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Application of bp neural network algorithm in Sustainable Development of Highway Construction Projects

Physics Procedia 2012年 25卷 1212-1217页

作者： Mingshun Li Wencui Chen Department of Project Management Changsha University of Science & Technology Changsha China

Highway construction project does not exist for its own, but also to meet the needs of the society. Its development strategy should be based on the overall goal of the society, not just for its own. Therefore, the sustainable evaluation of the highway construction should be considered from the two parts of sustainability of social needs and economic development. In this paper, using the bp neural network algorithm, through the analysis of sustainable development of the following four areas in road construction: economics, environmental resources, operations, management systems and policy, the author studies the sustainable development evaluation of highway construction project.

关键词： bp neural network algorithm Highway construction projects Sustainable Development Evaluation

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Inventory Prediction Research Based on the Improved bp neural network algorithm

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INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING 2016年第9期9卷 307-316页

作者： Pan, Fu-bin Xiamen Univ Technol Sch Econ & Management Xiamen 361024 Peoples R China

Since the idea of the supply chain management is proposed, many enterprises have attached great importance to the supply chain management and pay a lot of manpower and resources to study. It is also the focus to study the inventory in the field of the supply chain. Quantity of the inventory is not only related to the profit of the enterprises, but also related to the survival of the entire supply chain. Predicting the inventory can improve the ability of enterprises to prevent risk, increase the profits and reduce the losses. In order to predict better on inventory, we propose an improved bp neural network algorithm. In the algorithm, we use the improved GSA algorithm to optimize the parameters of bp neural network algorithm and improve the bp neural network algorithm aiming at its deficiency. The experimental results show that this method has good prediction effect.

关键词： bp neural network algorithm inventory prediction

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An Improved bp neural network algorithm for Evaluating Food Traceability System Performance

An Improved BP Neural Network Algorithm for Evaluating Food ...

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2015 International Conference on Materials Engineering and Information Technology Applications(MEITA 2015)

作者： Weiya Guo School of Economics and Management Beijing Jiaotong University

ISBN: (纸本)9781510812055

bp neural network algorithm has powerful calculation ability, but the algorithm has some shortages such as low convergence which limits its application, so improving bp algorithm has become a matter of concern in the fields related. Based on analyzing improvement methods wildly used today, the paper presents a new bp neural network algorithm and applies it to evaluate food traceability system performance. Firstly, the paper improves the bp algorithm through changing learning rate, trigonometric function to simplify the original calculation structure;secondly, the calculation step of the improved bp algorithm is redesigned to speed up its convergence. Finally, the paper conducts the theoretical analysis of the calculation performance of the improved algorithm and applies it to evaluate food traceability system performance, the theoretical analysis and experimental evaluation results show that the improved algorithm can improve evaluation accuracy and algorithm calculation efficiency and can be used for evaluating food traceability system performance practically.

关键词： bp neural network algorithm Performance evaluation food traceability system trigonometric function

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Application Analysis of Forecasting Model Based on bp neural network algorithm 22

Application Analysis of Forecasting Model Based on BP Neural...

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Proceedings of the 2022 5th International Conference on E-Business, Information Management and Computer Science

作者： Zhaoyi Xu Wuhan Business University China

ISBN: (纸本)9781450397827

With the development of big data technology, the hotel industry has also entered the era of big data. The imbalance between supply and demand in the hotel industry will directly affect the hotel's operating conditions. This paper uses the bp neural network algorithm to predict the hotel's demand analysis and reservation rate, and establishes a prediction model based on the bp neural network algorithm through the two variables of reservation time and consumption time. Investors can make better decisions, thereby increasing hotel revenue.

关键词： bp neural network algorithm

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Based on the bp neural network algorithm of Highway Engineering Cost Data Analysis

Based on the BP Neural Network Algorithm of Highway Engineer...

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国际道路联盟中国研讨会暨中国公路学会2015年学术年会

作者： WANG Hong-chuan LANG Zhi-hai Liaoning Transportation Research Institute Shenyang 110015China

Engineering information is a very precious information resources, and it is of great significance to predict the engineering *** this paper, using bp neural network algorithm through to complex, decentralized completed engineering data collecting and analyzing statistics and draw all kinds of traffic engineering of the quantity of consumption, and the market price of the overall *** can provide the basis for the investment estimation, calculation of engineering cost, engineering quotation and contract adjustment, and provide the main basis for the new engineering project decision, construction and design.

关键词： bp neural network algorithm highway engineering cost information system data analysis

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Application of bp neural network algorithm in Sustainable Development of Highway Construction Projects

Application of BP Neural Network Algorithm in Sustainable De...

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2012 International Conference on Solid State Devices and Materials Science(SSDMS 2012)

作者： Mingshun Li Wencui Chen Department of Project Management Changsha University of Science & Technology

关键词： bp neural network algorithm Highway construction projects Sustainable Development Evaluation

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Based on the bp neural network algorithm of Highway Engineering Cost Data Analysis

Based on the BP Neural Network Algorithm of Highway Engineer...

