检索结果-内蒙古大学图书馆

Towards an improvement of the forecast of wind resources in europe: application of unsupervised machine learning on future projections of polar vortex

Towards an improvement of the forecast of wind resources in ...

引用

2020 Summer computer Simulation Conference, SCSC 2020, Held at the 2020 Summer Simulation Multi-Conference, SummerSim 2020

作者： Montes, María Rodríguez Ayarzagüena, Blanca Mata-García, María Guijarro Complutense University of Madrid Spain Dept. Earth Physics and Astrophysics Complutense University of Madrid Spain Dept. Computer Architecture and Automatic Control Complutense University of Madrid Spain

ISBN: (纸本)9781713819462

Studying the impact of climate change on wintertime polar stratosphere is of particular relevance not only for climate knowledge but also for tropospheric projections. Machine learning provides a way to extract information from different climate models and combine the data in a such way that patterns are clearer, so predictions can be inducted. The methods used in this study have been region growing algorithm, K-means and combination of predictions. The final results show three clusters of response trends for the intensity and location of the stratospheric polar night jet. The prediction shows an increase in zonal wind intensity over the 2xCO2 and 4xCO2 concentration points and a decrease in the related latitude. Our methods can be extended for more climate models and simulation periods, and will allow not only to map the behavior of the polar night jet, but other stratospheric and tropospheric features and interactions between them. ©2020 Society for Modeling & Simulation International (SCS)

关键词： Climate models

来源：评论

学校读者我要写书评

暂无评论

Optimization of Neural Networks using Swarm Intelligence Techniques for Achieving Energy Efficiency in Smart Building Architecture

Optimization of Neural Networks using Swarm Intelligence Tec...

引用

Cognitive Robotics and Intelligent Systems (ICC - ROBINS), International Conference on

作者： M. Karthick Raja Makhbuba Shermatova Mohammed Saleh Al Ansari Shokhjakhon Abdufattokhov Vuda Sreenivasa Rao I. Infant Raj Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore Civil Engineering and Architecture Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan College of Engineering Department of Chemical Engineering University of Bahrain Bahrain Automatic Control and Computer Engineering Dept Turin Polytechnic University Dept of Information Technologies Tashkent Intl. University of Education Tashkent Uzbekistan Department of Computer Science and Engineering Koneru Lakshmaiah Education Fou. Green Fields Vaddeswaram A.P India Department of Computer Science and Engineering K. Ramakrishnan College of Engineering Trichy Tamil Nadu India

ISBN: (数字)9798350372748

ISBN: (纸本)9798350372755

The increasing prevalence of smart building architectures, driven by the integration of Internet of Things (IoT) devices and automation systems, has led to a surge in energy consumption. This research explores the application of swarm intelligence techniques as an innovative approach to optimize neural networks, aiming to strike a balance between maintaining the desired performance levels and minimizing energy consumption. The study investigates the integration of swarm-based optimization algorithms, such as Particle Swarm Optimization (PSO) into the training and operation of neural networks. These algorithms enable the networks to dynamically adapt and optimize their parameters in response to changing environmental conditions and user requirements. The research focuses on developing a comprehensive framework that considers the specific challenges posed by smart building architectures, including real-time data processing, sensor integration, and adaptive control. The proposed approach aims to achieve optimal neural network configurations that minimize energy consumption while ensuring reliable and responsive operation of smart building systems. The results demonstrate the potential of swarm intelligence to significantly improve the energy efficiency of neural network-enabled smart building architectures, providing a promising avenue for sustainable and intelligent infrastructure. The proposed model has an accuracy of 98.23% which is 7.64% higher than that of the traditional approaches.

关键词： Training Energy consumption Smart buildings Architecture Heuristic algorithms Neural networks Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Deep Training and Adapting Algorithms in Medical with De-Noising EEG 3

Evaluation of Deep Training and Adapting Algorithms in Medic...

引用

3rd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Abdulwahid, Ali Hadi Karetla, Girija Rani Ganesh, K.V.B. Kumar, A Suresh Radha, K. Shivakumar, K. Southern Technical University Engineering Technical College Control and Automation Engineering Department Basra Iraq Western Sydney University School of Computer Data and Mathematical Sciences Australia Koneru Lakshmaiah Education Foundation KL Business School Guntur Andhra Pradesh India Graphic Era Deemed to Be University Department of CSE India St. Martin's Engineering College Dept. of IT Secunderabad Telangana India SR University School of Computer Science and Artificial Intelligence Warangal Telangana India

