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检索条件"任意字段=8th IFIP International Conference on Network and Parallel Computing"

共 1177 条记录，以下是561-570 订阅

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Accurate Inference of Rice Biomass Based on Support Vector Machine

Accurate Inference of Rice Biomass Based on Support Vector M...

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the 9th international conference on Computer and computing Technologies in Agriculture (CCTA 2015)

作者： Lingfeng Duan Wanneng Yang Guoxing Chen Lizhong Xiong Chenglong Huang College of Engineering Huazhong Agricultural University Agricultural Bioinformatics Key Laboratory of HubeiProvince Huazhong Agricultural University National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research Huazhong Agricultural University MOA Key Laboratory of Crop Ecophysiology and Farming System in the Middle Reaches of the Yangtze River Huazhong Agricultural University

ISBN: (纸本)9783319483566

Biomass is an important phenotypic trait in plant growth analysis. In this study, we established and compared 8 models for measuring aboveground biomass of 402 rice varieties. Partial least squares（PLS） regression and all subsets regression（ASR） were carried out to determine the effective ***, 6 models were developed based on support vector regression（SVR）. the kernel function used in this study was radial basis function（RBF）. three different optimization methods, Genetic Algorithm（GA） K-fold Cross Validation（K-CV）, and Particle Swarm Optimization（PSO）, were applied to optimize the penalty error C and RBF c. We also compared SVR models with models based on PLS regression and ASR. the result showed the model in combination of ASR, GA optimization and SVR outperformed other models with coefficient of determination（R） of 0.85 for the 268 varieties in the training set and 0.79 for the 134 varieties in the testing set, respectively. this paper extends the application of SVR and intelligent algorithm in measurement of cereal biomass and has the potential of promoting the accuracy of biomass measurement for different varieties.

关键词： Rice biomass Support vector regression Partial least squares All subsets regression Support Vector network Partial least squares aquifer storage and recovery Speech recognition Biomass Particle swarm optimization breeding Optimization methods Regression (Psychology)

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Dissolved oxygen prediction model which based on fuzzy neural network 7

Dissolved oxygen prediction model which based on fuzzy neura...

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7th ifip WG 5.14 international conference on Computer and computing Technologies in Agriculture, CCTA 2013

作者： Yalin, Liu Yaoguang, Wei Yingy, Chen Key Laboratory of Agricultural Information Acquisition Technology Ministry of Agriculture Beijing100083 China Beijing Engineering and Technology Research Center for Internet of Things in Agriculture Beijing100083 China China-EU Center for Information and Communication Technologies in Agriculture China Agricultural University Beijing100083 China Beijing Engineering Center for Advanced Sensors in Agriculture Beijing100083 China

ISBN: (纸本)9783642543401

In crab ponds, dissolved oxygen is the foundation for pond cultivation’s survival. the changes of dissolved oxygen content are influenced by multiple factors. Higher levels of dissolved oxygen content are crucial to maintaining healthy growth of crab breeding. Affected by physic-chemical process of aquatic water, the changes of dissolved oxygen content have a large lag. In order to solve the problem of dissolved oxygen forecast, the prediction model which based on fuzzy neural network has been proposed in this paper. It integrated the characteristic of learning fuzzy logic and neural networks optimized performance to realize the dissolved oxygen prediction. the prediction results have shown it more suitable for dissolved oxygen prediction than grey neural network method. the prediction accuracy can meet the need of dissolved control. © ifip international Federation for Information Processing 2014.

关键词： Fuzzy neural networks

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Communication security prognosis realized as the parallel dynamic auditing intelligent system 8

Communication security prognosis realized as the parallel dy...

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8th KES conference on Agent and Multi Agent Systems - Technologies and Applications, KES-AMSTA 2014

作者： Piech, Henryk Grodzki, Grzegorz Borowik, Piotr Czestochowa University of Technology Dabrowskiego 73 Czestochowa42201 Poland

ISBN: (纸本)9783319076492

Communication operations are realized according to cryptography protocols in a typical network. Such communication among users takes place on the basis of public keys, secrets, supplies, encrypted messages and nonces. the investigation of the communication run gives security information about forthcoming threats. the main goal of the research consists in the elaboration of a useful and simple (in the sense of complexity) prognosis algorithm adapted to an auditing form of investigation. the results of the prognosis presented in the time parameter about impending threats are dynamically changed, operation by operation. therefore, users can prepare a strategy of avoiding the closest (in the sense of time) or the most dangerous threat. the proposed approach is based on probability counting rules that guarantee fast realization at the cost of accuracy. the large scale of parallelization possibilities is also worth noticing. this follows from the independent module structure of fundamental security elements which are associated with dynamically designated counting threads. © Springer international Publishing Switzerland 2014

关键词： Intelligent systems

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the Research of Codeword Based on Fuzzy Hopfield Neural network

The Research of Codeword Based on Fuzzy Hopfield Neural Netw...

