other features of the framework include the definition of mobility models, dynamic obstacles, and detailed radio propagation modeling. TraCIDemo11p is used for mobility and communication by both RSUs and vehicles with applications in beaconing and channel switching. The whole framework analyzes smart traffic management solutions, providing as much insight into their performance based upon the communication reliability and overall efficiency in vehicular networks.

关键词： Protocols Vehicle-to-infrastructure simulation Vehicular ad hoc networks Switches Radio propagation Safety Security Reliability Vehicle dynamics

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Synchronization of computer Virus System Using Fractional Calculus

Synchronization of Computer Virus System Using Fractional Ca...

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Computational Intelligence Approaches and Applications (ICCIAA), international conference on

作者： Jamal Oudetallah Imane Zouak Wasim Audeh Adel Ouannas Amina-Aicha Khennaoui Iqbal M. Batiha Shaher Momani Department of Mathematics University of Petra Amman Jordan Department of Mathematics and Informatics University of Larbi Ben M'hidi Oum El Bouaghi Algeria NTIC Faculty University of Constantine 2 Constantine Algeria Department of Mathematics Al Zaytoonah University of Jordan Amman Jordan Nonlinear Dynamics Research Center (NDRC) Ajman University Ajman UAE

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

This paper presents a comprehensive study on the synchronization of fractional-order computer virus systems. By utilizing the concept of generalized synchronization, we explore the dynamic behavior of these systems and propose effective control strategies to achieve synchronized states. The proposed approach leverages the advantages of fractional calculus to model the memory effects and non-local properties of computer virus propagation. Numerical simulations are conducted to validate the theoretical findings and demonstrate the effectiveness of the proposed synchronization scheme. The results of this research contribute to a deeper understanding of computer virus dynamics and provide insights into potential security measures.

关键词： computer viruses Computational modeling Numerical simulation Numerical models Synchronization Security Fractional calculus Computational intelligence

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Enhancing the Autonomy of Soft Robots in Minimally Invasive Surgeries Through computer Vision 2

Enhancing the Autonomy of Soft Robots in Minimally Invasive ...

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2nd international conference on Advanced Innovations in Smart Cities, ICAISC 2025

作者： Alsirhani, Hams M Elhag, Salma King Abdulaziz and His Companions Foundation for Giftedness and Creativity 'Mawhiba' Riyadh Saudi Arabia King Abdul-Aziz University Department of Information Systems Jeddah Saudi Arabia

ISBN: (纸本)9798331506995

Researchers have recognized the potential of employing soft robots in minimally invasive surgeries (MIS), which could significantly reduce the side effects associated with traditional surgical methods and enhance patient outcomes. However, the extent to which this potential is realized depends on the level of autonomy achieved by the soft robots. Lower levels of autonomy necessitate increased hands-on involvement during MIS, potentially compromising the robots' ability to perform procedures with consistent accuracy. Consequently, achieving high levels of accuracy in the autonomy of soft robots remains a significant challenge. The autonomy of these robots is influenced by various factors, including their capacity to accurately classify their surroundings, particularly anatomical structures, which is crucial for effective decision-making. To address the challenge posed by our research question, How can the application of Deep Neural Networks (DNNs) and Deep Reinforcement Learning (DRL) improve the autonomy of soft robots in performing complex tasks in MIS, particularly in the precise classification of anatomical structures and decision making?, we conducted an in-depth literature review and investigation into the integration of DNNs and DRL within this context. Our study used a modeling and simulation methodology to evaluate and quantify the benefits of incorporating these advanced AI techniques. Through this approach, we measured the effects of DNNs and DRL on enhancing the autonomy of soft robots, particularly in their ability to perform complex tasks in MIS with improved precision and decision-making capabilities. This work represents a step toward optimizing robotic autonomy in surgical environments, potentially leading to more efficient and accurate outcomes in minimally invasive procedures. © 2025 IEEE.

关键词： Robotic surgery

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Improving Cloud Energy Efficiency through Machine Learning Models 33

Improving Cloud Energy Efficiency through Machine Learning M...

