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International Conference on Smart Grid and Electrical Automation (ICSGEA)

作者： Mei, Li Xian Eurasia Univ Xian 710065 Shaanxi Peoples R China

ISBN: (纸本)9781538669532

Neural network has good fault-tolerant ability, classification ability, parallel processing ability and so on, so the research of software reliability model based on neural network is paid more and more attention. bp neural network has strong nonlinear mapping ability and flexible network structure, so bp neural network is currently used in various fields. In this paper, a software reliability model optimized by hidden layer bp neural network is proposed and the training process of bp algorithm on this model is described.

关键词： neural network Software reliability Software reliability bp algorithm

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An Improved bp algorithm over Out-of-order Streams for Big Data

An Improved BP Algorithm over Out-of-order Streams for Big D...

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8th International ICST Conference on Communications and Networking in China (CHINACOM)

作者： Wang, Kun Zhuo, Linchao Lu, Heng Guo, Huang Xu, Lili Zhang, Yuhua Nanjing Univ Posts & Telecommun Minist Educ Key Lab Broadband Wireless Commun & Sensor Networ Nanjing 210003 Jiangsu Peoples R China

ISBN: (纸本)9781479914067

Due to the difficulty of getting the association rules over out-of-order streams for big data, a new improved bp algorithm based on dynamic adjustment is proposed. We firstly use a dynamic adaptive structural adjustment mechanism to change the network training structure according to the environmental requirements, which can automatically remove invalid training node, and optimize the iterative training process. Secondly, we adjust three factors (i.e. learning index, momentum factor and scaling factor) during the learning process to speed up the learning response, and to enhance the stability of the network. Simulation results show that compared with traditional bp algorithm, this algorithm can get more convergence times, the convergence rate can be improved effectively, and finally obtain the association rules over out-of-order data streams.

关键词： bp algorithm Out-of-order Streams Machine Learning Big Data

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Design and Application of Interval Type-2 TSK Fuzzy Logic System Based on QPSO algorithm

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2018年第3期20卷 835-846页

作者： Fan, Qiu-feng Wang, Tao Chen, Yang Zhan, Zhi-feng Liaoning Univ Technol Coll Sci Jinzhou 121001 Peoples R China

Studies on interval type-2 TSK fuzzy logic system is a hot topic in the current academic area. Parameter identification is very important for system design. Commonly used parameter identification methods are the least-square algorithm, bp algorithm, etc., few scholars use QPSO algorithm for parameter identification. In this paper, we propose a design of interval type-2 TSK fuzzy logic system based on quantum behaved particle swarm optimization (QPSO) intelligent algorithm. Firstly, by combining the A1-C1, A2-C0, A2-C1 interval type-2 TSK fuzzy logic system with neural network, the fuzzy neural network system is designed. Then, the QPSO intelligent algorithm was used to tune the fuzzy neural network system parameters, and the designed system model is applied to predict the Nasdaq Composite Index and International Gold Prices. Both QPSO algorithm and bp algorithm have been used to train the system model. By comparing QPSO algorithm and bp algorithm, the performance index and simulation results illustrated the proposed model is effective and feasible, which can achieve a better performance. Finally, compare the performance of the four fuzzy logic systems, it can be seen the effect of A2-C1 fuzzy logic system is better than that of the other three fuzzy logic systems.

关键词： Fuzzy logic system Neural network QPSO algorithm bp algorithm Nasdaq Composite Index International Gold Prices

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A New bp algorithm and Its Application

A New BP Algorithm and Its Application

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2013 2nd International Conference on Mechanical Properties of Materials and Information Technology(ICMPMIT 2013)

作者： Fang Liu Yueguang Li Gansu Normal University for Nationalities

In this paper, based on the combination of Genetic algorithm and bp algorithm, a new algorithm is proposed in this paper. The bp operator is embedded in the genetic operation in the algorithm, the algorithm effectively assimilates the global optimization of genetic algorithm and fast convergence of bp algorithm, and it encodes the construction and the weights hybrid with real code and binary code, achieving the same step optimization of structure and weights. The simulation results show that, the new algorithm can quickly converge to the global optimal solution, but also can obtain the best approximation of weights in the network structure.

