bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis and prediction of traffic flow based on Wavelet-BP neural network
Authors: Wang Zhuo , Zhao Lei
Published: November 2019

Through on-the-spot investigation, collected data of traffic flow from a certain section of 3rd Ring Road in Beijing, the investigation results were analyzed from the perspective of time and space, macro rules of traffic flow and the influence of incidental traffic events on roads was summarized. The MATLAB software was used to decompose traffic flow data by three-layer wavelet, and the variation characteristics of the detail coefficients were obtained by decomposing the parameters of traffic flow by wavelet. Analyzed the abrupt change phenomenon of the traffic flow parameters, so as to judge whether some traffic incident occurred and which kind of it. With the level of road traffic service, the same moment which anomalous traffic flow data produced theoretically and traffic service levels were greater than or equal to 4 levels was chosen, so as to verify whether the anomalous time point analyzed by wavelet-analysis were precise. Used MATLAB software to establish the prediction model by a neural network, and determined the various parameters, functions, training and testing samples. Coefficients of different parameters in the BP neural network were used to predict the changes of traffic flow in the future. Compared the predicted data with the actually observed traffic flow, the starting time of traffic incident and the anomalous mutation starting point of three traffic flow parameters was consistent. This research had great significance to the future intelligent traffic decision-making.
A multi-Cross Matching Network for Chinese Named Entity Linking in Short Text
Authors: Ouyang Xiaoye , Chen Shudong , Zhao Hua , Hao Yuexing , Li Wei , Li Shaojie , Wang Rong , Liang Xiaohu
Published: November 2019

Named entity linking(NEL) for Chinese short text is regard as a ranking task. Current research on NEL is mostly about long text and rich language, which may unfit Chinese short text situation. We propose a multi-cross matching network(CMN) to solve these problems. CMN first matches a candidate and the mention with the text in three different degree, and extracts important matching information through a couple of convolution and pooling layers. Then sequence vectors are accumulated through a Gated Recurrent Unit(GRU) which distill relationships among words in texts. Finally we use dynamic average algorithm to calculate the mention-entity similarity. Experimental results demonstrate that CMN exhibits the outstanding performance on several Chinese datasets for the Chinese short text entity linking problem.
Predicting sales by online searching data keywords based on text mining: Evidence from the Chinese automobile market
Authors: Li Yi , Yu Liangru , Wen Rui
Published: November 2019

Online searching data reflects consumers’ real footprints in information collection and purchase decision-making processes, which is greatly valued in understanding their needs. This paper which is at the background of China’s automobile market, studies the relationship between online searching data and automobile sales through approaches that differ from existing research to extract keywords. First the online searching data keywords are determined, primarily by using text-mining technology to extract them, and specifically: i) Jieba was used to tokenize crawled automotive forum posts’ text into segmented words; ii) All word-segmented Chinese corpus were segmented into word vector space by Word2vec model; and iii) Similar keywords were discovered by calculating the word vector’s similarity indexes. A fixed effect model was then built based on 108 months of long panel data. Finally, combing with panel vector autoregressive model (PVAR), we used rolling window to predict Chinese automobile sales from January to December 2015.The empirical results demonstrate that: a long equilibrium exists between online searching data and automobile sales; our regression model can explain 76% of the variance. The holdout analysis suggests that online searching data can be of substantial use in forecasting Chinese automobile sales.
An Action Recognition network for specific target based on rMC and RPN
Authors: Li Mingjie , Feng Youqian , Yin Zhonghai , Zhou Cheng , Dong Fanghao , Lin Yuan , Dong Yuhao
Published: November 2019

The traditional methods of action recognition are not specific for the operator, thus results are easy to be disturbed when other actions are operated in videos. The network based on mixed convolutional resnet and RPN is proposed in this paper. The rMC is tested in the data set of UCF-101 to compare with the method of R3D. The result shows that its correct rate reaches 71.07%. Meanwhile, the action recognition network is tested in our gesture and body posture data sets for specific target. The simulation achieves a good performance in which the running speed reaches 200 FPS. Finally, our model is improved by introducing the regression block and performs better, which shows the great potential of this model.
Slope reliability analysis based on PSO-RBF neural network
Authors: He Yongbo , Li Qing , Zhang Ning , Li Chuangjiang
Published: November 2019

