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检索条件"任意字段=3rd Euro-NF Conference on Network Control and Optimization"

共 1644 条记录，以下是1151-1160 订阅

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Improving network performance with Rate Adaptation Algorithms for Vehicular Simulations 3

Improving Network performance with Rate Adaptation Algorithm...

引用

3rd International conference on Artificial Intelligence, Modelling and Simulation (AIMS)

作者： Nwizege, Kenneth Stephen, Agbeb N. Mmeah, Shedrack MacMammah, Michael Gibson, Irimiagha P. Ken Saro Wiwa Polytech Sch Engn Dept Elect & Elect Engn Bori Nigeria

ISBN: (纸本)9781467386753

Below the Media Access control (MAC) layer is the Physical (PHY) layer which deals with the actual transmission of the bits received from the MAC layer above into electromagnetic signals. This layer is optimized to implore power management in wireless networks. Power management is a crucial issue in wireless and mobile networks. In this paper, we propose an Adaptive Context-Aware Rate Selection (ACARS) algorithm to handle the issue of power consumption in wireless networks. This algorithm is implemented by optimizing the PHY layer to transmit efficiently as the number of nodes changes and we estimate the Signal-to-Noise Ratio (SNR) to the PHY layer. Results show that by using the appropriate power management technique, ACARS is reliable and efficient for power consumption in wireless networks which is a high demand for vehicular networks.

关键词： PHY layer mobile networks optimization wireless networks context-Information rate adaptation vehicular communication IEEE802.11p propagation phenomena power management

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Cooperative control of networked Autonomous Vehicles Using Convex optimization

Cooperative Control of Networked Autonomous Vehicles Using C...

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RSI/ISM International conference on Robotics and Mechatronics

作者： Mohsen Ahmadi Mousavi Behzad Moshiri Zainabolhoda Heshmati Faculty of New Sciences and Technologis University of Tehran Tehran Iran School of Electrical end Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781467372350

In this paper a distributed, mathematical and optimization-based planning problem is introduced to control motion of multiple vehicles as a team which are connected to each other by a communication network. This framework is defined based on a Linear Time Varying Model Predictive control (LTV-MPC). To do so, we define linear time varying constraints to cover obstacle avoidance and maintain connectivity missions as a multi criteria optimization problem. The final proposed MPC problem is converted to a real time convex optimization problem by some definitions and simplifying methods.

关键词： Cooperative control networked vehicles Model predictive control Convex optimization

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Comparison on energy-efficient cluster based routing algorithms in wireless sensor network 3rd

Comparison on energy-efficient cluster based routing algorit...

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3rd Information Systems International conference

作者： Dehghani, Shahrzad Pourzaferani, Mohammad Barekatain, Behrang Higher Educ Inst Allameh Naeini Fac Comp Engn Dept Software Engn Naein Iran Univ Isfahan Fac Comp Engn Dept Software Engn Esfahan Iran Islamic Azad Univ Najafabad Branch Fac Comp Engn Najafabad Iran

Wireless sensor networks(WSNs) nowadays considered as a hot research topic because of its wide range of applications in various fields. Recently, advancement in electronic communications has led to multi-purpose sensor nodes with low-cost and power consumption. Wireless sensor networks are composed of limited power sensors, which their power supply could not be replaced or recharged. So, less power consumption will increase the lifetime of these networks. Therefore, providing efficient routing algorithms with less energy consumption is desirable. Among many routing algorithms, approaches based on clustering, result less energy consumption. In this article, all well-known routing algorithms based on clustering which focus on saving energy got reviewed. Each algorithm is described in detail and its pros and cons are discussed explicitly. Then some important metrics such as scalability, message overhead and algorithm complexity are used for comparing cluster-based algorithms and give an insight to challenges in this field. (C) 2015 Published by Elsevier B.V.

关键词： Wireless sensor networks energy consumption optimization Clustering algorithms Clustering based routing

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DiverGene: Experiments on controlling Population Diversity in Genetic Algorithm with a Dispersion Operator

DiverGene: Experiments on Controlling Population Diversity i...

