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International Conference on Intelligent Materials and Mechatronics (IMM 2013)

作者： Zhang, Han Guo, Ruifeng Geng, Cong Chinese Acad Sci Shenyang Inst Comp Technol Shenyang 110168 Peoples R China

ISBN: (纸本)9783037859353

In this paper, a new mathematical combined model and the corresponding solution algorithm were proposed by analyzing the characteristics of services resource combination in cloud manufacturing. Aiming at avoiding problems of uncertainty, coarse-grained, diversity and dynamic in the process of services resource combination, a hierarchical model based on the hierarchical manufacturing implementation processes was firstly proposed. Then, quality of service (QoS) has been chosen to evaluate effects of services combination. Finally, a annealing algorithm was developed to solve the proposed model. Simulation experiment results prove the validity of the model and algorithm.

关键词： Cloud manufacturing Hierarchical model annealing algorithm Service combination

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Leach-H: An Improved Routing Protocol for Collaborative Sensing Networks.

Leach-H: An Improved Routing Protocol for Collaborative Sens...

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International Conference on Wireless Communications and Signal Processing

作者： Wang, Wei Wang, Qianping Luo, Wei Sheng, Mengmeng Wu, Wanrong Hao, Li China Univ Min & Technol Dept Comp Sci & Technol Xuzhou Peoples R China

ISBN: (纸本)9781424448562

In order to prolong the WSN's lifetime, a refined protocol named LEACH-H (Hybrid Cluster Head Selection Leach) is proposed in this paper. In the first round of Leach-H, the base-station selects a cluster head set through adopting Simulated annealing algorithm;in the followed rounds, the cluster heads will select new cluster heads in their own cluster. This will not only solve the problem that the cluster heads are unevenly distributed in LEACH, but also maintain the characteristics of distribution. The energy consumption of the network is cut down and the live time of WSN is extended in Leach-H.

关键词： Leach annealing algorithm Cluster Head Reconstruction NCH (cluster member)

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RF characterization of polymer multi-walled carbon nanotube composites

RF characterization of polymer multi-walled carbon nanotube ...

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IEEE Conference on Antenna Measurements and Applications (CAMA)

作者： Miscuglio, M. Yahya, M. Hajj Savi, P. Giorcelli, M. Tagliaferro, A. Politecn Torino DET Turin Italy Politecn Torino Appl Sci & Technol Dept DISAT Turin Italy

ISBN: (纸本)9781479936786

A wide band microwave characterization of nanocomposites based on commercial multiwall carbon nanotubes (MWCNTs) and epoxy resin is presented. Field Emission Scanning Electron Microscopy is used for morphological samples analysis of nanocomposites and MWCNTs. Complex permittivity is measured using a commercial dielectric probe and a Network Analyzer. A statistical analysis based on one-way analysis of variance (ANOVA) technique is performed. The aim of this statistical analysis is to investigate concentration of nanoparticles inside the polymer matrix. It can be significantly different in nanocomposites even if the samples have similar electrical properties. The reflection coefficient of a single-layer structure backed by a metallic plate was simulated taking into account the value of the measured permittivity and the results compared with the measurements. A two-layer absorber was designed and optimized by means of an annealing algorithm.

关键词： field emission ion microscopy multi-wall carbon nanotubes nanocomposites nanoparticles permittivity polymers resins scanning electron microscopy statistical analysis ANOVA technique MWCNT RF characterization analysis of variance technique annealing algorithm complex permittivity dielectric probe epoxy resin field emission scanning electron microscopy metallic plate morphological sample analysis nanoparticle concentration network analyzer polymer matrix polymer multiwalled carbon nanotube composite reflection coefficient single-layer structure two-layer absorber wideband microwave characterization Carbon nanotubes Microwave theory and techniques Permittivity Permittivity measurement Polymers Reflection coefficient Transmission line measurements Reflection coefficient field emission scanning electron microscopy Microwave theory and techniques Dielectric constant metal plates Multi-Walled Nanotube Network analysers polymers Transmission line measurements Statistical methods Permittivity measurement Complex permittivity Nanocomposites Epoxy Resins Carbon Nanotubes

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PARAMETER ESTIMATION OF GAUSSIAN MIXTURE MODEL BASED ON VARIATIONAL BAYESIAN LEARNING 17

PARAMETER ESTIMATION OF GAUSSIAN MIXTURE MODEL BASED ON VARI...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Zhao, Linchang Shang, Zhaowei Qin, Anyong Tang, Yuan Yan Chongqing Univ Pattern Recognit Ctr & Comp Sci Chongqing 400044 Peoples R China Univ Macau Dept Comp Zhuhai Peoples R China

