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检索条件"主题词=BP Algorithm"

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Fault Diagnosis Method of Distributed Power Distribution Network Based on Advanced Petri net 29

Fault Diagnosis Method of Distributed Power Distribution Net...

引用

第29届中国控制与决策会议

作者： Liu Yunjia Gao Yiwei Liu Jialiang Chu Yongjin State Key Laboratory of Operation and control of Renewable Energy & Storage Systems China Electric Power Research Institute School of Information Science & Engineering Northeastern University

ISBN: (纸本)9781509046584

A DG-based distributed fault diagnosis method based on bp neural network with dynamic adaptive fuzzy Petri nets is proposed to solve the problem that traditional fault diagnosis methods lead to complex matrix and switching *** this paper,the general fault diagnosis model is constructed,and the simplified model of protection information is processed in the form of *** the operation mode and protection are changed,the model need not be reestablished,and the logic of the protection circuit breaker error correction is used with high fault ***,bp algorithm is used to train the fuzzy parameters in the ***,simulation test is carried out for the distribution network with DG,which verifies the reliability and fastness of the method.

关键词： Petri net distributed power supply fault diagnosis bp algorithm

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Research on Fault Diagnosis of Fork Lift Truck Hydraulic System Based on Artificial Neural Network

Research on Fault Diagnosis of Fork Lift Truck Hydraulic Sys...

引用

International Conference on Measuring Technology and Mechatronics Automation

作者： Li, Heqing Tan, Qing Changsha Univ Sci & Technol Sch Automobile & Mech Engn Changsha Hunan Peoples R China Cent S Univ Sch Mech & Elect Engn Changsha Peoples R China

ISBN: (纸本)9780769535838

The structure and algorithm of bp neural net were described, the reatization process of the fault diagnosis of hydraulic system based on, bp neural net was discussed. According to the experiment and test of fault of fork lift truck hydraulic system, the bp net! has better learning function, high net convergence rate and high stability of learning and memory. The diagnosis results indicate that the presented diagnosis method has high reliability and can attain the expected results, which can be applied to fault diagnosis of hydraulic system.

关键词： bp algorithm Neural network hydraulic system fault diagnosis

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Application of GA-FNC in Crystallizer Liquid Level Control System

Application of GA-FNC in Crystallizer Liquid Level Control S...

引用

2nd International Conference on Manufacturing Science and Engineering

作者： Li, Ming Yang, Da Yong Nanchang Univ Sch Environm & Chem Engn Nanchang 330031 Jiangxi Peoples R China

ISBN: (纸本)9783037850374

This article discusses the control strategy of the steel casting system which possesses the characteristics of large inertia, time-varying and nonlinear. Aiming at getting the minimum deviation of liquid level, the control strategy uses the genetic algorithm to off-line optimize the parameters (c(ij),b(j)) of the Gaussian membership function and the network structure of fuzzy controller which affect the overall system firstly. Then, bp algorithm is used to online regulate and optimize the weight parameters of the control output which affect the system partly. Finally, the intelligent control system of the liquid level which is based on GA-FNC is simulated. The results show that the method can enhance the ability of self-learning and robustness of the system greatly and improve the stability of steel casting system significantly.

关键词： Crystallizer Genetic algorithm bp algorithm Fuzzy Control Robustness

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Construction and Optimization of Intention Recognition Model Based on IFPN

Construction and Optimization of Intention Recognition Model...

引用

International Conference on Fuzzy System and Data Mining (FSDM)

作者： Shen, Xiao-Yong Li, Jin Shi, Zhao-Hui Wang, Yi Air Force Engn Univ Air & Missile Def Coll Xian Peoples R China

ISBN: (纸本)9781614996194;9781614996187

A model based on intuition fuzzy petri nets (IFPN) aiming at the dynamic and uncertain problem of tactical intention recognition is proposed and the parameters are optimized. Firstly, the author describes the situation characteristics and intention patterns of Intuitionistic Fuzzy Sets, constructs a intuitionistic fuzzy rules-table and extracts logic relation and decision-making rules;accordingly, an algorithm of rules extraction is given, and the IFPN model of intention recognition is formed. In order to improve rational precision, the error back propagation (bp) algorithm is introduced to the parameters-optimized process of IFPN. Finally, the feasibility and validity of the proposed algorithms are presented by an instance.

关键词： Intuitionistic Fuzzy Sets Petri Nets Intuitionistic Fuzzy Petri Nets Rules Extraction bp algorithm

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Dielectric Loss Factor Forecasting Based on Artificial Neural Network

Dielectric Loss Factor Forecasting Based on Artificial Neura...

引用

2nd International Conference on Information and Computing Science

作者： Zhao, Jin-Xian Jin, Hong-Zhang Han, Hai-Wei Harbin Engn Univ Automat Coll Harbin Peoples R China HeiLongJiang Inst Sci & Technol Coll Elect & Informat Engn Harbin Peoples R China

ISBN: (纸本)9780769536347

Now the online monitor and diagnose of capacitive equipments still remains in a simple data processing level. The level of application of diagnosis and monitoring will be improved if advanced mathematical tools for analysis used in it. The paper introduces a new methods of using the bp neural network to predict the dielectric loss angle. Selecting inputs, outputs and parameters of the bp neural network makes it possible to prove the data in experiments. The results show that the method is capable of more accurate to prediction of the dielectric loss angle, and it has a guiding significance to prevent the insulation fault of High-voltage electrical equipment.

