共查询到20条相似文献，搜索用时 62 毫秒
1.
《Journal of The Franklin Institute》2022,359(4):1747-1767
This paper studies the charging/discharging scheduling problem of plug-in electric vehicles (PEVs) in smart grid, considering the users’ satisfaction with state of charge (SoC) and the degradation cost of batteries. The objective is to collectively determine the energy usage patterns of all participating PEVs so as to minimize the energy cost of all PEVs while ensuring the charging needs of PEV owners. The challenges herein are mainly in three folds: 1) the randomness of electricity price and PEVs’ commuting behavior; 2) the unknown dynamics model of SoC; and 3) a large solution space, which make it challenging to directly develop a model-based optimization algorithm. To this end, we first reformulate the above energy cost minimization problem as a Markov game with unknown transition probabilities. Then a multi-agent deep reinforcement learning (DRL)-based data-driven approach is developed to solve the Markov game. Specifically, the proposed approach consists of two networks: an extreme learning machine (ELM)-based feedforward neural network (NN) for uncertainty prediction of electricity price and PEVs’ commuting behavior and a Q network for optimal action-value function approximation. Finally, the comparison results with three benchmark solutions show that our proposed algorithm can not only adaptively decide the optimal charging/discharging policy by on-line learning process, but also yield a lower energy cost within an unknown market environment. 相似文献
2.
《International Journal of Information Management》2014,34(2):177-184
Cloud or utility computing is an emerging new computing paradigm designed to deliver numerous computing services through networked media such as the Web. This approach offers several advantages to potential users such as “metered” use (i.e., pay-as-you-go) which offers scalability, online delivery of software and virtual hardware services (e.g., collaboration programmes, virtual servers, virtual storage devices) which would enable organizations to obviate the need to own, maintain and update their software and hardware infrastructures. The flexibility of this emerging computing service has opened many possibilities for organizations that did not exist before. Among those organizations are those engaged in healthcare provision. The aim of this article is to shed some light on this development and explore the potential (and future) of cloud computing in contributing to the advancement of healthcare provision. A small case study will also be presented and discussed. 相似文献
3.
伴随着互联网和计算技术的发展,人们的学习环境发生了巨大变化,大学图书馆作为学习支持服务部门,也需要与时俱进。通过网络调研国内外一些大学图书馆的学习支持服务情况,总结当前学习环境发展特点。在指出大学图书馆在学习支持中的作用基础上,提出大学图书馆以用户的学习需求为中心,围绕学习支持服务的资源、技术和空间要素,构建大学图书馆学习支持服务模式。 相似文献
4.
为了实现基于非训练数据的神经模糊控制器的在线学习，提出了一种基于强化学习的神经模糊控制系统和相应的学习算法。该控制系统由神经模糊预测器和神经模糊控制器两部分组成，其中，神经模糊控制器采用基于确定度的模糊规则模型作为知识表示形式的扩展型神经模糊网络。在学习算法的设计中，尝试了利用强化信号得到输入状态的“期望输出”，进而将强化学习转化为基于训练数据学习的解决思路。仿真实验验证了所提出的控制系统结构和学习算法的合理性和可行性。 相似文献
5.
[目的/意义]万物互联时代背景下,集中式的云计算模型将难以适应智慧图书馆的海量数据处理需求,而边缘计算的出现为这一问题的解决提供了新的技术手段,对图书馆的智慧服务产生影响。[方法/过程]首先阐释了边缘计算的基本架构与特点,然后在探讨图书馆智慧服务需求基础上,分析了图书馆智慧服务融入边缘计算的优势及可能性,最后构建了基于边缘计算的图书馆智慧服务体系框架,并对框架的每一层级进行了功能分析。[结果/结论]该体系框架可提高图书馆智慧服务响应实时性,降低智慧图书馆数据处理成本和网络带宽压力,开辟了促进图书馆智慧服务能力提升的新思路。 相似文献
6.
