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检索条件"任意字段=2nd International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering"

共 1404 条记录，以下是621-630 订阅

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A distributed Spare Parts Warehouse Allocation Strategy for Automobile Industry Chain Based on parallel Genetic Algorithm 2

A Distributed Spare Parts Warehouse Allocation Strategy for ...

引用

2nd international conference on Control Science and Systems engineering (ICCSSE)

作者： Lv, Rui Sun, Linfu Southwest Jiaotong Univ Sichuan Prov Key Lab Mfg Ind Chain Collaborat & I Chengdu Peoples R China

ISBN: (纸本)9781467398725

Aimed at inventory allocation needs with timeliness and accuracy of distributed spare parts warehouses, a collaborative allocation model for spare parts is proposed. Based on an analysis of the characteristics and defects of the genetic algorithm, a distributed inventory allocation strategy based on the parallel genetic algorithm is proposed, and a coarse parallel genetic algorithm within the framework of MapReduce is realized. The proposed strategy and algorithm together reduce the heavy computation burden during the process of problem-solving which is based on the genetic algorithm. Effectiveness of the proposed strategy is verified based on the spare parts inventory data of providers on the automobile industry chain.

关键词： inventory allocation industry chain cloud computing genetic algorithm

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ANALYSIS OF DATA SECURITY IN cloud computing 2

ANALYSIS OF DATA SECURITY IN CLOUD COMPUTING

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2nd IEEE international conference On Advances in Electrical and Electronics, Information, Communication and Bio Informatics (IEEE AEEICB)

作者： Iyer, K. B. Priya Manisha, R. Subhashree, R. Vedhavalli, K. MOP Vaishnav Coll Women Autonomous Madras Tamil Nadu India

ISBN: (纸本)9781467397452

cloud computing is one of the increasing technology that is connected with grid computing, Utility computing, distributed computing. In today's world, securing of data plays a vital role. In the computing environment, data privacy and data security is popular in fields like government, industry, and business for the future development. These are inter-related to both hardware and software. Hence, this paper analyses the data security solutions in cloud computing.

关键词： Data security Privacy protection cloud computing

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Infrared Detection Platform Based on Mobile and cloud computing Technology

Infrared Detection Platform Based on Mobile and Cloud Comput...

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2017 2nd international conference on Applied Mechanics and Mechatronics engineering(AMME 2017)

作者： Li-qun NIU Zhi-xin ZHANG Fuyang Power Supply Company State Grid

With the continuous development of technology, mobile and cloud computing technology in the power industry has been widely used. Make full use of mobile and cloud computing technology, so that in all aspects of infrared detection work, in the infrared detection operations management, on-site standardization of operational processes and data templates, teamwork,communication and knowledge accumulation, give full play to mobile terminals and cloud computing platform characteristic. This can improve the traditional business model, the establishment of infrared detection site and state evaluation center real-time linkage of the new business model, improve on-site work efficiency, improve the level of fine management, give full play to the evaluation center expert resource advantages, effectively support the continuous development of infrared testing business.

关键词： Infrared detection Mobile and cloud computing technology

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Coupled Geomechanics and Reservoir Flow Modeling on distributed Memory parallel Computers 2

Coupled Geomechanics and Reservoir Flow Modeling on Distribu...

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2nd IEEE international conference on High Performance and Smart computing (IEEE HPSC)

作者： Luo, Jia Wang, Kun Liu, Hui Chen, Zhangxin Univ Calgary Dept Chem & Petr Engn Calgary AB T2N 1N4 Canada

ISBN: (纸本)9781509024032

A geomechanical model and a multiphase black oil model are iteratively coupled in this paper. parallel computing is employed to handle large scale problems by benefiting from its features of distributed memory storage and efficient runtime reduction. The finite element method and the finite difference method are employed to discretize the two models, respectively. The geomechanical model is developed with the capability of simulating the rock matrix deformation with complex constitutive laws and its effects on reservoir properties. The multiphase flow model is modified by introducing geomechanical variables in a conventional flow model. A coupling strategy is carefully proposed to enable tight and dynamic interactions between these two models, as well as improving parallel computational efficiency. Example problems are presented to demonstrate the utility and efficiency of the coupled models. Expected geomechanical phenomena are illustrated by numerical experiments and validated by commercial software. In addition, for testing the scalability behaviour, field scale problems with millions reservoir and geomechanical grid blocks are performed. The results show encouraging speedups which indicate the integrated models can be an efficient and useful tool for evaluating and analyzing oil and gas production of stress-sensitive reservoirs.