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The 6th International Symposium on Project Management(ISPM2018)

作者： Hongchuan WANG Liping WU LANG Zhi hai Liaoning Transportation Information Technology Company Limited Shenyang Vocational and Technical College

Engineering information is a very precious information resources, and it is of great significance to predict the engineering cost. In this paper, using bp neural network algorithm through to complex, decentralized completed engineering data collecting and analyzing statistics and draw all kinds of traffic engineering of the quantity of consumption, and the market price of the overall trend. This can provide the basis for the investment estimation, calculation of engineering cost, engineering quotation and contract adjustment, and provide the main basis for the new engineering project decision, construction and design.

关键词： bp neural network algorithm highway engineering cost information system data analysis

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Research on multi-sensor information fusion algorithm of fan detection robot based on improved bp neural network 6

Research on multi-sensor information fusion algorithm of fan...

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6th IEEE Advanced Information Technology, Electronic and Automation Control Conference (IEEE IAEAC)

作者： Jin, Lele Kou, Zhiwei Liu, Liqiang Qi, Yongsheng Cui, Xiaoming Inner Mongolia Univ Technol Coll Elect Power Hohhot 010051 Peoples R China Inner Mongolia Key Lab Elect Control Hohhot 010051 Peoples R China

ISBN: (数字)9781665458641

ISBN: (纸本)9781665458641

The functional structure of the fan operating system is complex, and the condition detection of a single signal source will inevitably result in errors and false alarms. The diagnostic method of information fusion can make full use of more information. Thus the problem can be avoided: the Fan Detection robot is equipped with multiple sensors, and these sensors are fused by a reasonable information fusion algorithm. The fused sensor information can obtain a more accurate statement of the fan. The purpose of saving cost and making the fan run stably aims to reduce man-made overhauls. bp neural network has the capability of non-linear mapping, self-learning and self-adaptation, and the fusion performance is good, the application of a wide range. Therefore, bp neural network algorithm can be chosen to carry out sensor information fusion.

关键词： multi-sensor information fusion bp neural network algorithm fan

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Multi-parameter modeling and analysis of ground motion amplification in the Quaternary sedimentary basin of the Beijing-Tianjin-Hebei region

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Earthquake Science 2025年第2期38卷 136-151页

作者： Hong Zhou Institute of Geophysics China Earthquake AdministrationBeijing 100081China

Basin effect was first described following the analysis of seismic ground motion associated with the 1985 MW8.1 earthquake in *** affect the propagation of seismic waves through various mechanisms,and several unique phenomena,such as the basin edge effect,basin focusing effect,and basin-induced secondary waves,have been *** and quantitatively predicting these phenomena are crucial for earthquake disaster *** pioneering studies in this field have proposed a quantitative relationship between the basin effect on ground motion and basin ***,basin effect phenomena predicted using a model based only on basin depth exhibit large deviations from actual distributions,implying the severe shortcomings of single-parameter basin effect *** sediments are thick and widely distributed in the Beijing-Tianjin-Hebei *** seismic media inside and outside of this basin have significantly different physical properties,and the basin bottom forms an interface with strong seismic *** this study,we established a three-dimensional structure model of the Quaternary sedimentary basin based on the velocity structure model of the North China Craton and used it to simulate the ground motion under a strong earthquake following the spectral element method,obtaining the spatial distribution characteristics of the ground motion amplification ratio throughout the *** back-propagation(bp)neural network algorithm was then introduced to establish a multi-parameter mathematical model for predicting ground motion amplification ratios,with the seismic source location,physical property ratio of the media inside and outside the basin,seismic wave frequency,and basin shape as the input *** then examined the main factors influencing the amplification of seismic ground motion in basins based on the prediction results,and concluded that the main factors influencing the basin effect are basin shape and differenc

关键词： three-dimensional basin effect ground motion modeling bp neural network algorithm spectral element method

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Multi-parameter identification of earthquake simulation shaking table based on bp neural network

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FRONTIERS IN PHYSICS 2024年 12卷

作者： Gao, Chunhua Li, Cun Qin, Mengyuan Yang, Yanping Yuan, Zihan Xinyang Normal Univ Coll Architecture & Civil Engn Xinyang Henan Peoples R China

Since the model parameters of the shaking table exist in a non-linear form, this leads to distortion of the reproduced waveforms and can even lead to bias in the ground vibration test results. Therefore, the selection of the controller is particularly critical. Multi-variable (MVC) controllers are often used in shaking table control, to improve the control effect of MVC controllers. In this paper, a multi-parametric (bp-MVC) controller based on bp neural network is proposed. The bp neural network is applied to the multi-parameter (MVC) controller to identify the shaking table model, adjust the parameters in real-time, accelerate the convergence speed, and reduce the system error. The simulation results show that the correlation coefficient (CC) of the bp-MVC controller is greater than 0.985, and the root-mean-square error (RMSE) and mean absolute error (MAE) are less than 0.04 and 0.25, respectively, in a nonlinear, time-varying hydraulic system. This suggests that the bp-MVC controller has a better control performance and parameter adaptivity, which can provide a reference for the subsequent ground vibration tests.

关键词： shaking table three-parameter control multi-parameter control bp neural network algorithm parameter identification

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