《Information processing & management》2023,60(2):103212
The massive number of Internet of Things (IoT) devices connected to the Internet is continuously increasing. The operations of these devices rely on consuming huge amounts of energy. Power limitation is a major issue hindering the operation of IoT applications and services. To improve operational visibility, Low-power devices which constitute IoT networks, drive the need for sustainable sources of energy to carry out their tasks for a prolonged period of time. Moreover, the means to ensure energy sustainability and QoS must consider the stochastic nature of the energy supplies and dynamic IoT environments. Artificial Intelligence (AI) enhanced protocols and algorithms are capable of predicting and forecasting demand as well as providing leverage at different stages of energy use to supply. AI will improve the efficiency of energy infrastructure and decrease waste in distributed energy systems, ensuring their long-term viability. In this paper, we conduct a survey to explore enhanced AI-based solutions to achieve energy sustainability in IoT applications. AI is relevant through the integration of various Machine Learning (ML) and Swarm Intelligence (SI) techniques in the design of existing protocols. ML mechanisms used in the literature include variously supervised and unsupervised learning methods as well as reinforcement learning (RL) solutions. The survey constitutes a complete guideline for readers who wish to get acquainted with recent development and research advances in AI-based energy sustainability in IoT Networks. The survey also explores the different open issues and challenges. 相似文献
7.
《Journal of The Franklin Institute》2022,359(3):1152-1171
In this paper, a novel complete model-free integral reinforcement learning (CMFIRL) algorithm based fault tolerant control scheme is proposed to solve the tracking problem of steer-by-wire (SBW) system. We begin with the recognition that the reference errors can eventually converge to zero based on the command generator model. Then an augmented tracking system is constructed with a corresponding performance index which is considered as a type of actuator failure. By using the reinforcement learning (RL) technique, three novel online update strategies are respectively developed to cope with the following three cases, i.e., model-based, partially model-free, and completely model-free. Especially, the RL algorithm for the complete model-free case eliminates the constraints of requiring the known system dynamics in fault-tolerant tracking controlling. The system stability and the convergence of the CMFIRL iteration algorithm are also rigorously proved. Finally, a simulation example is given to illustrate the effectiveness of the proposed approach. 相似文献
8.
IP电话认证计费系统使用时要将用户名、密码等敏感信息在网络上传输,这样就需要对信息进行加密并认证用户身份。RADIUS协议是目前应用最为广泛的认证、授权、计费的方法。多用户并发访问时会消耗大量的服务器系统资源,服务器的资源处于瓶颈状态,严重影响了系统性能,在本系统的实现中,设计一个专门的负载平衡服务器调度多个RADIUS服务器,使得各个服务器的负载达到均衡,从而较好地解决了该问题。 相似文献
9.
《Information processing & management》2022,59(3):102914
In the era of autonomous systems, the security is indispensable module for flexible computing environment. Due to increased computer power and network speed, a new computing paradigm, such as cognitive inspired computing, will emerge. Such a paradigm provides human-centered services that are convenient and enjoyable at any time, anywhere, and on any device. On the foundation of smart city environment, human computer interaction, intelligent services, and universal device connectivity, Cyber Physical Computing for Cyber Physical systems has recently been investigated. However, in this proposal, a cognitive inspired framework for securing CPS is scrutinized. The cognitive ability is conceded to the search engines by updating the PageRank ranking methodology. The proposed framework, named SecureCPS is trained with real time collective dataset for marking the relevancy of web page with the support the facial expressions. The eye regions are marked using Focal Point Detector algorithm. The framework is validated with machine learning models and resulted in achieving 98.51% accuracy and its outperforms the existing frameworks. 相似文献
10.
《Research Policy》2019,48(7):1633-1646
Drawing on data from an original survey of UK and US publicly traded knowledge-intensive business services (KIBS) firms, we investigate what types of KIBS firms collaborate with universities and consider the collaboration important for their innovation. First, we find that science-based KIBS firms (those engaged in a science, technology, and innovation [STI] mode of organizational learning), like science-based manufacturing firms, are active collaborators with universities for innovation. This relationship is further enhanced if these firms also provide highly customized services. Second, in contrast to the existing literature suggesting that firms engaged in a doing, using, and interacting (DUI) mode of organizational learning do not regard collaboration with universities as important for their innovation, we find that KIBS firms engaged in a DUI mode of organizational learning and offering highly customized services are active collaborators with universities for innovation, despite the fact that they may not possess highly formalized scientific knowledge. These findings suggest that KIBS firms co-create knowledge with universities differently than manufacturing firms. Moreover, the findings highlight the wide variety of roles that KIBS firms play in innovation networks with universities. 相似文献
11.
