检索结果-内蒙古大学图书馆

9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020

作者： Ijiri, Moe Tabata, Tomoaki Hosoda, Takaaki Tokai University School of Information and Telecommunication Engineering Course of Information Telecommunication Engineering Tokyo Japan Tokai University School of Info Rmation and Telecommunication Engineering Department of Management System Engineering Tokyo Japan Advanced Institute of Industrial Technology Information Systems Architecture Tokyo Japan

ISBN: (纸本)9781728173979

In recent years, a credit scoring service that based on personal behavioral data has been providing in the world. Alibaba Group's Ant Financial in China developed Sesame Credit and launched its service in 2015 as an additional function of Alipay. Credit score(risk) is mainly used in case of calculating loan limit and loan interest rate. On the other hand, a personal credit score affects not only loans but also to benefit public services, job hunting, and marriage hunting. In many countries, personal credit scores will be created as part of various services and become credit score society as in China. Personal credit scores have been already performed practically, but there is not so much research on academic at present. In particular, there is not research on the personal credit risk using only non-financial data without financial data. Generally, financial data is used principally to measure a company's credit risk. However, the use of financial data to measure a personal credit risk is considered dangerous. Therefore, in the latter case, it's important to calculate credit risk using only non-financial data without using financial data. In this study, we examine the method to calculate personal credit score using non-financial ***, we describe the flow of a customer who purchases a product using relation diagram until it defaults. Secondly, we performed a two-group discriminant analysis using the default variable as the objective variable and adding some default factors to the explanatory variables. As a result of the correct discrimination rate, discrimination was possible, albeit slightly. In addition, it turned out to be meaningful to analyze personal credit using only non-financial data. © 2020 IEEE.

关键词： Discriminant analysis

来源：评论

学校读者我要写书评

暂无评论

Bayesian Optimization Framework for Efficient Fleet Design in Autonomous Multi-Robot Exploration

arXiv

引用

arXiv 2024年

作者： Concha, David Molina Li, Jiping Yin, Haoran Park, Kyeonghyeon Lee, Hyun-Rok Lee, Taesik Sirohi, Dhruv Lee, Chi-Guhn The Dynamic Optimization and Reinforcement Learning Laboratory The Department of Mechanical & Industrial Engineering University of Toronto TorontoONM5S3G8 Canada The Department of Electrical & Computer Engineering University of Toronto TorontoONM5S3G8 Canada The Division of Engineering Science The Faculty of Applied Science and Engineering University of Toronto TorontoONM5S3G8 Canada The Complex System Design Laboratory The Department of Industrial and Systems Engineering Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of The Department of Industrial Engineering Inha University Incheon22212 Korea Republic of

This study addresses the challenge of fleet design optimization in the context of heterogeneous multi-robot fleets, aiming to obtain feasible designs that balance performance and costs. In the domain of autonomous multi-robot exploration, reinforcement learning agents play a central role, offering adaptability to complex terrains and facilitating collaboration among robots. However, modifying the fleet composition results in changes in the learned behavior, and training multi-robot systems using multi-agent reinforcement learning is expensive. Therefore, an exhaustive evaluation of each potential fleet design is infeasible. To tackle these hurdles, we introduce Bayesian Optimization for Fleet Design (BOFD), a framework leveraging multiobjective Bayesian Optimization to explore fleets on the Pareto front of performance and cost while accounting for uncertainty in the design space. Moreover, we establish a sub-linear bound for cumulative regret, supporting BOFD’s robustness and efficacy. Extensive benchmark experiments in synthetic and simulated environments demonstrate the superiority of our framework over state-of-the-art methods, achieving efficient fleet designs with minimal fleet evaluations. Copyright © 2024, The Authors. All rights reserved.