关键词： Geomechanics Iteratively Coupling parallel computing Reservoir Simulation

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Factors influencing cloud technology adoption in Australian organisations

Factors influencing cloud technology adoption in Australian ...

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international conference on Information Technology (INCIT)

作者： L N Prasanna Balaaooriya Santoso Wibowo Marilyn Wells Central Queensland University Rockhampton QLD AU School of Engineering & Technology Central Queensland University Melbourne Australia

ISBN: (纸本)9781538614327

The purpose of this paper is to investigate the relevant factors including security, perceived usefulness, and perceived ease of use affect employee's behavioral and adoption intentions of cloud technology in organisations. This study was carried out using the quantitative research methodology based on a survey distributed to information technology (IT) professionals in Australia. The survey questionnaire was developed based 6 hypotheses and 13 indicator variables. Around 220 valid responses were received and analyzed by adopting a two-tier approach consisting of (1) confirmatory factor analysis to confirm the reliability and validity of the latent variables, and (2) analysis of the structural model to confirm or reject the hypothesis. The finding of this study indicates that the hypotheses that have been developed are valid and can be adopted in an organisation. This study has found that cyber attacks and cloud reliability factors are insignificant and have no affects in the cloud adoption. Furthermore, this study suggests that approximately 37 % of other factors which are not covered in this study need to be considered during its adoption.

关键词： cloud computing Security Information technology Data privacy Australia Atmospheric measurements Particle measurements

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A double-stage hierarchical hybrid PSO-ANN model for short-term wind power prediction

A double-stage hierarchical hybrid PSO-ANN model for short-t...

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IEEE international conference on cloud computing and Big Data Analysis (ICCCBDA)

作者： Abinet Tesfaye Eseye Jianhua Zhang Dehua Zheng Han Li Gan Jingfu School of Electrical and Electronic Engineering Goldwind Science and Etechwin Electric Co. Ltd Beijing China Microgrid Platform R&D Department Goldwind Science and Etechwin Electric Co. Ltd. Beijing China School of Electrical and Electronic Engineering North China Electric Power University Beijing China State Grid Energy Conservation Service Tanshan Electric Power Utility China State Grid Co. Ltd. Beijing China

ISBN: (纸本)9781509045006

Power output of wind generators is always associated with some uncertainties due to wind speed and other weather parameters alteration, and precise short-term forecasts are essential for their efficient operation. This can efficiently support transmission and distribution system operators and schedulers to improve the power network control and management. In this paper, we propose a double stage hierarchical particle swarm optimization trained artificial neural network (double-stage hybrid PSO-ANN) model for short-term wind power prediction of a microgrid wind farm in Beijing, China. The model has two hierarchical stages. The first PSO-ANN stage employs numerical weather prediction (NWP) meteorological parameters to forecast wind speed at the wind farm exact site and turbine hub height. The second stage models the actual wind speed and power relationships. Then, the predicted next day's wind speed by the first stage is applied to the second stage to forecast next day's wind power. The proposed approach has attained significant prediction accuracy improvements. The performance of the proposed model is compared with other two prediction approaches and showed best accuracy improvement than both methods.

关键词： Predictive models Generators Microgrids Computational modeling Atmospheric measurements Particle measurements Springs

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Short-term wind power forecasting using a double-stage hierarchical hybrid GA-ANFIS approach

Short-term wind power forecasting using a double-stage hiera...

引用

IEEE international conference on cloud computing and Big Data Analysis (ICCCBDA)

ISBN: (纸本)9781509045006

Wind generation power output estimation is always associated with some uncertainties as a result of wind speed and other weather parameters intermittency, and accurate short-term predictions are important for their efficient operation. This can greatly help transmission and distribution system operators and schedulers to improve the power network control and management. In this paper, a double stage hierarchical genetic algorithm based adaptive neuro-fuzzy inference system (double-stage hybrid GA-ANFIS) approach is proposed for short-term wind power forecast of a microgrid wind farm in Beijing, China. The approach has two hierarchical stages. The first GA-ANFIS stage utilizes numerical weather prediction (NWP) meteorological parameters to predict wind speed at the wind farm exact site and turbine hub height. The second stage maps the actual wind speed and power relationships. Then, the forecasted next day's wind speed by the first stage is applied to the second stage to predict next day's wind power. The presented approach has achieved considerable prediction accuracy enhancement. The accuracy of the proposed model is compared with other four forecasting methods and resulted in the best accuracy improvement of all.