关键词： bp algorithm Genetic algorithm bp operator Binary code Weight

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An Improved bp algorithm and its Application

An Improved BP Algorithm and its Application

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2013 3rd International Conference on Advanced Measurement and Test(AMT 2013)

作者： Juping Peng Yueguang Li Gansu Normal University for Nationalities

Aiming at bp algorithm convergence slow and be prone to plunge a partial basis,an improved bp algorithm——ACbp algorithm is proposed in this paper,it has better diversity and global search *** ability of optimization for the algorithm is tested through numerical computation,the experimental demonstrates that the improved bp algorithm has better diversity and global search capacity than genetic algorithm,bp algorithm,ant colony algorithm and simulated anneal algorithm.

关键词： bp algorithm Ant colony algorithm ACbp algorithm Function problem

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Recurrent Neural Network Model for Prediction of Microclimate in Solar Greenhouse

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IFAC-PapersOnLine 2018年第17期51卷 790-795页

作者： Hongkang, Wang Li, Li Yong, Wu Fanjia, Meng Haihua, Wang Sigrimis, N.A. Key Laboratory on Modern Precision Agriculture System Integration Research of Ministry of Education China Agriculture University Beijing100083 China Key Laboratory of Agricultural Information Acquisition Technology Ministry of Agriculture China Agriculture University Beijing100083 China Department of Natural Resources Management & Agricultural Engineering Agricultural University of Athens Athens11855 Greece

A recurrent neural network(RNN) based dynamic back propagation(bp) algorithm model with historical internal inputs are developed to predict the temperature and humidity of a solar greenhouse in the north of China. Climate data including air and substrate temperature, air humidity, illumination and C02 concentration recorded over eight days were used to build and validate models for climatic prediction. In order to compare the accuracy of predictions, different performance measures, such as average relative error (ARE), mean absolute error (AME) and root mean square error (RSME), were calculated, for using bp and untrained RNN neural networks using the same processing. For the RNN model, a context layer as the last hidden layer output, is input with the next input to the next hidden layer, which is equivalent to the state feedback. The results demonstrate that the RNN-bp model provides reasonably good predictions with the RSME for temperature 0.751 and 0.781 for humidity, including both of the R2 is both above 0.9, which outperforms the compared models tested in this paper. © 2018

关键词： Recurrent neural networks Backpropagation Climate models Errors Forecasting Greenhouses Mean square error Predictive analytics Solar heating State feedback bp algorithm Dynamic back propagation Microclimate Prediction model Recurrent neural network (RNN) Recurrent neural network model Solar greenhouse Temperature and humidities

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The Study of RNN Enhanced Convolutional Neural Network for Fast Object Detection Based on the Spatial Context Multi-fusion Features 11

The Study of RNN Enhanced Convolutional Neural Network for F...

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11th International Symposium on Computational Intelligence and Design (ISCID)

作者： Wang, Ning Cai, Aihua Zhang, Shunsheng Univ Elect Sci & Technol China Res Inst Elect Sci & Technol Chengdu Sichuan Peoples R China

ISBN: (纸本)9781538685273

In object detection, the spatial context information of the actual scene can improve the accuracy of detection while current object detection methods based on deep learning usually relies on CNNs to combine the local geometric and texture features without using these context information. In this paper, we proposal a method inspired by RNN that can extract the spatial context features and design a lighter, faster and more accurate network model for object detection that can fuse these features into multi-scale feature maps from CNNs to generate more comprehensive multi-information fusion features as inputs of localization and classification tasks subnetwork. The spatial context features extractor can be trained by joining in the bp process of the entire model, and we give the detailed optimized derivation procedures. Then we also demonstrate the validity of our model by conducting the contrastive experiments on KITTI dataset.

关键词： object detection lightweight model spatial context fusion features bp algorithm

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Compressive sensing-based super-resolution DOA estimation for mechanical scanning radar

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JOURNAL OF ENGINEERING-JOE 2019年第21期2019卷 7800-7804页

作者： Cheng, Fanglei Wang, Hongyu Liu, Yang Beijing Inst Technol Sch Informat & Elect Beijing Peoples R China Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing Peoples R China