In this paper, a reliability analysis method based on ABAQUS and particle swarm optimization radial basis function neural network is proposed. The strength reduction method based on ABAQUS is used to calculate the safety factor corresponding to the selected random variable. The data fitting function of the radial basis function neural network is used to establish the model and map the relationship between the safety factor and the random variable to construct the response surface function. A large number of random samples generated by Monte Carlo are substituted into the function to obtain the corresponding safety coefficient,in order to calculate the instability probability and reliability index of the slope.
Knowledge Acquisition for the Air Combat Based on GWO
Authors: Huang Changqiang , Wei Zhenglei , Yang Yuanzhi , Ku Shuo , Zhang Hongpeng
Published: November 2019

The problem of knowledge acquisition for the air combat of fighter is studied, and a way to acquire knowledge from massive flight parameters data is put forward. First, expert system of air combat is built; then for flight maneuver knowledge extraction, a method based on grey wolf optimization (GWO) is proposed, in order to obtain simple and effective knowledge, and design a new evaluation function of the GWO algorithm. Finally, the simulation results of horizontal right turn and single plane loop verify that the knowledge extraction method of flight maneuver is effective and feasible.
Rehabilitation system for children with cerebral palsy based on body vector analysis and GMFM-66 standard
Authors: Wang Ziqi , Ding Zanhan
Published: November 2019

This paper mainly proposes a rehabilitation training system that uses motion recognition technology to help children with cerebral palsy complete the evaluation of gross motor functions. This article makes a comprehensive introduction to this product with regard to the system functional architecture, application technology principles and its application scope.
OGRU: An Optimized Gated Recurrent Unit Neural Network
Authors: Wang Xin , Xu Jiabing , Shi Wei , Liu Jiarui
Published: November 2019

Due to the structural problem, the traditional neural network models are prone to problems such as gradient explosion and over-fitting, while the deep GRU neural network model has low update efficiency and poor information processing capability among multiple hidden layers. Based on this, this paper proposes an optimized gated recurrent unit(OGRU) neural network.The OGRU neural network model proposed in this paper improves information processing capability and learning efficiency by optimizing the unit structure and learning mechanism of GRU, and avoids the update gate being interfered by the current forgetting information. The experiment uses Tensorflow framework to establish prediction models for LSTM neural network, GRU neural network and OGRU neural network respectively, and compare the prediction accuracy. The results show that the OGRU model has the highest learning efficiency and better prediction accuracy.
An early warning method for structural safety based on EEG
Authors: Li Jailong , Zheng Wei , Zhao Qing
Published: November 2019

It is an important part in the field of structural safety detection to warn the monitored results accordingly. Studying the effect of visual environment on EEG can provide theoretical evidence for structural security warning. Most of the existing studies on the effect of visual environment on EEG are based on a single factor of color or frequency, and seldom involve the effect of shape on EEG. In order to solve these problems, this paper carried out an experiment to explore the effect of color, frequency and shape on EEG. The EEG signal was pretreated by EMD-HHT algorithm. It was found that the effects of visual signals on brain waves were concentrated in the first 20 seconds. By the observed β power in the first 20 seconds we found that when the color is red or yellow, the frequency is 10 Hz, the shape is circular or triangular, the β power will increase significantly, it’s the electroencephalogram most relevant to attention.
Opportunities and Challenges of Unmanned Aircraft Vehicles Networking in Confrontation Environment: Collaborative and Reliable Communication with Intelligence
Authors: Wang Guisheng , Huang Guoce , Ren Qinghua , Zhang Wenhe , Wang Ye , Gao Weiting
Published: November 2019

With a wide range of applications of artificial intelligence (AI) technology in communication networks, collaborative and reliable communication with intelligence has enormous potential to improve the performance of unmanned aerial vehicles (UAVs) in complex confrontation environment. Two typical application scenarios of UAVs, assisted communication and swarm communication, are introduced after discussions of characteristics. In details, the preliminary network architecture is given to improve the adaptability in different scenarios. Then, combined with the characteristics of the UAVs and the anti-UAV countermeasures, the opportunities and challenges in UAVs cooperative communication are analyzed. Finally, highlighting the key design considerations of the AI technology gives possible solutions correspondingly, which deserves to be exploited for the cooperative and reliable UAVs’ communication.
Disease Regions Recognition on Mural Hyperspectral Images Combined by MNF and BP Neural Network
Authors: Lin Yuxian , Xu Chenqi , Lyu Shuqiang
Published: November 2019