ISBN: (纸本)9781538652145

Parameter estimation of gaussian mixture model has recently seen significant activity in many areas of science and engineering, motivated by recent theoretical results for researching on global optimal convergence and interesting practical applications. In this paper, we present novel evaluation algorithm for estimating the parameter of gaussian mixture model based on Variational Bayesian Learning (VBL) principles. Starting from a traditional VBEM algorithm and analysing the convergence of the algorithm as an initial-value constraint, we develop an approach that is very effective in estimating the parameter of gaussian mixture model while providing high astringency performance. We provide empirical results and comparison with current VBEM algorithm that illustrate the effectiveness of this approach.

关键词： Parameter estimation Gaussian mixture model Variational bayes EM annealing algorithm Tsallis-DAVBEM

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Hearing Environment Recognition in Hearing Aids 12

Hearing Environment Recognition in Hearing Aids

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12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Zeng, Weihao Liu, Ming Harbin Inst Technol Shenzhen Grad Sch Key Lab IOT Terminal Pivotal Technol Shenzhen Peoples R China

ISBN: (纸本)9781467376822

The hearing environment recognition algorithm is one of the core algorithms of the modern digital hearing aids. It can recognize the quiet, noisy and musical environment under a variety of scenarios, such as street, train or restaurant scene in noise environment. It then adjusts the parameters of other hearing aids algorithms according to different audio environment. This paper presents a method to improve the training algorithm of Gaussian mixture models(GMMs), which uses fusion LBG clustering algorithm and annealing algorithm to initialize the value of GMM parameter means mu, instead of initializing it randomly in traditional way. The method can improve recognition accuracy by optimizing the GMM parameters. The experimental result demonstrates that the accuracy rate of the traditional GMMs algorithm is about 77%, while that of the method we proposed is about 85%. In the end, we continue to explore the influence of the selection of the MFCC features and Gaussian mixture numbers on the recognition rate.

关键词： Hearing environment recognition Hearing aids GMMs LBG algorithm annealing algorithm MFCC features

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An Ethnic Costumes Classification Model with Optimized Learning Rate 11

An Ethnic Costumes Classification Model with Optimized Learn...

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11th International Conference on Digital Image Processing (ICDIP)

作者： Zhang, Shuang Song, Zongxi Xian Inst Opt & Precis Mech CAS Xian 710071 Shaanxi Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (数字)9781510630765

ISBN: (纸本)9781510630765

In the convolutional neural network model, the learning rate represents the magnitude of the neural network parameters that change at each iteration. When the learning rate is too high, the loss function will oscillate without converging. When the learning rate is too low, the loss function converges slowly. How to set the appropriate value of the learning rate becomes an important issue. Based on the learning rate annealing algorithm, this paper sets the segmentation attenuation and adds periodic pulse perturbation. The learning rate gradually declines and rises at the end of the cycle, and then continues to fall. This prevents the network from oscillating at a local minimum or saddle point in the late training period due to the low learning rate [1]. Finally, this paper verifies the method in the application of ethnic clothing classification using the transfer learning VGG-16 model.

关键词： Learning rate annealing algorithm transfer learning image classification

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ALLOCATION OF REMOTELY SENSED DATA USING MARKOV MODELS FOR IMAGE DATA AND PIXEL LABELS

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Australian Journal of Statistics 1992年第3期34卷 361-374页

作者： Kiiveri, H.T. Campbell, N.A. CSIRO Division of Mathematics and Statistics Wembley Western Australia 6014 Private Bag P.O. Australia

For remotely sensed data, this paper reviews the Bayesian approach to the allocation of picture elements (pixels) to groups. Group labels are assumed a priori to be spatially correlated and, conditional on the labels, the image data are also assumed to be spatially correlated. The models considered have the property that the posterior distribution of the pixel labels given the image data inherits conditional independence constraints. Two allocation algorithms which exploit this fad are discussed. These algorithms are based on maximising the posterior distribution, and involve the use of neighbouring image and label data to update the label of any given pixel. The effect of spatial correlation in the image data on allocation performance is examined. Copyright © 1992, Wiley Blackwell. All rights reserved

关键词： allocation annealing algorithm conditional autoregressive models conditional independence cyclic ascent algorithm Markov random fields posterior distribution spatial dependence

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Analytical Study on the Optimization of Heliostat Field Layout Based on the Ray Tracing Method 3

Analytical Study on the Optimization of Heliostat Field Layo...