关键词： Multipurpose robots

来源：评论

学校读者我要写书评

暂无评论

Optimal convergence rates of totally asynchronous optimization

arXiv

引用

arXiv 2022年

作者： Wu, Xuyang Magnńsson, Sindri Feyzmahdavian, Hamid Reza Johansson, Mikael The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden The Department of Computer and System Science Stockholm University StockholmSE-164 07 Sweden ABB Cooperate Research VästeråsSE-721 78 Sweden

Asynchronous optimization algorithms are at the core of modern machine learning and resource allocation systems. However, most convergence results consider bounded information delays and several important algorithms lack guarantees when they operate under total asynchrony. In this paper, we derive explicit convergence rates for the proximal incremental aggregated gradient (PIAG) and the asynchronous block-coordinate descent (Async-BCD) methods under a specific model of total asynchrony, and show that the derived rates are order-optimal. The convergence bounds provide an insightful understanding of how the growth rate of the delays deteriorates the convergence times of the algorithms. Our theoretical findings are demonstrated by a numerical example. © 2022, CC BY.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Dynamic neural network with memristive CIM and CAM for 2D and 3D vision

arXiv

引用

arXiv 2024年

作者： Zhang, Yue Zhang, Woyu Wang, Shaocong Lin, Ning Yu, Yifei He, Yangu Wang, Bo Jiang, Hao Lin, Peng Xu, Xiaoxin Qi, Xiaojuan Wang, Zhongrui Zhang, Xumeng Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100049 China ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong Institute of the Mind The University of Hong Kong Hong Kong Key Lab of Fabrication Technologies for Integrated Circuits Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai200433 China University of Chinese Academy of Sciences Beijing100049 China College of Computer Science and Technology Zhejiang University Zhejiang310027 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

The brain is dynamic, associative and efficient. It reconfigures by associating the inputs with past experiences, with fused memory and processing. In contrast, AI models are static, unable to associate inputs with past experiences, and run on digital computers with physically separated memory and processing. We propose a hardware-software co-design, a semantic memory-based dynamic neural network (DNN) using memristor. The network associates incoming data with the past experience stored as semantic vectors. The network and the semantic memory are physically implemented on noise-robust ternary memristor-based Computing-In-Memory (CIM) and Content-Addressable Memory (CAM) circuits, respectively. We validate our co-designs, using a 40nm memristor macro, on ResNet and PointNet++ for classifying images and 3D points from the MNIST and ModelNet datasets, which not only achieves accuracy on par with software but also a 48.1% and 15.9% reduction in computational budget. Moreover, it delivers a 77.6% and 93.3% reduction in energy consumption. © 2024, CC BY.

关键词： Memristors

来源：评论

学校读者我要写书评

暂无评论

Inverse learning of black-box aggregator for robust Nash equilibrium

arXiv

引用

arXiv 2024年

作者： Chen, Guanpu Xu, Gehui He, Fengxiang Tao, Dacheng Parisini, Thomas Johansson, Karl Henrik Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden Digital Futures Stockholm100 44 Sweden Artificial Intelligence and its Applications Institute School of Informatics University of Edinburgh EdinburghEH8 9AB United Kingdom College of Computing & Data Science Nanyang Technological University Singapore639798 Singapore Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom Department of Engineering and Architecture University of Trieste Trieste34127 Italy

In this note, we investigate the robustness of Nash equilibria (NE) in multi-player aggregative games with coupling constraints. There are many algorithms for computing an NE of an aggregative game given a known aggregator. When the coupling parameters are affected by uncertainty, robust NE need to be computed. We consider a scenario where players' weight in the aggregator is unknown, making the aggregator kind of "a black box". We pursue a suitable learning approach to estimate the unknown aggregator by proposing an inverse variational inequality-based relationship. We then utilize the counterpart to reconstruct the game and obtain first-order conditions for robust NE in the worst case. Furthermore, we characterize the generalization property of the learning methodology via an upper bound on the violation probability. Simulation experiments show the effectiveness of the proposed inverse learning approach. Copyright © 2024, The Authors. All rights reserved.