关键词： Springs Weather forecasting Forecasting Databases Pragmatics

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Load Balancing in cloud computing: Challenges & Issues 2

Load Balancing in Cloud Computing: Challenges & Issues

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2nd IEEE international conference on Contemporary computing and Informatics (IC3I)

作者： Joshi, Shalini Kumari, Uma Mody Univ Sci & Technol Comp Sci & Engn Lakshmangarh India

ISBN: (纸本)9781509052561

cloud computing is latest emerging technology for large scale distributed computing and parallel computing. cloud computing gives large pool of shared resources, software packages, information, storage and many different applications as per user demands at any instance of time. cloud computing is emerging quickly;a large number of users are attracted towards cloud services for more satisfaction. Balancing the load has become more interesting research area in this field. Better load balancing algorithm in cloud system increases the performance and resources utilization by dynamically distributing work load among various nodes in the system. This paper presents cloud computing, cloud computing architecture, virtualization, load balancing, challenges and various currently available load balancing algorithms.

关键词： cloud computing architecture virtualization load balancing

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Combined Approach to Reliability of Great Software Complexes for distributed computing with Big Data in Contemporary Physical Experiments 2

Combined Approach to Reliability of Great Software Complexes...

引用

2nd international Symposium on Stochastic Models in Reliability engineering, Life Science, and Operations Management (SMRLO)

作者： Ososkov, Gennady JINR Lab Informat Technol Dubna Russia

ISBN: (纸本)9781467399418

The new challenging era of scientific data management in the coming decade named "Big Data" requires giant complexes for distributed computing and corresponding grid-cloud internet services. Known common approaches to software reliability based on the probability theory or on considering software as an open non-equilibrium dynamic system cannot conform to advanced grid-cloud software management systems. Therefore to provide the optimality and reliability of such sophisticated systems we choose the imitative simulation method oriented on a knowledge of dynamics of the system functioning. A new grid and cloud service simulation system was developed in the JINR Dubna laboratory of information technologies which focused on improving the efficiency and reliability of the grid-cloud systems development by using work quality indicators of some real system to design and predict its evolution. For these purposes the simulation program is combined with real monitoring system of the grid cloud service through a special database. Some examples of the program applications to simulate a sufficiently general cloud structure, which can be used for more common purposes, are given.

关键词： grid computing system cloud computing reliability fault tolerance simulation

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parallel Simulation of Full-Field Polymer Flooding 2

Parallel Simulation of Full-Field Polymer Flooding

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2nd IEEE international conference on Big Data Security on cloud, IEEE BigDataSecurity 2016, 2nd IEEE international conference on High Performance and Smart computing, IEEE HPSC 2016 and IEEE international conference on Intelligent Data and Security, IEEE IDS 2016

作者： Wang, Kun Liu, Hui Luo, Jia Yu, Song Chen, Zhangxin Zhang, Peng Department of Chemical and Petroleum Engineering University of Calgary Canada College of Engineering and Applied Sciences Stony Brook University United States

ISBN: (纸本)9781509024025

In recent years, polymer flooding has become a mature technology to improve the reservoir recovery rate and has been successfully implemented in many oil fields. Because of high operating costs of a polymer flooding project and the impact to the environment, the polymer injected per unit volume should be tracked for each polymer flooding pattern. Hence, the full-field reservoir simulations with fine-scale grids are needed to capture fine-scale phenomena and to optimize the process. To meet these objectives, a polymer module has been developed in our in-house parallel black oil simulator, which allows parallel simulations using clusters and supercomputers. With our parallel simulator, the elapsed time of full-field simulations with millions of grid blocks can be reduced from days to hours or minutes, and even for a much larger model with hundreds of millions ofgrid blocks, the simulations can be finished in practical time. In order to guarantee the computational efficiency and the parallel scalability, an inexact Newton method is applied and a new CPR (Constrained Pressure Residual)-type preconditioner is designed. In this paper, a SPE10-based polymer flooding case is tested, the performance of nonlinear and linear solvers are robust, and an encouraging parallel scalability is obtained. The second case is a full-field polymer flooding case, for which a coarse grid model anda fine grid model are both used. The results show the differences of the oil production rate and the water cut, which illustrates the accuracy of fine-grid simulations. For the fine grid model, up to 1024 CPU cores are employed, and an excellent speedup is achieved. © 2016 IEEE.

关键词： Supercomputers

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