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检索条件"主题词=Back propagation algorithm"

共 277 条记录，以下是161-170 订阅

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Clustering based Short Term Load Forecasting using Artificial Neural Network

Clustering based Short Term Load Forecasting using Artificia...

引用

IEEE/PES Power Systems Conference and Exposition

作者： Jain, Amit Satish, B. Int Inst Informat Technol Power Syst Res Ctr Hyderabad Andhra Pradesh India

ISBN: (纸本)9781424438105

A novel clustering based Short Term Load Forecasting (STLF) using Artificial Neural Network (ANN) to forecast the 48 half hourly loads for next day is presented in this paper. The proposed architecture uses the historical load and temperature to forecast the next day load. It is trained using back propagation algorithm and tested. The daily average load of each day for all the training patterns and testing patterns is calculated and the patterns are clustered using a threshold value between the daily average load of the testing pattern and the daily average load of the training patterns. The results obtained from neural network are presented and the results show that the clustering based approach is more accurate.

关键词： Artificial Neural Network back propagation algorithm Clustering Short Term Load Forecasting

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Study of Digital Character Recognition Based on BP Neural Networks

Study of Digital Character Recognition Based on BP Neural Ne...

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2nd International Conference on Measurement, Instrumentation and Automation (ICMIA 2013)

作者： Yuan, Shuai Zhang, Guo Yun Wu, Jian Hui Guo, Long Yuan Hunan Inst Sci & Technol Dept Informat & Commun Engn Yueyang 414006 Hunan Peoples R China

ISBN: (纸本)9783037857502

A digital character recognition method is presented based on BP Neural Network. This paper preprocesses the digital character image and extracts character feature, then uses BP Neural Network to recognize digital character. back propagation algorithm seeks network weights to minimize training error in the solution space. A network with hidden layer is created at first, then an input sample vector is sent to network input terminal and the square error E between output values and training sample object output values is calculated. Above process is repeated for input samples of training sets until the error is reduced within the limits of the threshold. The results show that the method presented has good accuracy, quick speed and strong robustness for realtime application.

关键词： Digital character recognition back propagation algorithm Training sample BP Neural Network

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Relevance study of Data mining for the identification of negatively influenced factors in sick groups 1

Relevance study of Data mining for the identification of neg...

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International conference on Graph algorithms, High Performance Implementations and its Applications (ICGHIA)

作者： Aneeshkumar, A. S. Venkateswaran, C. Jothi Presidency Coll PG & Res Dept Comp Sci Madras 600005 Tamil Nadu India Presidency Coll Dept Comp Sci & Applicat Madras 600005 Tamil Nadu India

The application of medical data mining is emphasis with temporal data in this piece of writing. The application of computational methods in medical field is well known and which started in previous decades, but still now also lot of researches take place in artificial intelligence, knowledge discovery and mining. Correlating computational intelligence with medical intelligence to predict negatively influenced epidemiological factors in liver disorder patients. (C) 2015 The Authors. Published by Elsevier B.V.

关键词： Neural Networks back propagation algorithm Analysis of Variance

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Application of artificial neural network in optimal design of step motor 5

Application of artificial neural network in optimal design o...

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5th International Conference on Electrical Machines and Systems

作者： Chen, J Yu, ZM Xian Jiaotong Univ Xian 710049 Peoples R China

A neural network with back propagation algorithm is developed in this paper to identify the error patterns of the method of linear interpolation. Then the relationship between the input samples and the output error pa... 详细信息

ISBN: (纸本)7506251159

关键词： neural network back propagation algorithm step motor

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A hybrid Gravitational Search algorithm-Genetic algorithm for neural network training

A hybrid Gravitational Search Algorithm-Genetic Algorithm fo...

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21st Iranian Conference on Electrical Engineering (ICEE)

作者： Sheikhpour, Saeide Sabouri, Mahdieh Zahiri, Seyed-Hamid Birzeit Univ Fac Elect Engn Birjand Iran

ISBN: (纸本)9781467356343

Tuning optimum parameter of neural networks, such as weights and biases, has major effects on their performance improvement. Estimation of optimum values for these parameters requires strong and effective training methods, so that the error of the training data reaches its minimum. This paper presents, a suitable training method for optimizing neural networks parameters using a novel hybrid GA-GSA algorithm. Extensive experimental results on different benchmarks show that the hybrid algorithm, performs equal to or better than standard GSA, and backpropagation algorithm.

关键词： neural network gravitational search algorithm genetic algorithm back propagation algorithm

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A hybrid method based on neural networks and a meta-heuristic bat algorithm for stock price prediction 2

A hybrid method based on neural networks and a meta-heuristi...

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2nd International Conference on Knowledge Based Engineering and Innovation (KBEI)

作者： Golmaryami, Marjan Behzadi, Marziveh Ahmadzadeh, Marziyeh Shiraz Univ Technol Dept Comp Engn & Informat Technol Shiraz Iran

ISBN: (纸本)9781467365062

Recent developments in the stock market have created an urgent need for efficient methods to help stockholders take appropriate decisions about their stocks. Since large fluctuations occur in the stock market over time and there are many parameters which influence this, it seems difficult to make good decisions that are also well-timed. The purpose of this study is to apply artificial neural networks (ANNs), which can deal with time series data and nonlinear parameters, to predict the next day's stock price. This research has trained the proposed ANN with a meta-heuristic bat algorithm which has a fast and powerful convergence. The recommended method has been applied to stock price forecasting for the first time. This work has used a seven-year dataset of a private bank stocks in order to prove the performance of the suggested method. After data pre-processing, three types of ANNs (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) were employed to predict the stocks' closing price. Afterwards, MATLAB was used to evaluate the performance of these three methods by scoring the target of the mean absolute percentage error (MADE). This paper indicates that the bat algorithm adjusts the weight matrix of ANN more precisely than the two other algorithms. The results may be adapted to other companies' stocks.

