检索结果-内蒙古大学图书馆

Rock Macro-Meso Parameter Calibration and Optimization Based on improved bp algorithm and Response Surface Method in PFC 3D

引用

ENERGIES 2022年第17期15卷 6290页

作者： Ren, Junqing Xiao, Ming Liu, Guoqing Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan 430072 Peoples R China China Inst Water Resources & Hydropower Res State Key Lab Simulat & Regulat Water Cycle River Beijing 100048 Peoples R China

In order to obtain the calibration law of rock macro and meso parameters under three-dimensional conditions, based on the parallel bond model, starting with the basic theory of PFC and the qualitative relationship between macro and meso parameters, an orthogonal experimental scheme is designed. An improved bp algorithm is proposed, which has a function with gradient factor, adaptive Nesterov momentum method, and adaptive learning rate for the lightweight analysis of meso parameters. The sensitivity between macro and meso parameters is quantified, and the key meso parameters are screened out. Based on the lightweight model, the correlation and influence mechanisms between macro and meso parameters are analyzed. It was found that the elastic modulus increases linearly with the increase in equivalent modulus. The parallel bond stiffness ratio can inhibit the growth of the elastic modulus, and the elastic modulus decreases greatly when the stiffness is relatively high. There is a linear relationship between Poisson's ratio and stiffness ratio, and the increase in the friction coefficient will cause the nonlinear decrease in it. The strength parameters have an incentive effect on the peak strength. When the tensile and shear strengths of the parallel bond are at a high level, the combination has the most significant effect on the increase in the peak strength. The internal friction angle mainly has a certain influence on the postpeak strength of the rock, because it has a control effect on the particle sliding on both sides of the shear zone when the sample is loaded after the peak. Based on the central composite experimental design and response surface method, a nonlinear model of macro-meso parameters described by multiple subresponse surfaces is obtained. Finally, the mathematical model of parameter calibration is established, and the optimal solution of rock meso parameters is obtained by using optimization techniques. Through the example verification, it was found t

关键词： PFC 3D improved bp algorithm adaption lightweight subresponse surfaces optimization parameter calibration

来源：评论

学校读者我要写书评

暂无评论

Fault Diagnosis and Performance Analysis of Steam Turbine Thermal System based on improved bp algorithm

Fault Diagnosis and Performance Analysis of Steam Turbine Th...

引用

作者： Bochao Xiang Southeast University

Steam turbine is an important tool in the growth of power generation work in power plants,and it is of great help to the growth of power generation work. The thermal power plant needs to constantly innovate the unit when generating electricity, and the steam turbine is an important part of the operation of the unit. Therefore, this paper proposes research on fault diagnosis and performance analysis of steam turbine thermal system based on improved bp algorithm. It mainly gives an overview of the steam turbine, and uses the improved bp algorithm scientifically, hoping to provide some help for the application of steam turbine.

关键词： improved bp algorithm Steam Turbine Thermal System Fault Diagnosis and Prediction

来源：评论

学校读者我要写书评

暂无评论

Research on Power Fault Data Fusion and Diagnosis Model Based on improved bp Network algorithm 6

Research on Power Fault Data Fusion and Diagnosis Model Base...

引用

6th International Symposium on Computer Science and Intelligent Control (ISCSIC)

作者： Wang, Li Zhang, XuYang Deng, Wen Zhejiang Elect Power Co Ltd Supply Chain Operat Ctr Zhejiang Procurement Co 378 Fengqi Rd Hangzhou 310005 Zhejiang Peoples R China State Grid Zhejiang Elect Power Co Ltd Shengzhou Power Supply Co 18 Huancheng North Rd Shengzhou 312400 Zhejiang Peoples R China State Grid Zhejiang Elect Power Co Ltd Mat Supply Sub Ctr Shengzhou Power Supply Co Shengzhou 312400 Zhejiang Peoples R China

ISBN: (纸本)9781665454889

The power transformer is the core of the whole power grid. By using the power transformer, the voltage value on the transmission line can be converted into electric energy, thus becoming a hub of the power grid. The current Back Propagation (bp) algorithm has a relatively high probability of local optimization problems, resulting in low fault accuracy. Based on this, the research combines the Particle Swarm Optimization (PSO) algorithm with the Particle Filter (PF) algorithm to improve its structure optimization, so as to propose the PFPSO algorithm. Through this algorithm, the bp network algorithm is improved, and the PFPSO-bp algorithm is obtained, At the same time, its effectiveness is verified. The experimental results show that the PFPSO-bp algorithm is higher than the other three algorithms both in training and in actual experiments, and the average accuracy rate is higher than 90%, the highest is 98%, showing a higher accuracy rate of fault identification, which has a stronger practical application significance in the actual power transformer fault identification.