Many murals are suffering from some serious diseases such as deep loss, mud besmirch and sootiness nowadays. And it is necessary to identify these regions before conservation and restoration. The purpose of this study was to explore the disease region recognition method using hyperspectral images. A method combined Minimum Noise Fraction(MNF) rotation and Back Propagation (BP) neural network was developed to classify the mural images to several kinds of damaged regions and normal parts. The MNF was adopted to select feature bands while the BP network was constructed and trained to classify the mural images. Some mural images collected in Beijing were utilized for the experiment. And according to the error matrix and sampling analysis, the overall accuracy of this method was 86.6% and the Kappa coefficient was 0.864. And they were higher than the maximum likelihood classification method.
The Selection and Optimization of a Negative comment Identification Method
Authors: Luo Haibo , Dong Jianhu , Luo Xianlu
Published: November 2019

This paper introduces the research background and significance of negative comments, and analyzes the present situation and development trend of negative comments identification at home and abroad. Several popular classification algorithms of naive Bayes, support vector machines and neural network are introduced. The word bag model, TF-IDF model and Word2Vec/Doc2Vec model feature model are also introduced. The data of feature extraction and classification algorithm in IMDB movie review website are simulated, and the results are compared and analyzed, and an optimal combination of feature extraction and classification algorithm is obtained.
Research on Users’ Emotion in the Later Period of the Inversion of public opinion--Taking the case of Wang Fengya as an example
Authors: Zhang Yuan , Zheng Yingli
Published: November 2019

Online public opinion reversal events occur frequently. The emotional characteristics and reasons of users in the later period of online public opinion reversal events are still not clear. Therefore, it is necessary to analyze the user emotions in the later period of the online public opinion reversal event, so as to help strengthen the supervision of public opinions and avoid the negative impact on the society in the process of public opinion reversal as far as possible. In this paper, Wang Fengya’s public opinion reversal event was taken as an example. Python crawler was used to capture the user comment data of the later period of this network public opinion reversal event. Combined with BosonNLP emotion dictionary, HowNet emotion dictionary and the characteristics of data capture, a custom emotion dictionary was constructed to realize the emotion analysis based on the custom emotion dictionary. In the later period of the reversal of public opinion on the Internet, user emotion has the characteristics of scattered user group structure, extreme and irrational emotion, and a high proportion of negative emotional comments. This is related to China’s economic development, the composition of Weibo network users and the diversity of media communication means.
The Business Logistics Security Research on Web Application
Authors: Tan Kangyu , Xie Yongjie
Published: November 2019

The rich functions of web applications have played an important role in the rapid development of the Internet. Different web applications have different functions. Compared with traditional XSS vulnerabilities, SQL injection vulnerabilities, and command execution vulnerabilities, the security issues involved in different server functions of Web applications vary widely, which leads to the absence of general solutions for specific security vulnerabilities in business logic process. After analyzing the security of the business logic process, it can be found that when the various security points of the business logic process are used by the attacker, and the behaviour of the attacker does not have any obvious difference from the normal user, which leads to the inability to achieve effective protection by directly using various types of scripts. Therefore, it is of practical significance to research a penetration detection idea of a logical vulnerability.
Research and Construction of Word Vector Extension Structure Based on Context
Authors: Wang Yiying , Ning Hongyun
Published: November 2019

The CBOW (Continuous Bag-of-Words) model is a three-layer forward neural network that predicts the central word vector by the fixed-size window information. In fact, context has a very important role in understanding the meaning of words. However, the context information of the fixed window size is partial and it is not enough to represent the whole context. Due to the polysemy of Chinese words, the same word may have different semantics in different contexts, while the traditional CBOW method ignores the polysemy of words. Therefore, this paper proposes a context-based word vector extension structure for the above problems. The main contents are as follows: (1) Introducing the concept of context vector. The entire sentence in which the target word is located is represented by a vector. (2) Constructing the polysemy storage method of words, adding a contextual list to each word vector, so that the multiple semantics of the words can be effectively distinguished. (3) Based on the word vector extension structure of this paper, a new character vector generation model is proposed, and the effect of the new model and the traditional CBOW model in the news headline similarity sorting task is compared. The experimental results show that the new character vector generation model based on the extension structure of the word vector obtains better result.
The Cultural Exchange between China and Korea under the Network Media Environment
Authors: Hong Sun
Published: November 2019

With the popularization of network media, it has changed the current structure of cultural communication, and also made cross-border cultural exchanges enter the digital era. Cultural soft power has become an important indicator of the development of countries in the world. South Korea is one of the countries representing the strategy of cultural soft power in the world. In the 21st century centered on globalization and informationization, “Korean Current” has brought great development to Korea. At the same time, it has brought great influence to China. This paper takes the cultural exchange between China and Korea as the research object. Firstly, from the perspective of network communication, this paper analyses the cultural trade between China and Korea under the network media environment. Then this paper analyses the influence and function of network media on cross-border cultural exchanges between China and Korea. Finally, some suggestions are put forward.
Identity-Based Parallel Key-Insulated Proxy Signature Without Random Oracles
Authors: JianhongChen
Published: November 2019