关键词： Artificial Neural Networks back propagation algorithm Particle Swarm Optimization algorithm Bat algorithm Stock Market Forecasting

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A Parallel BP Neural Network Based on the FPGA

A Parallel BP Neural Network Based on the FPGA

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International Conference on Measurement, Instrumentation and Automation (ICMIA 2012)

作者： Guo Yu-Hui Zhou De-Tai Qian Xiang-Ping Zeng Xian-Qiang Chinese Acad Sci Inst Modern Phys 509 Nanchang Rd Lanzhou Gansu Peoples R China Lanzhou Univ Sch Nucl Sci & Technol Lanzhou Gansu Peoples R China

ISBN: (纸本)9783037855454

This paper, with the analysis of BP neural network learning and execution algorithm on single computer unit, a parallel neural network on many computer units is constructed, a system on programmable chip based on FPGA and uClinux is provided. Because it's flexibility and reliability, this parallel neural network can be widely used where there is a large quantity of data to be processed. In addition to it, the system based on the SOPC has good versatility and easy to transplant because the reconfiguration of the hardware logic and software system.

关键词： Neural network Field programmable gate array(FPGA) back propagation algorithm Parallel architecture System On Programmable Chip(SOPC)

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Optical Electronic Nose Based on Fe(III) Complex of Porphyrins Films for Detection of Volatile compounds

Optical Electronic Nose Based on Fe(III) Complex of Porphyri...

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1st International Conference on Materials and Applications for Sensors and Transducers (IC-MAST)

作者： Akrajas Salleh, Muhamad Mat Yahaya, Muhamad Univ Kebangsaan Malaysia Inst Microengn & Nanoelect Bangi 43600 Selangor Malaysia Univ Kebangsaan Malaysia Fac Sci & Technol Sch Appl Phys Bangi 43600 Selangor Malaysia

ISBN: (纸本)9783037852927

Electronic nose is a device that attempts to mimic the living being smell system for detection of particular gases or volatile compounds. This paper reports the development of an optical electronic nose using Fe(III) based metalloporphyrins Langmuir-Blodgett thin films as sensing elements for discriminating four volatiles, 2-propanol, acetone, cyclohexane and ethanol. A multilayer feed forward neural network was developed to classify the input vectors from these two sensors. After the network being trained 100 times and introduced to blind samples, it was found that there are three fault decision for propanol, two for acetone, five for cyclohexane and one four ethanol, during 50 times being recognized to the samples.

关键词： Optical electronic nose Neural network back propagation algorithm Metalloporphyrins

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Engine Performance Optimization using Machine Learning Techniques

Engine Performance Optimization using Machine Learning Techn...

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SAI Intelligent Systems Conference (IntelliSys)

作者： Dutta, Praneet Sharma, Sparsh Rathnam, Pranav A. VIT Univ Sch Elect Engn Vellore Tamil Nadu India VIT Univ Sch Mech Engn Vellore Tamil Nadu India

ISBN: (纸本)9781467376068

The purpose of this paper is to integrate the concept of Supervised Learning algorithms in Engine tuning. These days Machine learning has become a very valuable tool for prediction. A given subset of this domain involves using supervised algorithms to intake data, analyze the data and 'learn' from it. The more the data that is processed by it (training stage), the better it learns (Fitting Parameters on Training Set) and the better it will be able to predict (Prediction Stage). By feeding data to the system we are teaching the system about how the input parameters (plenum volume, exhaust and intake runner length, Engine rpm) in the data are inter-related with one another and how the values of a set of variables can change by changing the value of any one variable. The efficiencies of various regression models were used and neural networks were also implemented.

关键词： back propagation algorithm Regression Model Runner Length Plenum Volume Neural Networks

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Robust neural-fuzzy method for function approximation

Robust neural-fuzzy method for function approximation

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7th International Conference on Machine Learning and Cybernetics

作者： Shieh, Horng-Lin Chang, Po-Lun St Johns Univ Dept Elect Engn Taipei Taiwan Natl Taipei Univ Dept Elect Engn New Taipei 23741 Taiwan Lunghwa Univ Sci & Technol Dept Elect Engn Guiyang Peoples R China

ISBN: (纸本)9781424420957

The back propagation (BP) algorithm for function approximation is multi-layer feed-forward perceptions to learn parameters from sampling data. The BP algorithm uses the least squares method to obtain a set of weights minimizing the object function. One of main issues on the RIP algorithm is to deal with data sets having variety of data distributions and bound with noises and outliers. In this paper, in order to overcome the problems of function approximation for a nonlinear system with noise and outliers, a robust fuzzy clustering method is proposed to greatly mitigate the influence of noise and outliers and then a fuzzy-based data sifter (FDS) is used to partition the nonlinear system's domain into several piecewise linear subspaces to be represented by neural networks. Two experiments are illustrated and these results have shown that the proposed approach has good performance in various kinds of data domains with data noise and outliers.

关键词： back propagation algorithm fuzzy neural networks fuzzy clustering robust noises and outliers

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