关键词： improved bp algorithm Power transformer Data fusion Diagnostic model

来源：评论

学校读者我要写书评

暂无评论

Research and implementation of children's wear model based on improved bp algorithm 3

Research and implementation of children's wear model based o...

引用

3rd IEEE International Conference on Electronic Information Technology and Computer Engineering, EITCE 2019

作者： Liu, Ying Qiu, Defu Zheng, Lixin Huaqiao University Fujian Prov. Acad. Eng. Res. Ctr. in Indust. Intellectual Techniques and Syst. Coll. of Engineering Quanzhou China

ISBN: (纸本)9781728135847

In order to alleviate the extreme shortage, casual resignation of clothing designers, and the continuous improvement of the need for individual customization, we have come up with an improved bp algorithm which using children's easy-to-measure parts size data to forecast the size of complex parts required for different children's wear. We made and produced the predicted data to meet the actual requirements. This study compares the predicted results of the improved bp algorithm with those of the original bp algorithm and other algorithms, proving that the improved bp algorithm is with stronger stability, higher accuracy and faster convergence speed. The data required for pattern making is predicted by the improved bp algorithm, and the error between the forecast data and the actual data is as high as 99% within 0.3 cm, which is more advantageous than other algorithms in learning various clothing types and realizing monomer customization. © 2019 IEEE.

关键词： Children's wear Clothing designer improved bp algorithm Individual customization Stability

来源：评论

学校读者我要写书评

暂无评论

High-dimensional Data Classification Based on Principal Component Analysis Dimension Reduction and improved bp algorithm

High-dimensional Data Classification Based on Principal Comp...

引用

2018 International Conference on Communication, Network and Artificial Intelligence (CNAI 2018)

作者： Tai-shan YAN Yi-ting WEN Wen-bin LI School of Information Science and Engineering Hunan Institute of Science and Technology

In order to realize high-dimensional data classification accurately and reduce computation cost and dimension disaster,principal component analysis(PCA) is applied to reduce dimension of high-dimensional data firstly,and then bp neural network is applied to *** at the problem of low classification efficiency of traditional bp algorithm,an improved bp algorithm with two times adaptive adjust of training parameters(TA-bp algorithm) is *** two dynamic adjustment of learning parameters,the algorithm has higher learning *** MATLAB simulation experiment,the improved bp algorithm is applied to classify high-dimensional data after reducing *** experimental results show that the training speed and classification accuracy of high-dimensional data is improved greatly by this method.

关键词： High-dimensional data classification Principal component analysis Neural network improved bp algorithm

来源：评论

学校读者我要写书评

暂无评论

Discussion on the prediction of engineering cost based on improved bp neural network algorithm

引用

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019年第5期37卷 6091-6098页

作者： Wang, Bin Dai, Jing Chengdu Univ Technol Dept Construct Management Chengdu Sichuan Peoples R China

With the continuous improvement of the social and economic level, the investment in fixed assets in the whole society is increasing steadily, while the phenomenon of uncontrollable investment is becoming more and more serious. Therefore, it is very important to increase the investment estimate in the early stage of the project construction. Based on this, in this paper, by studying the bp neural network, a mathematical model of the prediction of engineering cost based on the improved bp neural network model was proposed;then, taking a 15-storey tall building in a residential district as a prediction object, by collecting and sorting out engineering cost data similar to the predicted object, the improved bp neural network model was estimated and trained;finally, the prediction of the engineering cost data for the project was carried out, and the actual results were compared with the estimation results of the traditional prediction model;thus, the speediness and accuracy of the proposed improved bp neural network model in the field of the prediction of engineering cost were verified.

关键词： bp neural network improved bp algorithm engineering cost prediction model

来源：评论

学校读者我要写书评

暂无评论

Simulated Annealing algorithm improved bp Learning algorithm

Simulated Annealing Algorithm Improved BP Learning Algorithm

引用

International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI)

作者： Lin, Yingjian Chen, Xiaoji Bohai Univ Teaching & Res Inst Coll Comp Jinzhou Peoples R China

ISBN: (纸本)9783038350125

bp learning algorithm has advantage of simple structure, easy to implement and so on, it has gained wide application in the malfunction diagnosis and pattern recognition etc.. For bp algorithm is easy to fall into local minima shortcoming cites simulated annealing algorithm. Firstly, study the basic idea of bp learning algorithm and its simple mathematical representation;Then, research simulated annealing algorithm theory and annealing processes;Finally, the study makes bp algorithm combine with simulated annealing algorithm to form a hybrid optimization algorithm of simulated annealing algorithm based on genetic and improved bp algorithm, and gives specific calculation steps. The results show that the content of this study give full play to their respective advantages of two algorithms, make best use of the advantages and bypass the disadvantages, whether in academic or in the application it has a very important significance.