Exposure of private keys is the dangerous attack in the public key cryptosystems. We put forward an identity-based parallel key-insulated proxy signature (IBPKIPS) scheme to deal with the problem of key exposure in the identity-based proxy signature system. Our IBPKIPS scheme is secure without random oracles. In the IBPKIPS scheme, we use two different helper keys to renew the temporary private keys. Our IBPKIPS scheme is securer and more flexible than the identity-based proxy signature scheme.
Design and Implementation of Variable Precision Algorithm for Transcendental Functions
Authors: Jiangwei Hao , Jinchen Xu , Shaozhong Guo , Yuanyuan Xia , Dan Liu
Published: November 2019

Mathematical function is an essential part of numerical program, and it is also the key factor that affects the precision and performance of a program. In the design of mathematical functions, in order to satisfy most application scenarios, it is necessary to correctly round and cover the calculated interval as much as possible. But in certain applications, correct rounding and full coverage of definition domain may not be required. Therefore, mathematical functions can be customized according to application requirements to avoid precision waste as well as improve performance. However, manually implementing mathematical functions is a time-consuming and error-prone task. Tools like Metalibm is designed to automatically generate mathematical function code, which is difficult to take advantage of all the mathematical properties of a function and results in the generated code performing slowly than the corresponding mathematical library function. A method of generating variable precision code based on mathematical properties is proposed for the transcendental function in this work. Experiments showed the performance of the proposed method is comparable to Glibc mathematical function.
Solve Constrained Minimum Spanning Tree By cross-entropy (CE) method
Authors: Li Jing , Guo Zaifu
Published: November 2019

Given an undirected graph and nonnegative numbers as weights for each edge, we consider the problem of finding a spanning tree that has lowest total cost with respect to cost weight and has constrained budget with respect to constrains weight [1]. Different from the traditional Lagrangean relaxation method, we proposed a new randomized method for solving the constrained spanning tree problem in this paper. For this newly proposed method every solution found is in the original problem’s feasible region, there is no need to do the hard work to close the gap between the Lagrangean relaxation and the original problem. And the proposed algorithm is very easy to parallelize, can take full advantage of multi-core processors to improve problem solving efficiency. For most optimization algorithms, properly selecting the super parameters have big impact on the algorithm’s practical performance. Through computer numerical simulation, we can see that our algorithm is robust to super parameters.
Wave Superposition Method Applied to Calculate the Radiation Sound Power from a Thin Plate
Authors: Zhu Yong-yong , Peng Jing-hui , Liu Bao
Published: November 2019

A method for calculating the radiation sound power from a thin plate is described using the principle of wave superposition. After getting the velocity of the surface, the method can be used to calculate the strength of radiation source, which can be used to compute the sound power of the corresponding plate without computing the surface pressure. The paper gives an example of a rectangular baffled plate with simply supported boundary. And through comparing the computation result with the analytic result, it is shown that the mention method can reduce the unit and node number while it can ensure high precision without calculating the radiation resistance. Thus the method reduce computing time and improve the efficiency.
The Application of The Decision Tree Algorithm Based on K-means in Employee Turnover Prediction
Authors: Yunmeng Zhang , Chengyi Zhang
Published: November 2019

The employee’s voluntary turnover is one of the most difficult problems for the company. The research uses a human resource data as an example. K-means is used to classify employees, and then each type of the decision tree algorithm is used to conduct prediction and analysis of turnover. After research and analysis according to the experimental results, the two types of employees with high turnover rate are analyzed, and the management is provided with measures to prevent the occurrence of some acts of turnover.
Duality for higher-order (F,η)-invexity multiobjective fractional programming
Authors: Gao Xiaoyan , Yue Dongping , Wang Xuefeng
Published: November 2019

In this paper, we define a new class of generalized higher-order (F,η)-invexity functions, higher-order (F,η)-pseudo invexity functions and higher-order (F,η)-quasi invexity functions. Under the new generalized invexity, the Wolfe dual model for a class of multiobjective fractional programming problem is established, and several weak duality, strong duality and strict converse duality theorems are obtained and proved.
The empirical research of ARMA-GARCH models based on high frequency data
Authors: Guo Youming , Li Tingting
Published: November 2019