关键词： artificial Intelligence prediction of dielectric loss angle bp algorithm artificial neural network

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An MLP Neural Network for Time Delay Prediction in Networked Control Systems

An MLP Neural Network for Time Delay Prediction in Networked...

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20th Chinese Control and Decision Conference

作者： Sadeghzadeh, Nargess Afshar, Ahmad Menhaj, Mohammad Bagher Amirkabir Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781424417339

This paper considers networked control systems with time varying delays. The main idea is to apply a variable sampling period in order to compensate for the time delay. A feedforwrd multilayered neural network is first properly developed to estimate the time delay at each sampling period. Then, this predicted time delay is taken as the sampling period between the current and the next sampling steps. The simulation results show that the proposed approach makes the controller more robust for stabilizing the system by reducing remarkably the influence of the closed loop time delay.

关键词： Networked control systems (NCS) Neural network bp algorithm Multi Layer Perceptron (MLP)

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3-D Imaging Under Low-Rank Constraint With Radio Signals 24

3-D Imaging Under Low-Rank Constraint With Radio Signals

引用

IEEE 24th International Workshop on Multimedia Signal Processing (MMSP)

作者： He, Ying Zhang, Dongheng Sun, Qibin Chen, Yan Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu Peoples R China Univ Sci & Technol China Sch Cyber Sci & Technol Chengdu Peoples R China

ISBN: (数字)9781665471893

ISBN: (纸本)9781665471893

Compared with optical imaging, radio frequency (RF) imaging enables object imaging in an all-weather, privacy-preserving, and cost-effective way. However, the existing heuristic solutions such as back projection (bp) and range migration (RM), suffer from the sidelobe interference due to limited antenna aperture. In this paper, we propose a super-resolution 3-D imaging algorithm to enhance imaging performance. Mathematically, the reconstruction problem is an inverse problem that can be formulated as an optimization problem. The low-rank property of the object is exploited to regularize the imaging problem by nuclear norm minimization. We evaluate the proposed algorithm with both simulations and measurements. With a frequency band range from 2.7-4.1 GHz and a 16 x 6 multiple-input-multiple-output (MIMO) antenna array, simulation results show high imaging quality with a median boundary keypoint precision of 2 cm, and experimental results validate the feasibility of the proposed algorithm in a real-world environment.

关键词： 3-D imaging bp algorithm low-rank

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Research on Welding Line Defect Recognition of the In-service Pipeline Using X-ray Detecting

引用

International Conference on Mechanical Engineering and Intelligent Systems (ICMEIS 2012)

作者： Yuan Peixin Zhang Congcong Yuan Yue Northeast Univ Coll Mech & Automat Shenyang Peoples R China

ISBN: (纸本)9783037854693

This paper, based on the practical demands of in-service pipeline detection, a set of X-ray digital image welding line defect intelligent recognition system is established. Taking the welding line image detected by X-ray as objects of study, self-adaptive median filter method filters noise, high frequency enhancement filter method conducts the image edge sharpening enhancement;a edge detection method for X-ray digital image based on morphological gradient is proposed;a group of characteristics parameters that accurately reflects the essence characteristic of defects is selected, using a self-organizing, self-adaptive three-layer feed-forward neural network, applying bp algorithm, the bp neural network recognition system is established, thus, to achieve detecticn and recognition of weld defects.

关键词： X-ray Digital image processing Edge detecting Feature extraction Neural network bp algorithm Weld defects recognition

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Lossless data compression methods based on neural network

引用

International Conference on Communication Technology

作者： Yang, GW Li, ZX Tu, XY Qingdao Univ Teachers Coll Ctr Comp Qingdao Peoples R China

ISBN: (纸本)7563506861

No lossless data compression method based on neural network is found before. A lossless compression method based on bp network for the long character-string of 0 and 1 is given by establishing specific mapping Y and specific integer function and with the non-linear approximation capability of concrete three-layer bp network in this paper, and the compression & decompression algorithms of the lossless compression method are provided. Experiments show that the compression ratio of the lossless compression method is usually around 16/11 and the method can effectively compress the data which have been compressed by Huffman coding, arithmetric coding or dictionary coding.

关键词： data compression lossless data compression neural network bp algorithm

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A New Shelf Life Prediction Method for Farm Products based on an Agricultural IOT

A New Shelf Life Prediction Method for Farm Products based o...

引用

International Conference on Mechatronics and Semiconductor Materials (ICMSCM 2013)

作者： Wu, Mingze Weng, Yitong Liao, Zhicheng Fudan Univ Sch Comp Sci Shanghai 201203 Peoples R China

ISBN: (纸本)9783037859391

Shelf life prediction is an important problem in the field of food safety. This problem has been extensively studied in different research fields. In this paper, based on our agricultural JOT (Internet of Things) platform, we study this problem from the viewpoint of data mining. In our agricultural JOT platform, by setting various types of sensors, it is possible for us to collect information of a farm product during its whole life cycle such as planting, storage, processing, transportation and sale. Shelf life of a farm product is very difficult to determine since it will be affected by many factors during its life cycle, such as temperature, air/soil humidity etc. After integrate raw sensor data streams into batch id-based data streams, we adapt Back-Propagation method to the integrated sensor data streams to predict the shelf life of a farm product. Experiments are conducted on real data from our agricultural JOT platform and the experimental results demonstrate that the proposed method could provide a very good prediction for the shelf life of a farm product.

关键词： Shelf life prediction data integration data streams bp algorithm

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