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检索条件"主题词=LM Algorithm"

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Research on Prediction Model of Optimal Coagulant Dosage in Water Purifying Plant Based On Nerual Network

Research on Prediction Model of Optimal Coagulant Dosage in ...

引用

2009 ISECS International Colloquium on Computing, Communication, Control, and Management

作者： Zheying SONG Yingbao ZHAO Xueling SONG Chaoying LIU College of Electrical Engineering & Informational Science Hebei University of Science of Technology Shijiazhuang,China

Coagulant dosing process is an important part in water reatment plan,it directly affects the water quality and operating costs of *** is very difficult to set up its mathematical model accurately basing on its reactive mechanism at presen .Factors that affect the coagulation effect are analyzed in this paper,then a BP neural network prediction model of coagulant dosage is established.A improved BP algorithm——lm algorithm is used to train the neural network,it can improve the data's convergent *** results show that the prediction accuracy of the BP neural network model is very *** online predictive control of coagulant dosage can be made basing on this model,so it can optimize the coagulant dosage.

关键词： Coagulant dosage BP neural network lm algorithm

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A FPGA power estimation method based on an improved BP neural network

A FPGA power estimation method based on an improved BP neura...

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International Conference on Intelligent Information Hiding and Multimedia Signal Processing

作者： Guochang Zhou Baolong Guo Xiang Gao Jing Ma Hongjie He Yunyi Yan China Academy of Space Technology (Xi'an) Xi'an 710000 China School of Aerospace Science and Technology Xidian University Xi'an 710071 China

ISBN: (纸本)9781509001897

Programmable logic device FPGA has characteristics of flexible design, high efficiency design, short development cycle and low cost. The power of FPGA is divided into static power and dynamic power. The static power is mainly decided by the temperature, it is easy to get power by building a simple model. But the dynamic power is decided by many kinds of design resources. This article focuses on XC4VSX55 FPGA chip and studies the process of its power model, especially proposes a BP neural network algorithm combines adaptive learning rate algorithm with Levenberg-Marquardt. Specific implementation is as follows, firstly, gets the sample data provided by XPower Estimator, then trains the sample data by BP neural network, and estimates the intrinsic links through the weights and thresholds of network, finally, obtains the power model. This article provides a power model, and the improved BP network algorithm not only ensures the accuracy of the training results, but also improves the convergence speed.

关键词： FPGA BP neural network XPower Estimator lm algorithm

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Prediction of Stock Index Based on BP Neural Network

Prediction of Stock Index Based on BP Neural Network

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作者： Zhun Jiang Peng Zhu School of Economics and Management Nanjing University of Science and Technology

With the continuous development of China's economy in recent years, more and more investors are devoted in stock market and the changes of stock market are related to the vital interests of every shareholder. In the mature market economy, the index related to stock price and trading volume is the important basis for investors to make decisions and the barometer of the national economy at the same time. Therefore, the method to effectively forecast the stock index is particularly important. First, the paper introduces the basic situation of Shanghai Composite Index and Shenzhen Composite Index. Then we make the relevant introduction of BP neural network. Next,we introduce how to construct the BP(Back Propagation) neural network model optimized by lm(Levenberg-Marquard) algorithm according to the nonlinear characteristics of the stock market for further forecasting the closing prices of Shanghai Composite Index and Shenzhen Composite Index in order to test the validity of BP neural network in stock forecasting by the comparison between forecasts and actual stock prices, to provide some help and reference for investors' investment and government's macro-control.

关键词： Stock index forecast BP neural network lm algorithm

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Antenna Recognition Based on BP Neural Network

Antenna Recognition Based on BP Neural Network

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The Sixth Asia-Pacific Conference on Environmental Electromagnetics(CEEM’2012)

作者： ChunyanZhao~1,Dan Shi~2,Yougang Gao~3 School of Electronic Engineering,Beijing University of Posts and Telecommunications Beijing,100876,P.R.China

This paper studies several commonly used algorithms in the BP neural *** the BP neural network under these different algorithms can see the various performance of their *** study of both classical BP algorithm and lm algorithm will find the improvements of lm *** addition,practical applications show the following two *** one hand,different BP algorithm impacts the speed of the *** the other,the number of hidden layer neurons is also a sensitive factor to the performance of BP neural network. On the basis of the BP neural network,we want to build a suitable antenna model and use it in the identification of the antennas,it will have great practical significance.

关键词： BP neural network hidden layer nodes classic BP algorithm lm algorithm

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RESEARCH ON INTRUSION DETECTION SYSTEMS BASED ON LEVENBERG-MARQUARDT algorithm

RESEARCH ON INTRUSION DETECTION SYSTEMS BASED ON LEVENBERG-M...

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2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

作者： MING-QING LING WEI-WEI LIU School of Computer and Information Technology Beijing Jiaotong UniversityBcijing 100044 China Air School of Computer and Information Technology Beijing Jiaotong UniversityBcijing 100044 China

Intrusion detection system is a hot spot in the researching domain of information security. The paper puts forward an intrusion detection model called lmBP. Firstly the paper does a research on different optimal algorithms of BP (Back Propagation) networks and then combines improved BP algorithm with Levenberg-Marquardt algorithm to device lmBP. Based on this model the lm-HIDS intrusion detection system is established. The result of the experiment shows that it is an efficient way to detect host intrusion by applying Levenbcrg-Marquardt algorithm to optimize BP network.

关键词： Information security Intrusion detection Neural Network lm algorithm

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A Reliability-Based SNR Estimation Method in Turbo Detection Systems

A Reliability-Based SNR Estimation Method in Turbo Detection...