Based on high frequency data (5 minutes) and low frequency data (day), this paper models and analyses the Shanghai Stock Exchange Index (SH1A0001). Through the stationarity test and the ARCH effect test, the ARMA (1,1) – GARCH (1,1) model is established. Under the assumption of the error term obeys the Laplace distribution, the estimation is obtained. By the result of forward prediction, it is found that the result of model prediction in high frequency data is better than those in low frequency data.
Establishment and Solution of Mathematical Model for Unconventional Cracks in Multi-stage Fracturing of Horizontal Wells
Authors: Chen Zhanjun , Liu Xuefen , Cao Feng
Published: November 2019

Cracks tend to be asymmetrical during complex fracture processes. In this paper, the mathematical model of well test interpretation of vertical cracks under finite diversion conditions is established by the basic theory of point source function. The interpretation model of multi-stage fracturing unconventional fracture horizontal well test well is obtained by using the principle of pressure drop superposition. The semi-analytical solution of the model is obtained by integral transformation. By numerically discretizing the cracks, combined with the semi-analytical solution and the Duhamei principle, according to the Stehfest numerical inversion method, the bottom hole pressure and pressure derivative curves of the multi-stage fracturing unconventional crack horizontal wells are drawn.
Parameter Estimation of Multi-Frequency Hopping Signals Based on FastICA Algorithm
Authors: Zhang Shengkui , Yao Zhicheng , Fan Zhiliang , Wu Zhihui
Published: November 2019

In order to solve the parameter estimation problem while multi-frequency hopping signal aliasing, this paper proposes a multi-frequency hopping parameter estimation algorithm based on FastICA (Fast Independent Component Analysis). Firstly, the FastICA algorithm is used to blindly separate the observed signals, and then using the short-time Fourier transform to extract the time-frequency ridges from separated signals. After that, wavelet transform is used to detect its singularities, and to estimate the period of each frequency-hopping signal. The simulation results show that the proposed algorithm can blindly separate multiple hopping signals and estimate their hopping periods, with fast convergence speed and strong robustness.
CPHD Tracking Algorithm Based on BPF for Multiple Group Targets
Authors: Guo Yiduo , Gong Jian , Gao Qian
Published: November 2019

Aim to solve the tracking of multiple group targets in strong clutter environment, a rectangular box is used to deal with extension state of group targets. Combining the box particle filter algorithm and the cardinalized probability hypothesis density (CPHD) algorithm, a CPHD algorithm for multiple group targets tracking based on box particle filter (BPF), which is called BPF-CPHD, is proposed in this paper. Compared with the existed algorithm of multiple group targets tracking, the proposed algorithm can improve the tracking accuracy and efficiency greatly. Simulation results confirm the effectiveness of the BPF-CPHD.
Research on Routing Algorithm in Intelligent Meter Reading
Authors: Fangyu Xu , Wang Heng
Published: November 2019

The introduction to broadband micro-power wireless technology in the national network intelligent meter reading system can increase the bandwidth, improve the meter reading performance, and make up for the narrow bandwidth and low speed in narrow-band micro-power wireless and PLC technology. In the smart meter reading network, the generation and maintenance of routes are the key. This paper improves the AODVjr algorithm and improves it from full-network broadcasting to semi-directional directed broadcasting, calculating channel quality based on weight, making it suitable for real-time routing repair in broadband micro-power wireless intelligent meter reading. The improved algorithm minimizes route repair time and routing overhead while ensuring communication success rate. The simulation results show that with the increase of the number of nodes, the semi-directional broadcast has much better performance in routing request packet transmission success rate, average hop count, communication success rate, and route repair delay than the whole network broadcast.
A Novel Method of Radar Antenna Scan Pattern Recognition Using Visibility Graph
Authors: Wan Tao , Fu Xinying , Jiang Kaili , Tang Yanli , Xiong Ying , Tang Bin
Published: November 2019

Radar antenna scan has a great influence on reconnaissance targets, interference decision-making, and electronic support measures. In this paper, we propose a recognition methods of antenna scan pattern based on visibility graph, including circular scan, sector scan, helical scan, raster scan, conical scan, phased array scan, phased array azimuth scan and circular elevation scan. We have mapped the radar scans pattern, the azimuth and elevation curves of various scan pattern and the signal variation of the EW receiver. Moreover, the related features are extracted from the visibility graph and the seven radar scan patterns are classified by five kinds of classifiers. Simulation experiments verify the efficiency of the algorithm.
Hg Content in Jiaozhou Bay from Atmosphere
Authors: Yang Dongfang , Yang Danfeng , Fan Bailing , Su Chunhua , Zhu Sixi
Published: November 2019

