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检索条件"任意字段=3rd IEEE Intelligent Data Acquisition and Advanced Computing Systems"

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A BP Neural Network-based Approach to intelligent Computer Image Recognition

A BP Neural Network-based Approach to Intelligent Computer I...

引用

Power Electronics, Computer Applications (ICPECA), ieee International Conference on

作者： Jingwen Ze Tianjin University of Technology Tianjin China

The computer image recognition model based on BP neural network can effectively identify the convergence recognition error. To solve the problems of low convergence speed and inability to quickly reduce recognition errors in the practical application of traditional image recognition methods, an optimized model for computer image recognition based on GA & BP deep neural network algorithm is proposed through computer image data acquisition and processing, image recognition model construction based on BP neural network and computer image recognition model training.

关键词： Training Image recognition Computational modeling Neural networks data models Real-time systems Power electronics

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Accounting management for personal communications

Accounting management for personal communications

引用

International Conference on Universal Personal Communications

作者： J.M. Michaels M.E. Pontones Bell Communications Research Inc. Red Bank NJ USA

The paper focuses on the accounting management that may be done in the advanced intelligent network (AIN) network to support personal communication systems (PCS). The authors provide an overview of an end-to-end PCS network including a description of a wireless network and the AIN; they also focus on potential accounting management philosophies and the usage data that may be generated for PCS at the Service Switching Point and the Service Control Point. They finally provide a call delivery example to demonstrate how data generation and collection for automatic message accounting is envisioned to support PCS.< >

关键词： Personal communication networks Wireless networks intelligent networks Identity management systems Radio spectrum management Resource management Radio control Springs Telecommunication services Transfer functions

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Latency Reduction for Narrowband LTE with Semi-Persistent Scheduling

Latency Reduction for Narrowband LTE with Semi-Persistent Sc...

引用

ieee International Symposium on Wireless systems (IDAACS-SWS)

作者： Zubair Arnjad Axel Sikora Benoit Hilt Jean-Philippe Lauffenburger ivESK Offenburg University of Applied Sciences Offenburg Germany IRIMAS University of Haute Alsace Mulhouse France

ISBN: (纸本)9781538675885

The excessive control signaling in Long Term Evolution networks required for dynamic scheduling impedes the deployment of ultra-reliable low latency applications. Semi-persistent scheduling was originally designed for constant bit-rate voice applications, however, very low control overhead makes it a potential latency reduction technique in Long Term Evolution. In this paper, we investigate resource scheduling in narrowband fourth generation Long Term Evolution networks through Network Simulator (NS3) simulations. The current release of NS3 does not include a semi-persistent scheduler for Long Term Evolution module. Therefore, we developed the semi-persistent scheduling feature in NS3 to evaluate and compare the performance in terms of uplink latency. We evaluate dynamic scheduling and semi-persistent scheduling in order to analyze the impact of resource scheduling methods on up-link latency.

关键词： Long Term Evolution Dynamic scheduling Job shop scheduling Uplink Automation 3GPP Cellular networks

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RESEARCH AND DESIGN OF intelligent NAVIGATION data PLATFORM

RESEARCH AND DESIGN OF INTELLIGENT NAVIGATION DATA PLATFORM

引用

2014 ieee 3rd International Conference on Cloud computing and Intelligence systems

作者： Yiming Shen Yu Wu Rui Wan Guangdong Televehicle Information Technology Service Co. ltd

After studying the structure and model of existing navigation map data,this paper presented a design scheme of intelligent navigation data *** described the data model and data organization which was used by data platform,and designed conceptual model,logical model,physical model in *** paper achieved the construction of intelligent navigation data platform and provided strong support for various applications of telematics and intelligent tourism.

关键词： intelligent navigation,data Platform,Spatial data

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Integrative data Mining for Assessing International Conflict Events

Integrative Data Mining for Assessing International Conflict...