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3rd International conference on Innovative network Systems and Applications (iNetSApp) held in conjunction with Federated conference on Computer Science and Information Systems (FedCSIS)

作者： Strzezek, Anna Trammer, Ludwik Sydow, Marcin Polish Japanese Inst Informat Technol Ul Koszykowa 86 PL-02008 Warsaw Poland Polish Acad Sci Inst Comp Sci PL-00901 Warsaw Poland

ISBN: (纸本)9788360810668

We present diverGene - a novel, diversity-aware population selection operator for genetic algorithm - to be used especially for particularly complex and multi-criteria optimisation problems. Genetic algorithm is one of the most known evolutionary algorithms for solving hard optimisation problems. Many attempts have been made to improve its convergence rate and quality of the result. In this paper we propose a novel extension of the selection operator that makes it possible to control the level of diversity in the population. We discuss its theoretical background, including its computational hardness and propose an efficient way of computing it. The approach is implemented and tested on three hard optimisation problems: Knapsack Problem, Travelling Salesman Problem and a relatively new Travelling Thief Problem that might be viewed as the composition of the latter two. We report experimental results that seem to indicate that the novel approach has a potential to improve the quality of the results for some hard optimisation problems.

关键词： genetic algorithms knapsack problems travelling salesman problems DiverGene convergence rate diversity-aware population selection operator evolutionary algorithms genetic algorithm hard optimisation problems knapsack problem multicriteria optimisation problems travelling salesman problem travelling thief problem Approximation methods Cities and towns Dispersion Genetic algorithms optimization Sociology Statistics

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Research summary of the Micro Grid Energy Management System control Structure

Research summary of the Micro Grid Energy Management System ...

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2015 3rd International conference on Mechanical Engineering and Intelligent Systems(ICMEIS 2015)

作者： Xiaocen Cai Dongtao Wang Zhilong Gao Tianjin University of Technology and Education: Joint Lab of Information Sensing & Intelligent Control

ISBN: (纸本)9781510812031

With the continuous development of micro grid technology, the power energy management system has gradually become a research hotspot. Micro grid energy management system can be divided into two control structures, centralized control and decentralized *** multi-agent system is the best choice for these two kinds of structure. And then we introduced the multi-agent system building. Finally this paper summed up the problems that need to be solve in micro grid energy management: renewable energy and controllable load more uncertainty problem, the optimization of energy storage technology cooperation and joint scheduling problem, the micro grid communication design of energy management system and network security problem.

关键词： Micro power grid Energy management control structure

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A Short Term Load Forecasting Algorithm Based on Gray Elman Neural network and Genetic Algorithm

A Short Term Load Forecasting Algorithm Based on Gray Elman ...

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2015 3rd International conference on Machinery,Materials and Information Technology Applications(ICMMITA 2015)

作者： Baoyi Wang Zheng Wang Shaomin Zhang School of Control and Computer Engineering North China Electric Power University

Short term power load sample is highly variable, and the influence factors are not determined, the data sample is little. In view of the characteristics of the load, we combine the Grey Theory and Elman neural network to predict the short-term power load. Because the gray neural network convergence is slow, We introduce the genetic algorithm to the gray Elman neural network optimization, and propose the genetic algorithm to optimize the gray Elman neural network algorithm, the genetic algorithm to optimize the gray Elman neural network algorithm is applied to short-term load forecast. Experimental results show that the prediction accuracy is improved. The algorithm achieves fast convergence, and it is feasible and effective.

关键词： gray theory genetic algorithm Elman neural network load forecasting

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optimization of distributed energy resources to balance power supply and demand in a smart grid

Optimization of distributed energy resources to balance powe...