ISBN: (纸本)9798350399264

An electroencephalogram that was captured with electrodes placed can easily get contaminated with a variety of artifacts. Here is a comparative of various electroencephalogram (EEG) de-noising techniques. Three alternative techniques are used to eliminate five different kinds of noise, and also the outcomes are evaluated. These three methods are just the Least Mean Square (LMS) technique, the Connected Neural Network, and also the Recursive Least-square (RLS) adaptable algorithm (FCNN). Period charts of the actual EEG signal, the noise EEG signal, and thus the predicted EEG signal are used to display the results. RRMSE and signal-to-noise ratio were utilized to compare the effectiveness of the 3 de-noising strategies in this study. Investigating the model parameters in this case, we discover the FCNN forecasts a better outcome compared to the other two methods. © 2023 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Numerical approach to design of low frequency magnetic field irradiation system for lab on chip experiments

Numerical approach to design of low frequency magnetic field...

引用

ELEKTRO

作者： Roman Radil Marek Bajtoš Lucia Č arnecká Klaudia Hargaš ová Patrik Kamencay Department of Electromagnetic and Biomedical Engineering University of Zilina Zilina Slovakia Department of Systems Biology and Engineering Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Dept. of Electromagnetic and Biomedical Engineering Organization University of Zilina Zilina Slovakia

ISBN: (数字)9781665467261

ISBN: (纸本)9781665467278

The article is focused on design of specific electromagnetic coil system using numerical modelling and simulation methods. The proposed solution would be capable of delivering magnetic field of desired strength/ flux density and homogeneity within the specific area to affect the cultivation process of single cells in lab on chip experiments.

关键词： Radiation effects Numerical models Magnetic fields Electromagnetics

来源：评论

学校读者我要写书评

暂无评论

Formal control Synthesis for Stochastic Neural Network Dynamic Models

arXiv

引用

arXiv 2022年

作者： Adams, Steven Lahijanian, Morteza Laurenti, Luca Delft Center for Systems and Control TU Delft Netherlands Dept. of Aerospace Eng. Sciences and Computer Science CU Boulder United States

Neural networks (NNs) are emerging as powerful tools to represent the dynamics of control systems with complicated physics or black-box components. Due to complexity of NNs, however, existing methods are unable to synthesize complex behaviors with guarantees for NN dynamic models (NNDMs). This work introduces a control synthesis framework for stochastic NNDMs with performance guarantees. The focus is on specifications expressed in linear temporal logic interpreted over finite traces (LTLf), and the approach is based on finite abstraction. Specifically, we leverage recent techniques for convex relaxation of NNs to formally abstract a NNDM into an interval Markov decision process (IMDP). Then, a strategy that maximizes the probability of satisfying a given specification is synthesized over the IMDP and mapped back to the underlying NNDM. We show that the process of abstracting NNDMs to IMDPs reduces to a set of convex optimization problems, hence guaranteeing efficiency. We also present an adaptive refinement procedure that makes the framework scalable. On several case studies, we illustrate the our framework is able to provide nontrivial guarantees of correctness for NNDMs with architectures of up to 5 hidden layers and hundreds of neurons per layer. © 2022, CC BY.

关键词： Dynamic models

来源：评论

学校读者我要写书评

暂无评论

On the Trade-Offs Between Accuracy, Privacy, and Resilience in Average Consensus Algorithms

On the Trade-Offs Between Accuracy, Privacy, and Resilience ...

引用

IEEE Conference on Decision and control

作者： Guilherme Ramos André M. H. Teixeira Sérgio Pequito Dept. of Computer Science and Engineering Instituto Superior Técnico University of Lisbon Portugal and Instituto de Telecomunicações Lisbon Portugal Department of Information Technology Division of Systems and Control Uppsala University Sweden

There can be none. In this paper, we address the problem of a set of discrete-time networked agents reaching average consensus privately and resiliently in the presence of a subset of attacked agents. Existing approaches to the problem rely on trade-offs between accuracy, privacy, and resilience, sacrificing one for the others. We show that a separation-like principle for privacy-preserving and resilient discrete-time average consensus is possible. Specifically, we propose a scheme that combines strategies from resilient average consensus and private average consensus, which yields both desired properties. The proposed scheme has polynomial time-complexity on the number of agents and the maximum number of attacked agents. In other words, each agent that is not under attack is able to detect and discard the values of the attacked agents, reaching the average consensus of non-attacked agents while keeping each agent's initial state private. Finally, we demonstrate the effectiveness of the proposed method with numerical results.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Pursuit-Evasion on a Sphere and When It Can Be Considered Flat

Pursuit-Evasion on a Sphere and When It Can Be Considered Fl...