关键词： bp neural network bp learning algorithm improved bp algorithm simulated annealing algorithm

来源：评论

学校读者我要写书评

暂无评论

A novel fault diagnosis scheme for a ballast system

引用

AUTOMATICA 2023年 148卷

作者： Qu, Huifang Zhang, Weidong Zhang, Guoqing Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Hainan Univ Sch Informat & Commun Engn Haikou 570228 Hainan Peoples R China Dalian Maritime Univ Nav Coll Dalian 116026 Peoples R China

The Back Propagation (bp) neural network model is one of the neural network models suitable for model recognition and classification. However, a single bp network model cannot fully tap the feature information hiding in the data and is vulnerable to the uncertainty associated with system parameter changes and also suffers from the effects of long diagnosis times, inaccurate and undesired diagnosis results in applying a large amount of high-dimensional feature data. In addition, the standard bp algorithm has limitations in pattern recognition and classification. For example, it adopts the quadratic cost function to train the neural network, which can lead to low convergence accuracy, low convergence rate, and so on. Compared with the quadratic cost function, the cross-entropy cost function can effectively improve the convergence accuracy and the convergence rate of the neural network. The Dempster-Shafer (D-S) evidence theory is a powerful tool for handling incomplete, imprecise, and uncertain information and merging it when it derives from multiple bp networks. In order to overcome the drawbacks of a single bp network, it is necessary to divide the high-dimensional feature data into several different categories of low-dimensional feature data and to input the same dimensional feature data into the same bp network model, as well as to design the information fusion algorithms based on D-S evidence theory and multiple improved bp networks with the cross-entropy cost function. For this reason, this paper proposes a novel information fusion diagnosis approach based on D-S evidence theory and multiple improved bp networks for fault diagnosis and classification of multiple devices in a ballast system subjected to extreme environmental conditions. The proposed diagnosis approach utilizes multiple neural networks to carry out local fault diagnosis, adopts the D-S evidence theory to fuse the results of local diagnosis and derive the decision results, and introduces an improve

关键词： Ballast system Fault diagnosis of multiple devices Multiple neural networks improved bp algorithm D-S evidence theory

来源：评论

学校读者我要写书评

暂无评论

Performance Evaluation of a New bp algorithm for a Modified Artificial Neural Network

引用

NEURAL PROCESSING LETTERS 2020年第2期51卷 1869-1889页

作者： Panda, Sashmita Panda, Ganapati Indian Inst Technol Kharagpur GS Sanayal Sch Telecommun Kharagpur 721302 W Bengal India CV Raman Engn Coll Elect & Commun Engn Bhubaneswar Odisha India

In a conventional artificial neural model, the nonlinear activation function (AF) follows the weight sum operation. In this paper, the AF is placed before the connecting weights of each artificial neuron and hence modified artificial neural network (MANN) is proposed and the corresponding backpropagation (bp) learning algorithm is derived. Further, the slope of AF which is conventionally fixed during the training phase is adjusted for achieving better and faster training of the multi-layer artificial neural network (MANN). In this case, also both the weights and slope update algorithms are derived. To assess and compare the performance of these two ANN models, standard applications such as classification, nonlinear system identification (direct modeling), nonlinear channel equalization (inverse modeling) are implemented through simulation and compared with that obtained by conventional bp based MANN. The simulation results demonstrate that the adaptive slope based MANN outperforms the fixed slope as well as conventional MANN in terms of three different performance measures such as the number of iterations to converge, mean of the square of residual error and mean absolute deviation.

关键词： Modified MANN Adaptive activation function improved bp algorithm New ANN structure

来源：评论

学校读者我要写书评

暂无评论

Stability Determination Method of Flame Combustion Based on improved bp Model with Hierarchical Rate

Stability Determination Method of Flame Combustion Based on ...

引用

International Conference on Life System Modeling and Simulation (LSMS) / International Conference on Intelligent Computing for Sustainable Energy and Environment (ICSEE)

作者： Chen, Rongbao Cao, Zipei Xiao, Benxian Hefei Univ Technol Hefei 230000 Anhui Peoples R China

ISBN: (纸本)9789811063732;9789811063725

For the purpose of automatic monitoring of the boiler combustion stability and quantifying the degree of combustion stability, a determination model for the combustion stability based on bp neural network is proposed. This model, according to the digital image processing technology, captures flame combustion state images, then extracts combustion states. Aimed at shortcomings of bp algorithm - anti-jamming ability, slow learning rate, easy to fall into local minimum, etc., this paper proposes a bp algorithm based on hierarchical dynamic adjustment of different learning rates. The samples are divided into training samples and test samples for training and testing the established model. Experience has shown that the improved model not only has better fault-tolerance and mapping ability but also improves recognition rates and computing speed, which can meet the real-time requirement of stability determination.

关键词： Flame image processing improved bp algorithm Hierarchical dynamic adjustment of different learning rates Combustion stability

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：