关键词： Inverse problems

来源：评论

学校读者我要写书评

暂无评论

Simulating Cyber Attacks and Designing Malware using Python

Simulating Cyber Attacks and Designing Malware using Python

引用

International Conference on Signal Processing and Integrated Networks (SPIN)

作者： Akash Ankit Shubham Inder Anuj Sharma Rahul Johari Deo Prakash Vidyarthi SWINGER: Security Wireless IoT Network Group of Engineering and Research University School of Information Communication and Technology Guru Gobind Singh Indraprastha University Dwarka New Delhi India Royal Melbourne Institute of Technology (RMIT University) Melboume Victoria Australia Parallel and Distributed System Lab School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi India

In this Internet era, we have become heavily dependent on the World Wide Web and it has become a basic amenity for humans. A normal user can be trapped easily in this vicious web if not careful enough. It is a field that requires users to be on their toes every time they try to connect to this enormous interconnection of networks. Reports and Surveys have said that in the coming years, Cybercrime could become the biggest threat. In this proposed work, the authors have deployed applications and designed malware for the purpose of simulating various kinds of cyber-attacks so that they could study their effects & affects and ultimately devise solutions to resolve the vulnerabilities in a system. These applications included networking concepts & protocols and a software based keylogger which was developed with no malicious intent, but to analyse the architectural view or design of a malware and to study the stages of a malware attack like entry, distribution, exploitation, infection and execution. Efforts have been made to demonstrate spooting attacks with an idea of identifying vulnerabilities and security loopholes in a particular system that can be exploited by an attacker if not resolved within time.

关键词： Surveys Protocols Malware Internet Web sites Security Signal resolution

来源：评论

学校读者我要写书评

暂无评论

LSTM Network-Based Method for Flexibility Prediction of Aggregated Electric Vehicles in Smart Grid 5th

LSTM Network-Based Method for Flexibility Prediction of Aggr...

引用

International Top-Level Forum on engineering Science and Technology Development Strategy and 5th PURPLE MOUNTAIN FORUM on Smart Grid Protection and Control, PMF2020

作者： Zhou, Huayanran Zhou, Yihong Zhang, Haijing Hu, Junjie Nordströmd, Lars Yang, Guangya State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Division of Electric Power and Energy Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Center for Electric Power and Energy Department of Electrical Engineering Technical University of Denmark Kongens Lyngby Copenhagen Denmark

ISBN: (纸本)9789811597459

The flexibility of Demand Response (DR) resources in grid operations has become a valuable solution to respond to the several problems brought about by the growth of intermittent renewable generation. However, the flexibility prediction of the DR resources has not yet been fully addressed in the available literature. This paper trained a long short-term memory (LSTM) recurrent neural network to predict the aggregated flexibility of electric vehicles (EVs). The prediction is based on the historical charging behavior of EVs and the DR signal (DS) which is proposed to facilitate prediction and DR management. Both the size and the maintaining time of the aggregated flexibility can be obtained from the prediction results. The accuracy of the flexibility prediction is verified through the simulation of case studies. The simulation results reveal that the size of flexibility changes under different maintaining time. The proposed flexibility prediction method may be of great assistance for DR management as well as the reserve of the gird. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

On the convergence of step decay step-size for stochastic optimization

arXiv

引用

arXiv 2021年

作者： Wang, Xiaoyu Magnússon, Sindri Johansson, Mikael The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Department of Computer and System Science Stockholm University Stockholm Sweden

The convergence of stochastic gradient descent is highly dependent on the step-size, especially on non-convex problems such as neural network training. Step decay step-size schedules (constant and then cut) are widely used in practice because of their excellent convergence and generalization qualities, but their theoretical properties are not yet well understood. We provide the convergence results for step decay in the non-convex regime, ensuring that the gradient norm vanishes at an (Formula presented) rate. We also provide the convergence guarantees for general (possibly non-smooth) convex problems, ensuring an (Formula presented) convergence rate. Finally, in the strongly convex case, we establish an (Formula presented) rate for smooth problems, which we also prove to be tight, and an (Formula presented) rate without the smoothness assumption. We illustrate the practical efficiency of the step decay step-size in several large scale deep neural network training tasks. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Soft-Landing Dynamics of a Type of Four-Legged Space Lander