This study presents a novel super-resolution directions of arrival (DOA) estimation method for mechanical scanning radar by using the advanced compressive sensing algorithm. This method is implemented by constructing a signal model of the mechanical scanning radar through imitating the array radar signal model. Also then it established the compression relationship between the transmitted and received echo signals of the reader by sparsification technique of sending signals. Finally, the DOA estimation can be solved by employing advanced compressive sensing algorithm including basic pursuit (bp), orthogonal matching pursuit (OMP), regularised orthogonal matching pursuit algorithms and so on. Compared with the conventional super-resolution DOA estimation method such as multiple signal classification, the proposed method can distinguish two or more targets within one beamwidth more precisely. Compared with the earlier super-resolution DOA estimation method such as maximum likelihood, the proposed method can obtain more accurate and robust angle difference estimation and do not need to previously know the source number. Both simulated and experimental results show that the overall performance of the proposed DOA estimation is better than that of other methods.

关键词： direction-of-arrival estimation compressed sensing radar resolution radar receivers radar transmitters mechanical scanning radar arrival estimation method advanced compressive sensing algorithm array radar signal model regularised orthogonal matching pursuit algorithms multiple signal classification robust angle difference estimation received echo signal transmission compressive sensing-based super-resolution DOA estimation method directions of arrival estimation method received echo signal receiver sparsification technique bp algorithm basic pursuit algorithm OMP algorithm orthogonal matching pursuit algorithm maximum likelihood method

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Analysis of the Azimuth Ambiguity and Imaging Area Restriction for Circular SAR Based on the Back-Projection algorithm

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SENSORS 2019年第22期19卷 4920-4920页

作者： Du, Bang Qiu, Xiaolan Huang, Lijia Lei, Songlin Lei, Bin Ding, Chibiao Chinese Acad Sci Aerosp Informat Res Inst Beijing 100094 Peoples R China Univ Chinese Acad Sci Sch Elect Elect & Commun Engn Beijing 100049 Peoples R China Chinese Acad Sci Key Lab Technol Geospatial Informat Proc & Applic Beijing 100190 Peoples R China Chinese Acad Sci Inst Elect Beijing 100190 Peoples R China

Circular synthetic aperture radar (CSAR) has a 360 degrees observation capability on the central observation scenario. A typical way to process CSAR imaging is to cut data into small sub-apertures because most targets are only coherent at a very small observation angle. There are many sub-aperture imaging methods after development in recent years. The back-projection algorithm is widely used because it is simple and can be applied to an arbitrary trajectory. Because of the limitation of the Nyquist sampling frequency and influence of the antenna sidelobe, azimuth ambiguity is a phenomenon that may occur in the radar imaging process. The existing researches typically choose the back-projection (bp) imaging area according to the SAR platform flight path and the antenna beam width. The limitation of the CSAR imaging area and its azimuth ambiguity region are rarely analyzed theoretically. This paper focus on the sub-aperture imaging of CSAR, based on the bp algorithm, which derives the relationship of azimuth ambiguity with CSAR parameters such as the pause repeat frequency (PRF), slant range angle, velocity of radar platform, etc. This paper proposes an equation for the calculation of the azimuth ambiguity region and analyzes the limitations, which provides theoretical support for CSAR parameter design, imaging area selection, and azimuth ambiguity analysis.

关键词： circular SAR azimuth ambiguity bp algorithm synthetic aperture radar imaging

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A Further Research on Two-phase Decoding for GC-LDPC Codes 12

A Further Research on Two-phase Decoding for GC-LDPC Codes

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12th IEEE International Conference on Anti-counterfeiting, Security, and Identification (ASID)

作者： Zhou, Wei Zhang, Lijun Sun, Qiang Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing Peoples R China

ISBN: (纸本)9781538660638

For GC-LDPC code, a targeted decoding scheme is the two-phase decoding scheme, i.e., the local decoding phase and the global decoding phase. For both the phases, we find the direct application of log-domin belief propagation (bp) algorithm will lead to error. Hence, we propose an improved log-domin bp algorithm and it will be used in the two-phase decoding scheme. Since the two-phase decoding scheme has a large gain loss, we present a modified two-phase decoding scheme in order to further accelerate the convergence rate. Simulation results show that the modified two-phase decoder has a gain of about 0.2 dB compared to the two-phase decoder. Moreover, it also can reduce complexity by 33.4% in high SNR compared with the whole decoder.

关键词： GC-LDPC code bp algorithm the two-phase decoding algorithm the local decoder the global decoder

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