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10th international conference on Intelligent computing (ICIC)

作者： Fu, Xian Ding, Yi Hubei Normal Univ Dept Comp Sci & Technol Huangshi 435002 Peoples R China

ISBN: (纸本)9783319093338;9783319093321

Hopfield neural networks are known to cluster analysis and unsupervised learning programs. In this paper, a new Hopfield-model net called Corrected Fuzzy Hopfield Neural network (CFHNN) is proposed for vector quantization in image correction. In CFHNN, the Correct Fuzzy C-means (CFC) algorithm, modified from penalized fuzzy c-means, is embedded into Hopfield neural network so that the parallel implementation for codeword design is feasible. the proposed network also proposed to avoid the network to determine the weight factors of the energy function value. In addition, it plans to make e-learning training more quickly than FC and PFC, more effectively. In the experimental results, CFHNN method shows the FC and PFC method is relatively encouraging results.

关键词： Fuzzy Hopfield Corrected Fuzzy Hopfield Neural network Corrected Fuzzy c-means

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Page classifier and placer: A scheme of managing hybrid caches

Page classifier and placer: A scheme of managing hybrid cach...

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11th ifip WG 10.3 international conference on network and parallel computing, NPC 2014

作者： Yu, Xin Shi, Xuanhua Jin, Hai Liao, Xiaofei Wu, Song Li, Xiaoming Services Computing Technology and System Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China Department of ECE University of Delaware Newark DE United States

ISBN: (纸本)9783662449165

Hybrid cache architecture (HCA), which uses two or more cache hierarchy designs in a processor, may outperform traditional cache architectures because no single memory technology can deliver the optimal power, performance and density at the same time. the general HCA scheme has also been proposed to manage cache regions that have different usage patterns. However previous HCA management schemes control data placement at cache set level and are oblivious to software's different power and performance characteristics in different hardware cache regions. this hardware-only approach may lead to performance loss and may fail to guarantee quality of service. We propose a new HCA approach that enables OS to be aware of underlying hybrid cache architecture and to control data placement, at OS page level, onto difference cache regions. Our approach employs a light-weighted hardware profiler to monitor cache behaviors at OS page level and to capture the hot pages. With this knowledge, OS will be able to dynamically select different cache placement policies to optimize placement of data to achieve higher performance, lower power consumption and better quality of service. Our simulation experiments demonstrate that the proposed hybrid HCA achieves 7.8% performance improvement on a dual-core system compared to a traditional SRAM-only cache architecture and at the same time reduces area cost. © 2014 ifip international Federation for Information Processing.

关键词： Quality of service

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Combination of Self Organizing Maps and Growing Neural Gas 13

Combination of Self Organizing Maps and Growing Neural Gas

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13th ifip TC8 international conference on Computer Information Systems and Industrial Management Applications (CISIM)

作者： Vojacek, Lukas Drazdilova, Pavla Dvorsky, Jiri VSB Tech Univ Ostrava IT4Innovat 17 Listopadu 15-2172 Ostrava 70833 Czech Republic VSB Tech Univ Ostrava Dept Comp Sci Ostrava 70833 Czech Republic

ISBN: (纸本)9783662452370;9783662452363

the paper deals with the high dimensional data clustering problem. One possible way to cluster this kind of data is based on Artificial Neural networks (ANN) such as Growing Neural Gas (GNG) or Self Organizing Maps (SOM). the learning phase of ANN, which is time-consuming especially for large high-dimensional datasets, is the main drawback of this approach to data clustering. parallel modification, Growing Neural Gas with pre-processing by Self Organizing Maps, and its implementation on the HPC cluster is presented in the paper. Some experimental results are also presented.

关键词： self organizing maps growing neural gas high-dimensional dataset high performance computing

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A Path Planning Algorithm Based on parallel Particle Swarm Optimization

A Path Planning Algorithm Based on Parallel Particle Swarm O...