引用

IEEE Conference on Decision and control

作者： Dejan Milutinović Alexander Von Moll Satyanarayana G. Manyam David W. Casbeer Isaac E. Weintraub Meir Pachter Dept. University of California Santa Cruz Electrical and Computer Engineering Santa Cruz CA USA Control Science Center Aerospace Systems Directorate Air Force Research Laboratory Dayton OH USA DCS Corporation Dayton OH USA Dept. of Electrical Engineering Air Force Institute of TechnologyWright-Patterson AFB OH USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In planar pursuit-evasion differential games considering a faster pursuer and slower evader, the interception points resulting from equilibrium strategies lie on the Apollonius circle. This property is instrumental for leveraging geometric approaches for solving multiple pursuit-evasion scenarios in the plane. Here, we study a pursuit-evasion differential game on a sphere and generalize the planar Apollonius set to the spherical domain. We find that the interception point from the equilibrium strategies can leave the Apollonius set boundary and present a condition to keep the intercept point on the boundary. This condition allows for generalizing planar pursuitevasion strategies to the sphere.

关键词： Geometry Instruments Differential games Games

来源：评论

学校读者我要写书评

暂无评论

The All Wheel Speed Balance control Concept*

The All Wheel Speed Balance Control Concept*

引用

International Conference on Intelligent Transportation

作者： Gaël P. Atheupe Didier Martinez Bruno Monsuez Renault Technical centre RENAULT Group & ENSTA Paris Institute Polytechnique de Paris (IP Paris) Paris France dept. Chassis control & ADAS systems Renault Technical centre RENAULT Group Guyancourt France dept. Computer science & systems engineering ENSTA Paris Institute Polytechnique de Paris (IP Paris) Paris France

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

The transition to vehicle electrification introduces new demands on chassis dynamics, paving the way for advances in driving dynamics, safety, and efficiency. A key consideration arises: how are driving torque impulses converted in electric vehicles with multiple power sources? This study introduces a novel approach to address these demands through the integration of state-of-the-art yaw control, using concurrent front/rear axle and front right/front left torque distribution based on the wheel speed balance control concept. Our aim is not necessarily to demonstrate the supremacy of our approach, but rather to present a fresh philosophical perspective on the problem of yaw control in electric vehicles. Our method embodies dynamic load transfer and axle dynamics into the yaw control problem formulation, setting it apart from current methodologies. Through experimental results, we illustrate the effectiveness of our proposed approach regardless of road surface conditions.

关键词： Torque Systematics Roads Wheels Electric vehicles Stability analysis Trajectory Safety Vehicle dynamics Axles

来源：评论

学校读者我要写书评

暂无评论

The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects

The Goldilocks Framework: Towards Selecting the Optimal Appr...

引用

AI Engineering - Software Engineering for AI (WAIN), IEEE/ACM Workshop on

作者： Rimman Dzhusupova Jan Bosch Helena Holmströ m Olsson Dept. of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

Artificial intelligence is increasingly becoming important to businesses since many companies have realized the benefits of applying Machine Learning (ML) and Deep Learning (DL) into their operations. Nevertheless, ML/DL technologies’ industrial development and deployment examples are still rare and generally confined within a small cluster of large international companies who are struggling to apply ML more broadly and deploy their use cases at a large scale. Meanwhile, current AI market has started offering various solutions and services. Thus, organizations must understand how to acquire AI technology based on their business strategy and available resources. This paper discusses the industrial experience of developing and deploying ML/DL use cases to support organizations in their transformation towards AI. We identify how various factors, like cost, schedule, and intellectual property, can be affected by the choice of approach towards ML/DL project development and deployment within large international engineering corporations. As a research result, we present a framework that covers the trade-offs between those various factors and can support engineering companies to choose the best approach based on their long-term business strategies and, therefore, would help to accomplish their ML/DL project deployment successfully.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Challenges in developing and deploying AI in the engineering, procurement and construction industry

Challenges in developing and deploying AI in the engineering...

引用

IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Rimma Dzhusupova Jan Bosch Helena Holmströ m Olsson Dept. of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

ISBN: (数字)9781665488105

ISBN: (纸本)9781665488112

AI in the Engineering, Procurement and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Several research papers exist describing the potential of AI, and many surveys and white papers have been published indicating the challenges of AI deployment in the EPC industry. However, there is a recognizable shortage of in-dept. studies of deployment experience in academic literature, particularly those focusing on the experiences of EPC companies involved in large-scale project execution with high safety standards, such as the petrochemical or energy sector. The novelty of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

关键词： Industries Procurement Companies Manuals Petrochemicals Software Safety

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：