《Information processing & management》2022,59(2):102880
Predictive computation now is a more and more popular paradigm for artificial intelligence. In this article, we discuss how to design a privacy preserving computing toolkit for secure predictive computation in smart cities. Predictive computation technology is very important in the management of cloud data in smart cities, which can realize intelligent computing and efficient management of cloud data in the city. Concretely, we propose a homomorphic outsourcing computing toolkit to protect the privacy of multiple users for predictive computation. It can meet the needs of large-scale users to securely outsource their data to cloud servers for storage, management and processing of their own data. This toolkit, using the Paillier encryption system and Lagrangian interpolation law, can implement most commonly basic calculations such as addition, subtraction, multiplication and division etc. It can also implement secure comparison of user data in the encrypted domain. In addition, we discuss how to implement the derivative of polynomial functions using our homomorphic computing encryption tool. We also introduce its application in neural networks. Finally, we demonstrate the security and efficiency of all our protocols through rigorous mathematical analysis and performance analysis. The results show that our toolkit is efficient and secure. 相似文献
12.
对话学习是一种有效的学习方式,是完整学习体系的一部分.日本学者佐藤学认为,学习是“构筑世界”、“构筑伙伴”、“构筑自身”三位一体的对话性实践,提供了构筑学习共同体的可能性.基于佐藤学的对话学习理论建设小型学习共同体.小型学习共同体具有社会强化、信息交流两个基本功能.小型学习共同体能够有效地增加同学之间的交流,增进学生对集体的归属感和对自身的认同感. 相似文献
13.
《International Journal of Information Management》2016,36(1):155-166
This paper presents a systematic approach to develop a resilient software system which can be developed as emerging services and analytics for resiliency. While using the resiliency as a good example for enterprise cloud security, all resilient characteristics should be blended together to produce greater impacts. A framework, cloud computing adoption framework (CCAF), is presented in details. CCAF has four major types of emerging services and each one has been explained in details with regard to the individual function and how each one can be integrated. CCAF is an architectural framework that blends software resilience, service components and guidelines together and provides real case studies to produce greater impacts to the organizations adopting cloud computing and security. CCAF provides business alignments and provides agility, efficiency and integration for business competitive edge. In order to validate user requirements and system designs, a large scale survey has been conducted with detailed analysis provided for each major question. We present our discussion and conclude that the use of CCAF framework can illustrate software resilience and security improvement for enterprise security. CCAF framework itself is validated as an emerging service for enterprise cloud computing with analytics showing survey analysis. 相似文献
14.
区块链技术是图书馆在云计算、物联网、大数据、智慧概念后的又一次技术革新。区块链技术在图书馆的应用将改变读者利用图书馆的途径,实现从目前的网络信息服务向价值服务的图书馆智慧服务的变革。图书馆在智慧服务中融合进区块链理念,可以推动优势资源的共建,开拓低成本的资源共享市场。区块链技术去中心化、共识机制、时序稳定、可靠数据关系的4个主要特征,决定了该技术在图书馆智慧服务的可行性。区块链技术在数字货币、金融交易与诚信、人文社科应用领域发展的3个阶段,决定了该技术在图书馆智慧服务的必要性。区块链技术助力图书馆智慧服务在管理体制、机构库建设、知识交易服务模式上的转变,满足读者对馆内设备空间使用与网络学习交流平台的智慧服务需求,是实现图书馆服务以读者阅读需求为中心的捷径。 相似文献
15.
Fernando Ornelas Tellez Alexander G. Loukianov Eduardo Jose Bayro Corrochano 《Journal of The Franklin Institute》2010,347(6):1015-1034
This paper presents a discrete-time decentralized neural identification and control for large-scale uncertain nonlinear systems, which is developed using recurrent high order neural networks (RHONN); the neural network learning algorithm uses an extended Kalman filter (EKF). The discrete-time control law proposed is based on block control and sliding mode techniques. The control algorithm is first simulated, and then implemented in real time for a two degree of freedom (DOF) planar robot. 相似文献
16.
Augmented reality is very useful in medical education because of the problem of having body organs in a regular classroom. In this paper, we propose to apply augmented reality to improve the way of teaching in medical schools and institutes. We propose a novel convolutional neural network (CNN) for gesture recognition, which recognizes the human's gestures as a certain instruction. We use augmented reality technology for anatomy learning, which simulates the scenarios where students can learn Anatomy with HoloLens instead of rare specimens. We have used the mesh reconstruction to reconstruct the 3D specimens. A user interface featured augment reality has been designed which fits the common process of anatomy learning. To improve the interaction services, we have applied gestures as an input source and improve the accuracy of gestures recognition by an updated deep convolutional neural network. Our proposed learning method includes many separated train procedures using cloud computing. Each train model and its related inputs have been sent to our cloud and the results are returned to the server. The suggested cloud includes windows and android devices, which are able to install deep convolutional learning libraries. Compared with previous gesture recognition, our approach is not only more accurate but also has more potential for adding new gestures. Furthermore, we have shown that neural networks can be combined with augmented reality as a rising field, and the great potential of augmented reality and neural networks to be employed for medical learning and education systems. 相似文献
17.