In May, August and October of 1991, the variation of Hg content in Jiaozhou Bay was0.006-0.086μg/L, which satisfies the Case I and IISea Water Quality Standard, and there was mild or none pollution in Jiaozhou Bay, specifically, 0.010-0.06μg/L in May, 0.021-0.086μg/L in August and 0.006-0.074μg/L in October, which were all mild pollution. It was mainly transported by ships and wharfs, atmospheric sedimentation and open sea current, 0.06μg/L, 0.074-0.086μg/L and 0.08μg/L, respectively. The modelling diagram was established to display the different paths and contents of Hg in Jiaozhou Bay. Ships and wharfs were mainly mildly polluted by Hg content in May, atmospheric sedimentation and open sea current in August and atmospheric sedimentation in October. It showed that Hg content was transported by human in two ways. On the one hand, it was directly emitted by ships and wharfs to sea, which was low in content and short in period. On the other hand, it was discharged indirectly by human to sea in atmosphere, which was high and long. Thus, it is necessary to pay attention to the transport of Hg content in atmosphere, which was wide in space and long in period.
AHP Based Driving Behavior Evaluation Model
Authors: Zheng Haocheng , Wu Yufan , Wang Zhili , Zhang Zhengyu
Published: November 2019

Driving behavior is one of the most important reasons that affect traffic safety and energy saving. In view of the management problems existing in traffic safety, it is necessary to strengthen the driver’s safety and energy conservation awareness. To this end, based on the driving status information collected by the road transportation industry in the vehicle networking system, we propose a data-driven approach to dig deeper into driving behaviors that affect driving safety and energy efficiency. Among them, we used the quantitative description of idle speed preheating, overspeed, fatigue driving and other series of indicators, and combined with the AHP (Analytic Hierarchy Process) to construct a comprehensive driving safety evaluation index system. Assisting the Ministry of Transportation in managing roads more efficiently and creating a harmonious driving environment via our evaluation model.
Maneuvering Target Tracking in Wireless Sensor Network with Range Only Measurement
Authors: Wang Yufeng , Feng Xinxi
Published: November 2019

In this paper, we consider the condition of range-only measurement, and propose a novel maneuvering target algorithm in wireless sensor network (WSN) that can estimate the position and velocity of the target. Our algorithm combines maximum likelihood estimation and interacting multiple model filtering. Based on range information that the sensors measured, we use maximum likelihood method with constraint information to estimate the position, and then adopt interacting multiple model filtering to further improve the tracking accuracy. Simulation results shows that our algorithm can track maneuvering target effectively in wireless sensor network when we can obtain only range information.
The static friction force in commensurate structures with an asymmetric deformable substrate potential
Authors: Jia Liping , Li Xiangfu , Yin Huamin , Cao Pengfei
Published: November 2019

It is used that a series of interacting atoms subjected in an asymmetric deformable substrate potential. With the increase of external driving force, the system moves from locked state to sliding state. This critical force is also known as depinning force or the maximum static friction force. It has been analyzed for the shape parameter.
Dependence of static friction force on stiffness in a confined chain with the incommensurate and commensurate structrue
Authors: Jia Liping , Li Xiangfu , Yin Huamin , Cao Pengfei
Published: November 2019

It is used that a series of interacting atoms. They are confined between two sinusoidal substrate potentials. When the top substrate is driven by the external driving force, its velocity changes from zero to non-zero. The dependence of the static friction force on the strength is presented for the incommensurate(the spiral mean and the golden mean ) and commensurate structrue. It is found that incommensurate structures is more likely to produce superlubricate phenomenon more than commensurate structures under different stiffness coefficients.
An interval interference reliability evaluation method for structural strength
Authors: Xin T D , Zhao Y L , Duan Y S
Published: November 2019

The structural strength reliability analysis can effectively improve the service life of the structure. Based on the interval method and stress-strength interference method, the structural stress and strength at any time can be converted into the standardized interval. According to the relationship between the critical state function and the standardized interval, the interval interference reliability index η is defined. And then an interval interference evaluation method is proposed for structural strength. The validity of the method is verified through compared with the interval reliability method and the stress-strength interference reliability method. The results show that the proposed method can analysis the structural strength reliability without the parameter distribution form.
The prediction method of supporting force distribution for the refitting vehicle
Authors: Ma Hongfeng , Guo Youwei , Liu Gaojie
Published: November 2019