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33rd Euromicro international conference on Parallel, Distributed, and Network-Based Processing, PDP 2025

作者： Cesario, Eugenio Lindia, Paolo Lobello, Federica Vinci, Andrea Zarin, Shabnam Capalbo, Santina University of Calabria DICES Department Rende Italy University of Calabria DIMES Department Rende Italy CNRNational Research Council of Italy Rende Italy Monmouth University Computer Science Department West Long BranchNJ United States

ISBN: (纸本)9798331524937

The rapid growth of Cloud Computing and the expansion of large data centers have led to significant increases in energy consumption for hardware and cooling systems. This surge in power usage has raised operational costs, making energy efficiency a pressing issue for data center management. Virtual Machines (VMs) consolidation is a widely studied strategy to mitigate these costs by minimizing the number of active physical servers while maintaining user Service Level Agreements (SLAs). However, the success of consolidation largely depends on accurately forecasting VM resource needs. This paper presents the design and development of an energy-aware VMs allocation system that leverages predictive machine learning models to forecast future computational demands (CPU) of each VM. By anticipating these needs, the system optimally allocates VMs to available servers, effectively balancing energy savings with performance. A preliminary experimental evaluation, conducted on synthetic data, leverages predictive modeling within a server simulation to assess CPU and energy usage, demonstrating the effectiveness of energy-aware VMs allocation in optimizing resource utilization and reducing energy consumption. © 2025 IEEE.

关键词： Energy efficiency

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Rack Sensor Metrics Odyssey: Analyzing Sensor Behavior with Random Forest and kNN for Strategic Job Allocation Insights

Rack Sensor Metrics Odyssey: Analyzing Sensor Behavior with ...

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IEEE Students' conference on Electrical, Electronics and computer Science (SCEECS)

作者： Angelina George B. M. Beena Department of Computer Science & Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

Data centers are vital to modern computing but contribute significantly to carbon emissions due to their high energy consumption. To address this, machine learning models can optimize resource allocation by analyzing sensor metrics. In this study, the Random Forest Regressor was chosen for its ability to capture sensor behavior, even showing negative R 2 values, aligning with observed patterns. Meanwhile, k-Nearest Neighbors (kNN) emerged as the best model for learning from the same data, despite irregularities, with R 2 values ranging between 0.6 and 1. This analysis supports sustainable data center management by enhancing energy efficiency and minimizing environmental impact. Future work will explore the integration of these models into simulation environments.

关键词： Data centers Analytical models Biological system modeling Computational modeling Nearest neighbor methods Green computing Data models Resource management Sustainable development Random forests

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Research on Planting Optimisation Strategies Based on 3D Dynamic Matrix Linear Optimisation Algorithm and Monte Carlo simulation

Research on Planting Optimisation Strategies Based on 3D Dyn...

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Electronics, Energy Systems and Power Engineering (EESPE), IEEE international conference on

作者： Xiyuan Wu Shuling Xie Tiantian Sun Information Engineering University Zhengzhou China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

The aim of this paper is to investigate the application of three-dimensional dynamic matrix linear optimisation algorithms and Monte Carlo simulation in planting optimisation strategies. In this paper, a series of computer algorithm-based models and strategies are constructed as an example of a crop planting programme optimization problem from 2024 to 2030 in a village. Firstly, a three-dimensional dynamic matrix linear optimization algorithm is used to transform the crop planting problem into a profit-maximising optimization problem. By constructing a multidimensional matrix under the constraints and combining the CBC solver with the Big-M algorithm, the optimal planting plan that meets the requirement of maximum profit is solved. Next, Monte Carlo simulation is used to deal with the uncertainties in crop cultivation by forecasting the expected sales volume, cultivation cost, sales price, etc., and combining with the revised constraints to optimise the cultivation strategy to reduce the potential risks. The whole process is efficiently solved and optimised by computer algorithms on the data and models, and 3D spatial distribution maps and 2D heat maps are shown to visualise the optimal crop planting scenarios for each year. This study provides scientific decision support for optimal allocation of resources in complex systems through advanced algorithmic models, demonstrating the potential of computer technology to be widely applied in agricultural planning and sustainable development.

关键词： Monte Carlo methods Three-dimensional displays Uncertainty Heuristic algorithms Computational modeling Crops Planning Resource management Sustainable development Optimization

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