SSRN

引用

SSRN 2024年

作者： Shi, Tengfei Shi, Tengfei Yang, Yinping Zhang, Zhijuan Liu, Cuicui Liu, Caishan Ma, Daolin Applied Mechanics and Structure Safety Key Laboratory of Sichuan Province School of Mechanics and Aerospace Engineering Southwest Jiaotong University Chengdu610031 China State Key Laboratory for Turbulence and Complex Systems College of Engineering Peking University Beijing100871 China Institute of Dynamics and Control College of Mechanical Engineering and Applied Electronics Technology Beijing University of Technology Beijing100871 China China Academy of Space Technology Beijing100094 China School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Marine Intelligent Equipment and System Ministry of Education Shanghai200240 China

Analyzing the landing dynamics response is essential for enhancing the success rate of surface explorations on Mars, the moon, or asteroids. This paper develops a comprehensive dynamics model for a space lander equipped with four sets of buffer legs, each consisting of a primary strut, two secondary struts, and a footpad, during its soft landing process. The degrees of freedom of the main body and the footpads are defined as generalized coordinates to describe the motion of the space lander. The compression force of the buffer struts is obtained by interpolating real experimental data, and the contact force between the footpad and the ground is calculated using Archimedes law for granular media. Then, the dynamical model for the lander in terms of minimal degrees of freedom can be constructed by applying the Lagrange equations of the second kind. The proposed dynamics model is validated by the experiments of a single-legged lander vertical touchdown and a four-legged lander free touchdown. Moreover, histories of buffer force, acceleration of the main body, and other key physical quantities are computed to investigate the landing process. This highly efficient and accurate dynamics model provides a method to perform extensive simulations to design and optimize a soft landing process. © 2024, The Authors. All rights reserved.

关键词： Landing

来源：评论

学校读者我要写书评

暂无评论

Designing EV charging stations deployment through holistic simulations: the SANEVEC project

Designing EV charging stations deployment through holistic s...

引用

EVI: Charging Ahead (EVI 2023)

作者： J.-L. Guisado-Lizar G. Jimenez-Moreno F. Diaz-del-Rio J. L. Sevillano-Ramos D. Cagigas-Muñiz M. J. Morón-Fernández D. Cascado-Caballero F. Jimenéz-Morales M. Cárdenas-Montes G. A. Wainer D. Ragel-Díaz-Jara J. Rodríguez-Leal E. Cerezuela-Escudero J. M. Montes-Sánchez D. Casanueva-Morato A. Ayuso-Martínez Research Institute of Computer Engineering (I3US) Universidad de Sevilla Avenida Reina Mercedes s/n 41012 Sevilla Spain Department of Condensed Matter Physics Universidad de Sevilla Avenida Reina Mercedes s/n 41012 Sevilla Spain Department of Basic Research Centro de Investigaciones Energeticas Medioambientales y Tecnologicas Madrid Spain Department of Systems and Computer Engineering Carleton University Ottawa Canada Department of Computer Architecture and Technology Universidad de Sevilla Avenida Reina Mercedes s/n 41012 Sevilla Spain

To determine the optimal location of the large number of urban public charging stations that will have to be deployed in the following years to transition to electric vehicles (EVs) is a challenging task, as it is intimately interconnected with the complexity of urban traffic and electric grid operation. The city is a complex system in which emerging patterns such as traffic jams, and instabilities or even outages in the electric grid are difficult to predict. The layout of charging stations can alter those patterns in traffic and electric grid operation, with consequences to mobility, air quality, and electric system. The present article presents the concept under the research project SANEVEC. It will build a framework for the optimal determination of the location of EV charging stations in a city based on simulation, which will be able to reproduce the feedback effects between all the variables involved: locations of the stations, traffic patterns, characteristics, and operation of the electricity grid, charging fees and air quality in the city. It will employ artificial intelligence methods to find high-quality station location solutions from the simulations and to predict the air quality in the city.

关键词：

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：