引用

International ieee Conference on intelligent systems, IS

作者： Francisco Azuaje Haiying Wang Huiru Zheng Chang Liu Hui Wang Ruth Rios-Morales Computer Science Research Institute University of Ulster Jordanstown UK School of Computing and Mathematics (SC&M) University of Ulster Jordanstown UK SC&M University of Ulster Jordanstown UK School of Computing and Mathematics University of Ulster Jordanstown UK School of Business Studies Trinity College Dublin Dublin Ireland

State failure has been traditionally defined as the collapse of national authority, which may be reflected in disasters such as wars and disruptive regime transitions. The availability of comprehensive datasets and the limitations exhibited by previous forecasting analyses led us to integrate different predictive resources and models through statistical analysis and machine learning. Here we demonstrate the predictive ability of unsupervised and supervised learning approaches to detecting meaningful relationships between country cases, encoded by several socio-economic indicators, and the emergence of violent conflicts. Two clustering-based analyses (Kohonen maps and a network-based approach) provided the basis for exploratory analyses that confirmed hypotheses about the relevance of the data and the differences between state failure types. We also illustrate the potential of a novel network-based clustering approach for sub-class discovery in the area of political instability analysis. Furthermore, we show significant relationships between the emergence of violent conflicts and a dataset of quantitative indicators of good governance, which allows the design of effective supervised and unsupervised classifiers. This study contributes to the development of intelligent data analysis techniques for supporting hypothesis generation and testing in international conflict analyses

关键词： data mining Failure analysis Availability Predictive models Statistical analysis Machine learning Supervised learning Self organizing feature maps data analysis Testing

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advanced sensing, degradation detection, diagnostic and prognostic capabilities for structural health management 7

Advanced sensing, degradation detection, diagnostic and prog...

引用

7th International Workshop on Structural Health Monitoring: From System Integration to Autonomous systems, IWSHM 2009

作者： Niblock, T. Mian, M. Clements, R. Darr, D. O'Day, J. Morse, J. Laskowski, B.C. Sims, M. Ooi, T.K. Corder, A. Analatom Incorporated 562 E. Weddell Drive SunnyvaleCA94089 United States Army Aviation and Missile Research Development and Engineering Center Redstone ArsenalAL35898 United States Missile Defense Agency 7100 Defense Pentagon WashingtonDC20301 United States

ISBN: (纸本)9781605950075

Analatom, Inc. is developing a Structural Health Monitoring (SHM) system which provides both corrosion and strain measurements, data streams from other sensors and systems, AI analysis, maintenance scheduling and an intuitive interfacei. This combination of data provides critical assessment of structural health, leading to prediction of failure and offers an intuitive interface for the end user. The SHM system's sensors as well can be permanently installed in high value structures, such as buildings, bridges, or aircraft, and are connected to data acquisition nodes where initial processing is performed. These nodes can also interact with 3rd party systems and sensors to provide a complete sensing solution. From the nodes, processed data is transmitted using a ZigBee/ieee 802.15.4 compliant low-power, self-organizing, self-healing wireless network to a central server hub where it can be combined with inspection and ancillary data (e.g. weather) for analysis and interpretation. Analysis and interpretation of multiple, independent, non-linear data streams is a complex task. A physical system having multiple classes of sensors, each sensor streaming asynchronous, localized real-time data readings presents to an analyst a burdensome and daunting mass of unprocessed, seemingly unrelated informationii. Approached individually, each independent data stream contains meaningful raw information which carries only localized insight and benefits at most. Attempting to synthesize these many localized sources of information into a higher level of informational enhancement for the monitored structure is a nontrivial task. Second Generation Neural Networks, incorporating adaptive, nonlinear MESH architectures, attempt to organize these disparate pools of information into an interconnected, interrelated network of relationships. AI modeling results in global anomaly detection and localized diagnostics no longer restricted to only individual, independent sources of input dataiii. The

关键词： data acquisition

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Evaluation of Adaptive computing Concepts for Classical ERP systems and Enterprise Services

Evaluation of Adaptive Computing Concepts for Classical ERP ...