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10th international conference on Intelligent computing (ICIC)

作者： Dang, Weitao Xu, Kai Yin, Quanjun Zhang, Qixin Natl Univ Def Technol Coll Informat Syst & Management Changsha 410073 Hunan Peoples R China Nanchang Mil Acad Nanchang 330103 Jiangxi Peoples R China

ISBN: (纸本)9783319093338;9783319093321

A novel path planning algorithm based on parallel Particle Swarm Optimization (PSO) is proposed in this paper to solve the real-time path planning problem in dynamic multi-agent environment. this paper first describes the advantages of PSO algorithm in real time search problems, i.e. path finding problems. then considering the development trend of multiprocessors, the parallel PSO (PPSO) was proposed to speed up the search process. Due to the above mentioned advantages, we in this paper adopt the PPSO to distribute particles onto different processors. By exchanging data upon the shared memory, these processors collaborate to work out optimal paths in complicated environment. the resulting simulation experiments show that when compared with traditional PSO, using PPSO could considerably reduce the searching time of path finding in multi-agent environment.

关键词： Path Planning Particle Swarm Optimization parallelism Multiprocessor Multi-agent environment

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parallel Image Texture Feature Extraction under Hadoop Cloud Platform

Parallel Image Texture Feature Extraction under Hadoop Cloud...

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10th international conference on Intelligent computing (ICIC)

作者： Zhu, Hao-Dong Shen, Zhen Shang, Li Zhang, Xiao-Ping ZhengZhou Univ Light Ind Sch Comp & Commun Engn Zhengzhou 450002 Henan Peoples R China Suzhou Vocat Univ Dept Commun Technol Coll Elect Informat Engn Suzhou Peoples R China Tongji Univ Shanghai Coll Elect & Informat Engn Shanghai Peoples R China

ISBN: (纸本)9783319093338;9783319093321

With the increasing amount of digital image data, massive image process and feature extraction process have become a time-consuming process. As an excellent mass data processing and storage capacity of the open source cloud platform, Hadoop provides a parallel computing model MapReduce, HDFS distributed file system module. Firstly, we introduced Hadoop platform programming framework and Tamura texture features. And then, the image processing and feature texture feature extraction calculations involved in the process to achieve Hadoop platform. the results which comparison with Matlab platform shows it is less obvious advantage of Hadoop platform in image processing and feature extraction of lower-resolution images, but for image processing and feature extraction of high-resolution images, the time spent in Hadoop platform is greatly reducing, data processing capability the advantages is obvious.

关键词： Hadoop Tamura Texture Feature Image Processing Feature Extraction

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A fast algorithm of compressed sensing

A fast algorithm of compressed sensing

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international conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Hao Liu Yuehao Yan Junhai Wang Department of Computer Science Sichuan TOP Vocational Institute of Information Technology Chengdu China Department of Computer Engineering Chengdu Technology University Chengdu China

ISBN: (纸本)9781479972098

After studying the compressed sensing theory and its main reconstruction algorithm-Matching Pursuit (MP) algorithm, this paper proposes a new approach to improve the speed of MP algorithm, and it describes how to build a Beowulf parallel computing system with 8 PCs. Its parallel computations is implemented by Message-Passing-Interface(MPI), and a 100Mb/s high speed Ethernet network interconnects all PCs. Test is made using parallel computing program to measure the parallel efficiency of the system, results show that this approach can reduce the MP algorithm computing time-cost form 78 minutes with a PC to 11 minutes with 8 PCs.

关键词： Matching pursuit algorithms parallel processing Dictionaries Program processors Computers Compressed sensing Computational modeling

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network and parallel computing - 9th ifip international conference, NPC 2012, Proceedings

Network and Parallel Computing - 9th IFIP International Conf...

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9th ifip international conference on network and parallel computing, NPC 2012

ISBN: (纸本)9783642356056

the proceedings contain 75 papers. the topics discussed include: an application-level scheduling with task bundling approach for many-task computing in heterogeneous environments;knowledge-based adaptive self-scheduling;communication locality analysis of triplet-based hierarchical interconnection network in chip multiprocessor;reference variables for dynamic, reliable packet operations;dynamic spray and wait routing protocol for delay tolerant networks;dempster-shafer theory to identify insider attacker in wireless sensor network;breaking a robust remote user authentication scheme using smart cards;hybrid obfuscated javascript strength analysis system for detection of malicious websites;detection and mitigation of web application vulnerabilities based on security testing;small world asynchronous parallel model for genome assembly;and fast parallel garner algorithm for Chinese remainder theorem.

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