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International conference on Green Energy and Technology (ICGET)

作者： S.M. Al-imran M.A.R. Fuad T. Ahmed M.R. Ali M.N.I. Maruf Dept. of EEE Faculty of Engineering American International University-Bangladesh (AIUB) Dhaka Bangladesh

Energy crisis is one of the major problems for the economic growth and development of Bangladesh. The gap between power supply and demand is increasing day after day. Moreover, most of the power plants are based on fossil fuel and have the risk of being phased out in future. This paper aims to solve these problems by balancing the power supply and demand in a smart environment, focusing mainly on distributed energy resources (DER). The main DER components of the system are power plants based on renewable energy sources (RES). Since RES are intermittent, back up from fossil fuel based plants are also integrated in the final model to increase the system reliability. During off-peak hours residual energy from RES will be stored in the proposed storage arrangement. The proactive consumers (prosumer) in the demand side will have the scope to sell this stored energy to the national grid during peak hours in a proposed smart bilateral network. Finally, grid monitoring and metering interface with an advanced control mechanism has been developed, which is expected to increase the flexibility of the prosumer to handle their energy usage and costs.

关键词： Smart grids Biological system modeling Mathematical model Biomass Production Smart meters Data models

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Information collection system of agricultural traceability based on things

Information collection system of agricultural traceability b...

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2015 3rd International conference on Machinery,Materials and Information Technology Applications(ICMMITA 2015)

作者： Li Tingting Li Bo Huang Dechang School of Software Engineering East China Jiaotong University School of Information Engineering East China Jiaotong University

Things agriculture is an important development direction of networking applications, networking technology in the field of agriculture for the development of agriculture has brought immeasurable impetus and prospects immeasurable. In agriculture things, how can the production process the data collected for processing, analysis and display, making it better for agricultural services is needed to solve critical issues. Data processing agricultural Things is located in agricultural information networking application layer through data processing, integration and application to the development of scientific management decisions, to achieve the agricultural production process control.

关键词： Things agriculture Elman prediction model Stratified case-based reasoning network optimization

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A novel cross-layer adaptation and QoS optimization in LTE-A and beyond networks

A novel cross-layer adaptation and QoS optimization in LTE-A...

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IEEE conference on Wireless Communications and networking

作者： Sonia Ben Rejeb Nidal Nasser Sami Tabbane MEDIATRON Laboratory Higher School of Communications Ariana Tunisia

ISBN: (纸本)9781479984077

Among the major challenges in 3GPP LTE-A (3rd Generation Partnership Project Long Term Evaluation) and beyond networks are the convergence of services towards IP technology, the quality of service (QoS) and the maintenance of multimedia flows transmitted on wireless networking for mobile and heterogeneous users. In this environment, multimedia services must face various disadvantages generated by the unreliability of the wireless channel shared by several users. These new characteristics impose new requirements when designing wireless protocol, such as in LTE-A networks, where protocols must be dynamically adapted with the continuous changes of the radio operator state channel and seek at the same time to meet the QoS requirements with the supported applications. In this context, we will propose a new cross layer and performances optimization of the 3GPP LTE-A system. Our major contribution consists to set up coordinated interactions between high layers applications representing for example video streaming and those of low layers, such as network, MAC (Medium Access control) and physical layer. The information exchange between these layers will lead to optimize the application operation according to the changes observed on the radio operator channel. Thus, this solution would reduce the probabilities of the application dysfunction or interruption, while respecting the QoS constraints (time, throughput, PLR (Packet Loss Ratio) and maintain a constant flow for the user.

关键词： Streaming media Quality of service optimization Protocols Physical layer conferences

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A New Wind Power Forecasting Algorithm Based on Spark

A New Wind Power Forecasting Algorithm Based on Spark

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2015 3rd International conference on Machinery,Materials and Information Technology Applications(ICMMITA 2015)

作者： Shaomin Zhang Peng Chen Baoyi Wang School of Control and Computer Engineering North China Electric Power University

With the arrival of the era of big data, wind power forecasting data develops to the massive and multi-dimensional direction. Single computer lack of resources is difficult to solve the problem of wind power forecasting. In this paper, Spark cloud computing platform is introduced to solve the massive data problem that the traditional single machine can not deal with. The combination of BP neural network with the bacterial colony optimization algorithm can avoid the local optimum and improve the accuracy of forecasting results. In the experiment,the real data of a wind farm in Nei Mongol is used as the input data set and Spark cloud computing programming framework improve the parallel algorithm. The results show that the improved algorithm can increase the efficiency of prediction results about 10%.

关键词： Wind Power Prediction Spark Parallelization Improvement Artificial Intelligence

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