The supporting force distribution is very important for the vehicle to maintain safety and stability, especially for the heavy-duty refitting vehicle with eccentric load. A simple and generic model to compute the supporting force distribution is essential in the design stage of refitting vehicle, whereas there is little research involving in solving this problem by now. This article presents an efficient and simple method to predict the supporting force of tire (supporting point). Firstly, the model for the vehicle with three or four axles is simplified. Then, the mathematical matrix is established by force equilibrium equation, moment equilibrium equation and deformation compatibility equation. With the known parameters of load, position and dimension, the force of every supporting point can be calculated, and so the supporting force distribution is acquired. Finally, the method of predicting force distribution is utilized to computing the supporting force of a vehicle, and a corresponding experiment is also implemented. The results indicate that the general prediction method to calculate supporting force distribution presented in this paper is accurate and validated in the pre-design stage of the refitting vehicle.
The Influence and Anslysis of Gas Content on the Pressure Fluctuation induced by Cavitating Propeller
Authors: Chen Peng , Ye Jinming , Li Xiang , Tang Zhiyin
Published: November 2019

A ship hull model with all accessories is used to simulate the wake field of the propeller of a twin propeller ship in a large circulating water channel.The similarity of propeller wake field is guaranteed.The influence of air content in water on pressure fluctuation by cavitating propeller is studies.The cavity form of propeller was observed under the condition of different air content in water.The pressure fluctuations induced by cavitating propeller behind ship hull is also measured.The results showed that the air content has a significant influence on the pressure fluctuations. Each measuring points and each order frequency of pressure fluctuations amplitudes increase with the decrease of air content.The main reasons of influence of air content on pressure fluctuations are analyzed.It is proposed that how to set the air content in the model tests.
Geomechanics: historical contributions, current challenges and considerations on development for the new era
Authors: Song Licai , Li Huijun
Published: November 2019

Geomechanics is a marginal subject combining mechanics and geology and thus can be regarded as a branch of mechanics. Geomechanics is a descipline invented by China, and has made outstanding contributions in both theoretical and practical fields fulfilling national key demands. However, under the new situation, it is also faced with both challenges theoretical and practical challenges in fulfilling national needs. In this article, the authors analysed the challenges, and pointed out strategies for develping Geomechanics in the new era: rebuilding confidence in the advantage of Geomechanics, refining and enhancing already existing progresses and deploying future research concertrated on providing Geomechanics solutions to key national needs.
Comparative analysis of Geomechanics and General System Theory, Earth System Science and Geomechanics’ unique advantages in comprehensive survey of natural resources
Authors: Song Licai , Zhang Linyan
Published: November 2019

Under the backgrounds of comprehensive investigation of natural resources, Earth System Science becomes popular. However, it still needs further development. Geomechanics possesses the merits of General System Theory and has endured more than half a century’s practical test. This article aims to analyse the advantage of Geomechanics through comparison of connotations and characteristics of Geomechanics, General System Theory and Earth System Science. By comparison and relationship analyses, the authors pointed out that Geomechanics possesses the theoretical foundation and scientific potential of solving the problems in Earth System Science. Moreover, it can support the “Trinity Comprehensive Investigation and Evaluation” of energy and mineral resources, technical conditions, engineering construction and environmental impact.
Research and Design of Wireless Communication Module Based on Single Chip Microcomputer
Authors: Du Li
Published: November 2019

This paper studies a wireless communication control module with AT89S52 microcontroller as the control core. The basic principle, main circuit, hardware framework and software framework of the system are described in detail. The whole system adopts modular design, which mainly includes wireless communication control circuit between single-chip microcomputer and lower-level computer, and communication interface circuit between wireless communication module and 51 single-chip microcomputer. The communication control system communicates with the nRF2401 through the SPI of the 51 single chip microcomputer, thereby forming a connection with the lower computer through the wireless communication control module, controlling the lower machine motion controller, and saving the data received by the communication into the extended memory. The communication method of this module is simple, in addition to remote real-time control, it can also be widely used in industrial monitoring and data acquisition systems.
The Design of Planar Rectangular Spiral Antenna for Corona Discharge in Transmission Lines
Authors: Yin Chuangrong , Wei Haikun , Kuang Fan , Hei Guoyu , Zhang Wei
Published: November 2019

With the increasing grade of high voltage transmission lines, the frequent occurrence of corona discharge has brought great potential safety risk and power losses to power system. Therefore, the detection of corona discharge in transmission lines is of great significance to power system. Rectangular spiral antenna is widely used because of its smooth impedance and better circular polarization characteristics. In this paper, a planar rectangular spiral antenna is designed for the detection of radio frequency electromagnetic waves given out corona discharge of transmission lines. The basic structure of the antenna is determined by optimizing the length, spacing and turns of coil. The feasibility of the antenna is verified by experiments.
Grid dispatching domain division related to large-scale renewable energy grid-connecting
Authors: Shunjiang Wang , Yapu Zhang , Yan’an Li , Rongbin Ju , Zeng Li
Published: November 2019