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IEEE Vehicular Technology Conference

作者： Li Qiang Shaoqian Li Nion Key Lb of Counicion Universiy of Eecronic Science nd Technoogy of Chin Chengdu 610054 P.R. Chin

ISBN: (纸本)1424402638;9781424402632;1424402646

In this paper, we analyze the sensitivity of MAP algorithm and its reduced ones, as Max-Log-MAP and Scaled Max-Log-Map, to SNR mismatch in turbo detection systems. And then, we propose a new reliability-based SNR estimation method using the soft extrinsic information output from SMlm decoder. Next, a new turbo equalization scheme is also provided with the new SNR estimation algorithm. Finally, the performance of turbo equalization systems are evaluated using our new scheme. The simulation results show that our equalization scheme performs very close to the lm algorithm with known channel SNR, although it does not need pilot symbols.

关键词： equalisers maximum likelihood detection maximum likelihood estimation turbo codes lm algorithm MAP algorithm SMlm decoder log maximum a posteriori algorithm reliability-based SNR estimation method scaled max-log-map soft extrinsic information output turb Equalizers maximum likelihood detection turbo codes maximum likelihood estimation Detection systems Least mean square algorithm Worm gears Turbo

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Compared Several Neural Networks algorithm in GPS Height Conversion

Compared Several Neural Networks Algorithm in GPS Height Con...

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2010 Second IITA International Conference on Geoscience and Remote Sensing (IITA-GRS 2010)

作者： Hu Chuan Institute of Engineering Surveying Sichuan College of Architectural Technology Deyang,China

Neural network height fitting method was one of the best methods at present. Neural network parameter,especially the network training function was one of the most important factors to affect the network performance and accuracy. This paper analyzed the relationship between several important neural network algorithms and their characteristics;Anglicizing and comparing speed and accuracy of each algorithm training by an instance data,and finally obtained that lm algorithm was the most appropriate algorithm for GPS height conversion.

关键词： BP neural network GPS height conversion network performance lm algorithm

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A Camera Self-calibration Method Based on Hybrid Optimization algorithm 2nd

A Camera Self-calibration Method Based on Hybrid Optimizatio...

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Second International Symposium on Electronic Commerce and Security(第二届电子商务与安全国际研究大会)(ISECS 2009)

作者： Li QiShen Lin LiCai Jiang ZeTao School of Computing Nanchang Hangkong University Nanchang Jiangxi Province 330063 China

ISBN: (纸本)9781424442843

A new camera self-calibration approach is presented by combining an improved Genetic algorithm (GA) with Levenberg-Marquardt (lm) algorithm. Firstly, the simplified Kruppa equation defined by Hartley is translated into the optimized cost function. Secondly, the minimum value of the optimized cost function is calculated by a hybrid optimization algorithm which combines the improved GA with lm algorithm. Finally, the intrinsic parameters of the camera are obtained. Several experiments are implemented to demonstrate the validity and the performance of the presented approach. The results show that it is accurate, and the accuracy of the proposed method is obviously improved compared with the single optimization methods.

关键词： self-calibration kruppa equations GA lm algorithm

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OPTIMIZED ARITHMETIC USED IN GARBAGE POWER GENERATION PLANTS ADDRESSING

OPTIMIZED ARITHMETIC USED IN GARBAGE POWER GENERATION PLANTS...

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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： YUAN-SHENG HUANG YAN ZHENG GANG LUO School of Business Administration North China Electric Power University Baoding 071003 China School of Business Administration North China Electric Power University Beijing 102206 China

Neural network has ability of self-studying, self-adapting, fault tolerance and generalization. However, there are some defaults in its basic algorithm, such as low convergence speed, local extremes, and uncertain number of implied layer and implied notes. So there are some limitations in practice. In order to avoid these shortages, the paper solves these problems from two aspects. One is to adopt principle component analysis to select study samples and to make some of them containing more sample characteristics;the other is to train the network by using Levenberg-Marquardt backward propagation algorithm. Finally, an example is used to prove the new method is of high effectiveness and practicality in solving the addressing problem of garbage power generation plants.

关键词： Garbage power generation plant lm algorithm Neural network Location selection Principle component analysis

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Ultrasonic Parameter Estimation Using the Maximum Likelihood Estimation

Ultrasonic Parameter Estimation Using the Maximum Likelihood...

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International Conference on Electrical Engineering

作者： S. Laddada S. Lemlikchi H. Djelouah M. O. Si-Chaib Centre de Developpement des Technologies Avancees Laboratoire de Physique des Materiaux USTHB Laboratoire de Mecanique des Solides et Systemes UMB. Boumerdes

ISBN: (纸本)9781467366748

The estimation of the backscattered echo was performed using the Maximum Likelihood Estimation (MLE). The backscattered ultrasonic echo is modeled as a nonlinear function of a set of parameters using the Gaussian echo model corrupted with an additive noise. Because of the white Gaussian noise (WGN) assumption, the estimation problem reduces to a least squares estimation. Thus, the nonlinear least square curve fitting with the Levenberg-Marquardt (lm) optimization algorithm was tested in the estimation procedure. The results are compared with existing results from the literature. To improve the goodness of the fit, the multivariate denoising procedure were applied as a preprocessing operation. Then, the efficiency and robustness of the lm algorithm are evaluated for both denoised and noisy signals.

关键词： Ultrasonic echo Parameter estimation MLE lm algorithm Multivariate Wavelet Denoising

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