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3rd IEEE International Conference on Electrical Engineering, Big Data and algorithms, EEBDA 2024

作者： Sun, Nan Yang, Xiaoxu Ding, Zhen Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9798350380989

In this study, we propose plausible models for the heliostat field configuration, apply ray tracing to map the sun's light paths, and explore how the heliostat's distance and the quantity of effective intersections impact the interplay of incident and reflected sunlight. Furthermore, we leverage this approach to correlate a single heliostat's optical performance to its cosine efficiency, shadow-blockage efficiency, atmospheric transmissivity, receiver aperture efficiency, and mirror reflectivity. This study presents a mathematical model which employs mechanism analysis and vector transformation to build upon the Campo and radial staggered configurations of fixed-sun mirror fields. And utilizing geometric relationships, the model formulates a single-objective nonlinear optimization framework aimed at maximizing the annual average thermal power output per unit area of the mirror. Finally, under the constraints of the mirror field boundary, a heuristic algorithm is used to iterate the parameters of the heliostat in each region in order to determine the optimal size and number of mirrors, and an optimisation strategy is given. © 2024 IEEE.

关键词： annealing algorithm Campo layout method EB layout light tracing method particle swarm algorithm

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Network Mode based on Multi-communication Mechanism

Network Mode based on Multi-communication Mechanism

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2015 International Power,Electronics and Materials Engineering Conference(IPEMEC 2015)

作者： Fan Yibin Liu Zhifeng Zhang Sheng Lin Ying Department of Military Finance Military Economy Academy

ISBN: (纸本)9781510806474

For the sake of improving green energy-saving efficiency of the radio communication system,we proposed a green energy-saving algorithm for multichannel communication system based on the energy consumption model ***,mathematical model of the multi-channel energy consumption minimization problem was ***,we used PSO algorithm to solve mathematical model,and annealing operation of simulated annealing algorithm was introduced into the PSO algorithm,which would prevent the local optimal solution and promote the speed of *** the end,we used the simulation contrast experiments to test our algorithm *** results show that our algorithm can meet different user service requirements,and can reduce total transmission power and energy consumption of the system,which is in favor of environment protection.

关键词： Cognitive Radio Energy-saving PSO(Particle Swarm Optimization) annealing algorithm

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iHPSA: An improved bio-inspired hybrid optimization algorithm for task mapping in Network on Chip

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MICROPROCESSORS AND MICROSYSTEMS 2022年 90卷 1页

作者： Amin, Waqar Hussain, Fawad Anjum, Sheraz UET Taxila Dept Comp Engn Taxila Pakistan Dept Comp Sci CUI Wah Cantt Campus Wah Cantt Pakistan

System on a chip (SoC) is the leading technology in the recent global world of digitization. The classical bus based regular communication infrastructures of SoCs cannot handle the growing number of cores. Designers came up with new communication methods known as the network on chip (NoC) to solve this problem. NoC offers scalability, flexibility, modularity, and efficiency. As the number of cores of SoC keeps on increasing due to advancement in technology and shrinking size of transistors, the arrangement of cores on the NoC becomes more significant that can influence the Network on Chip's overall performance and efficiency. Therefore, there is always a need for efficient and intelligent mapping algorithms for achieving optimal mapping solutions since existing mapping techniques either do not achieve optimal results or possess more execution time. To resolve this issue, we proposed an improved hybrid particle swarm and simulated annealing optimization algorithm iHPSA. The proposed iHPSA combines Improved Particle Swarm Optimization and Simulated annealing for NoC mapping and incorporates a machine-learning K-means clustering algorithm to segregate tasks into clusters based on communication bandwidth. The Elbow method is used in the K-means clustering algorithm to predict the number of clusters in large applications intelligently. Comparative analysis of different performance factors shows that the proposed approach has performed better than the existing mapping algorithms. The proposed algorithm offers improved performance by reducing communication cost, latency, and power of the network. the proposed iHPSA shows an average enhancement on power reduction of 22.67%, 30.95% , 22.87%, 27.61%, 16.07%, 8.87%, 8.01% ,30% and 9% over PSO,SA,GA,ACO,BA,SCSO,BEMAP,CSO and ILP. Improved energy consumption by 5.70%, 20%, 25%, 24% and 4.09% over PSO, SA ,GA , BEMAP and CSO. iHPSA improved latency by 1.5% over PSO, 6.2% over SA, 6.67% over GA , 9.7% over BEMAP and 1.2% over CSO.

关键词： Network on chip Particle swarm optimization Simulated annealing Improved hybrid particle swarm and simulated annealing algorithm

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