针对目前科技服务数据管理中普遍存在的数据标准多样化、壁垒多,数据交互及时性与安全性难以得到保障等问题,综合考虑安全性、易用性和可扩展性等,在科技服务数据管理中融入区块链即服务(BaaS)架构和思想方法构建数据共享系统结构,基于系统结构和数据分类结构构建数据共享实现机制。基于此机制,根据数据交互流程设计出科技服务数据分类结构,实现对数据整合及其所有权确定;利用智能合约和加密密钥实现对数据的有效检索和共享,并保证数据共享过程中的安全性和隐私性。研究以期为科技服务业的创新发展及其数据管理标准化提供参考。 相似文献
18.
入驻孵化器获得知识服务是初创企业创新成长的关键。但是,能否得到有效的知识服务,往往取决于服务供给过程中孵化器的角色定位以及在孵企业的能动性行为选择。为此,基于54家孵化器376个在孵企业的问卷数据,采用跨层回归分析模型,本研究分析了规范型和背书型两类不同知识服务对创新孵化绩效的影响机制,并重点考察了在孵企业组织学习的中介作用和创业警觉的调节影响。结果发现：规范型知识服务与创新孵化绩效之间有倒U型关系,而背书型知识服务对创新孵化绩效有正向影响;在孵企业的获得式学习在两种知识服务与创新孵化绩效之间发挥中介作用;创业警觉不仅正向调节获得式学习和创新孵化绩效的关系,而且调节了获得式学习的中介效应。研究结果有助于理解引起差异化创新孵化绩效的内在原因,为孵化器改善知识服务质量提供借鉴。
〖HT5”H 相似文献
19.
《Information processing & management》2022,59(4):102967
Graph-based multi-view clustering aims to take advantage of multiple view graph information to provide clustering solutions. The consistency constraint of multiple views is the key of multi-view graph clustering. Most existing studies generate fusion graphs and constrain multi-view consistency by clustering loss. We argue that local pair-view consistency can achieve fine-modeling of consensus information in multiple views. Towards this end, we propose a novel Contrastive and Attentive Graph Learning framework for multi-view clustering (CAGL). Specifically, we design a contrastive fine-modeling in multi-view graph learning using maximizing the similarity of pair-view to guarantee the consistency of multiple views. Meanwhile, an Att-weighted refined fusion graph module based on attention networks to capture the capacity difference of different views dynamically and further facilitate the mutual reinforcement of single view and fusion view. Besides, our CAGL can learn a specialized representation for clustering via a self-training clustering module. Finally, we develop a joint optimization objective to balance every module and iteratively optimize the proposed CAGL in the framework of graph encoder–decoder. Experimental results on six benchmarks across different modalities and sizes demonstrate that our CAGL outperforms state-of-the-art baselines. 相似文献
20.
With the development of information technology and economic growth, the Internet of Things (IoT) industry has also entered the fast lane of development. The IoT industry system has also gradually improved, forming a complete industrial foundation, including chips, electronic components, equipment, software, integrated systems, IoT services, and telecom operators. In the event of selective forwarding attacks, virus damage, malicious virus intrusion, etc., the losses caused by such security problems are more serious than those of traditional networks, which are not only network information materials, but also physical objects. The limitations of sensor node resources in the Internet of Things, the complexity of networking, and the open wireless broadcast communication characteristics make it vulnerable to attacks. Intrusion Detection System (IDS) helps identify anomalies in the network and takes the necessary countermeasures to ensure the safe and reliable operation of IoT applications. This paper proposes an IoT feature extraction and intrusion detection algorithm for intelligent city based on deep migration learning model, which combines deep learning model with intrusion detection technology. According to the existing literature and algorithms, this paper introduces the modeling scheme of migration learning model and data feature extraction. In the experimental part, KDD CUP 99 was selected as the experimental data set, and 10% of the data was used as training data. At the same time, the proposed algorithm is compared with the existing algorithms. The experimental results show that the proposed algorithm has shorter detection time and higher detection efficiency. 相似文献