引用

ieee International Conference on e-Commerce Technology (CEC)

作者： M. Wimmer V. Nicolescu D. Gmach M. Mohr A. Kemper H. Krcmar Technische Universität München Munich Germany

To ensure the operability and reliability of large scale enterprise resource planning systems (ERP), a peak-load oriented hardware sizing is often used. Better utilization can be achieved by employing an adaptive infrastructure based on smaller computational units in combination with an intelligent allocation management. The SAP University Competence Center (German SAP HCC) at the Technische Universitat Munchen provides support for 55 ERP training systems. The evaluation of the historical load data revealed that many applications exhibit cyclical resource consumption. In this paper we show the extraction of load patterns and present self-organizing controlling concepts in the context of the SAP HCC

关键词： Enterprise resource planning Hardware Sun data mining Quality of service Blades Large-scale systems Computational intelligence Management training Application software

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An experimental active-memory-based network element

An experimental active-memory-based network element

引用

International Symposium on High Performance Distributed computing

作者： A. Asthana M. Cravatts P. Krzyzanowski AT and T Bell Laboratories Inc. Murray Hill NJ USA

We describe a network element based on an active memory named SWIM (Structured Wafer-based intelligent Memory), designed for efficient storage and manipulation of data structures. The key architectural idea in SWIM is to put some processing logic inside each memory chip that allows it to perform data manipulation operations locally and to interact with a disk or a communication line through a backend port. The processing logic is specially designed to perform operations such as pointer dereferencing, memory indirection, searching and bounds checking efficiently. The network element is built using an interconnected ensemble of such memory logic pairs. A complex processing task can now be distributed between a large number of small memory processors each doing a sub-task, while still retaining a common locus of control in the host CPU for higher level administrative and provisioning functions. We argue that active memory based processing enables more powerful, scalable and robust designs for storage and communications subsystems, that can support emerging network services, multimedia workstations and wireless PCS systems. A complete parallel hardware and software system constructed using an array of SWIM elements has been operational for over a year.< >

关键词： intelligent networks intelligent structures data structures Logic design Communication system control Robustness Multimedia systems Workstations Personal communication networks Hardware

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MCAR: multi-class classification based on association rule

MCAR: multi-class classification based on association rule

引用

ACS/ieee International Conference on Computer systems and Applications

作者： F. Thabtah P. Cowling Y. Peng Modelling Optimisation Scheduling and Intelligent Control Research Centre University of Bradford UK Department of Computing University of Bradford UK

Summary form only given. Constructing fast, accurate classifiers for large data sets is an important task in data mining and knowledge discovery. In this research paper, a new classification method called multi-class classification based on association rules (MCAR) is presented. MCAR uses an efficient technique for discovering frequent items and employs a rule ranking method which ensures detailed rules with high confidence are part of the classifier. After experimentation with fifteen different data sets, the results indicated that the proposed method is an accurate and efficient classification technique. Furthermore, the classifiers produced are highly competitive with regards to error rate and efficiency, if compared with those generated by popular methods like decision trees, RIPPER and CBA.

关键词： Association rules data mining Classification tree analysis Decision trees Processor scheduling intelligent control Error analysis Marketing and sales Transaction databases Promotion - marketing

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Computer Vision System for Determining the Reference Point 3

Computer Vision System for Determining the Reference Point

引用

3rd ieee KhPI Week on advanced Technology, KhPI Week 2022

作者： Sheremet, Oleksii Kovalchuk, Oleh Sheremet, Kateryna Sadovoi, Oleksandr Kiriienko, Tetiana Sokhina, Yuliia Donbass State Engineering Academy Department of Electromechanical Systems of Automation and Electric Drive Kramatorsk Ukraine Donbass State Engineering Academy Department of Intelligent Decision Support Systems Kramatorsk Ukraine Dnipro University of Technology Department of Electric Drive Dnipro Ukraine Dniprovsk State Technical University Department of Electrical Engineering and Machinery Kamianske Ukraine

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

The stages of development and implementation of neural network methods for visual determination of the reference points coordinates of a specific technical object are considered. Publicly available information about artificial neural networks and computer vision is analyzed. The description of the proposed intellectual system is carried out, questions of data markup, as well as an artificial increase in their number, are raised. The resulting intelligent system has an average accuracy of 95.2%. © 2022 ieee.

关键词： Image classification

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