As the proportion of renewable energy access to the grid increases, regional phenomenon of wind power and photovoltaic curtailment highlights. In order to improve the capacity of new energy consumption and alleviate the complexity of power grid scheduling, a regional power grid scheduling domain partitioning method for high proportion of renewable energy access is proposed. The renewable energy regional grid operation domain is divided into normal domain, abnormal domain and emergency domain, and combined with the regulation capability of conventional thermal power units and the power fluctuation ability of energy storage, the divide indicators of each operation domain is defined. Finally, an example analysis of the Dalian regional power grid in Liaoning is carried out to verify the validity and correctness of the grid multi-domain division method.
Multi-wind Farm Output Correlation Model Based on Clayton-Copula Function
Authors: Jinning Shan , Xiaodong Chen , Chenqi Wang , Guiyang Xing , Baoshi Wang
Published: November 2019

Because multiple wind farms are connected to the grid at the same time and the total amount of energy in the same wind zone is limited, there is a strong correlation between wind farms with similar geographical locations. Neglecting this correlation can lead to a large difference between wind power analysis and actual operation, which in turn leads to a series of adverse consequences. In this paper, we use nuclear density estimation to establish the edge distribution of wind power output, compare and analyze various Copula functions based on correlation parameters and entropy weight optimization theory. The simulation analysis results show that the Clayton-Copula function is the best correlation function, which can describe the tail part of the random time series more accurately.
Power Consumption Prediction Based on Deep Learning
Authors: Zhang Xuanwen , Liu Li
Published: November 2019

The purpose of this paper is to select a power consumption forecasting method with high accuracy and low error. Previous power consumption forecasting methods are basically based on the optimization and improvement of the original classical forecasting methods, and the error has not been substantially reduced. It was not until 2006 that the unveiling of deep learning technology opened a new chapter in the direction of artificial intelligence, and the research of power consumption forecasting has ushered in a new wave.

In this paper, the origin of deep learning technology is introduced, and the LSTMs model of deep learning is built, and the short-term electricity consumption forecasting model is built, which can complete the forecasting of the time series of electricity consumption.

At the end of this paper, a case simulation analysis is carried out. After 57 days’training of power consumption data, the power consumption curve in the next week is finally obtained. It is found that the error rate is very small and the accuracy is high.
Research on HVDC Converter Valve Thyristor Overvoltage Protection
Authors: Wang Zhen , Feng Lei
Published: November 2019

Converter valve is the core component of HVDC system, and its safety operation is significant for the system. However, the ability of thyristor in converter valve to withstand overvoltage is weak. Even transient overvoltage can lead to thyristor breakdown. Thus, thyristor is needed to configure overvoltage protection. The paper analyzes two kinds of thyristor overvoltage protection scheme BTC (Backup Trigger Circuit) and BOD (Break Over Diode), and then sets up PSPICE models to conduct simulation analysis. Finally, the performance of the two kinds of overvoltage protection is verified by practical circuit experiment. The result shows that both protection schemes can satisfy the requirement of thyristor overvoltage protection.
Research on data transmission based on power line carrier
Authors: Zhang Chuyu , Deng Huaqiu
Published: November 2019

In the research of power line carrier data transmission, STC89C52 chip is selected as the core microprocessor and KQ130F carrier module as the receiving and transmitting carrier of the system. The optimization of modulation and demodulation rate and the reduction of bit error rate are realized by improving the programming algorithm in the transmission process. In the analog LED street lamp monitoring system, the PC performs the data transmission test by setting up the hardware test platform through the actual application process of the power line carrier to the terminal control.
Smart Grid Risk Warning Based on Multi-Level Fuzzy Analytic Hierarchy Process
Authors: Zhang Liang , Wang Shudong , Jia Guangyao , Chen Lu
Published: November 2019

Real-time control of the risks that may occur in the smart grid is of great significance for the safe and efficient operation of the smart grid. This paper establishes a risk early warning system for smart grids based on analytic hierarchy process and fuzzy theory. Firstly, the analytic hierarchy process is used to comprehensively consider the system line, load, system power supply capacity and environment and other factors to establish a smart grid evaluation index system. Then the comprehensive weights of each level of indicators are calculated, and then the evaluation matrix of the index is established by combining the membership function. Finally, the fuzzy theory is used to predict the system risk. The case study shows that the qualitative and quantitative early warning system for assessing smart grid risk has good practicability.
Frequency hopping radio individual identification based on energy spectrum blended subtle characteristics
Authors: Yang Xin , Qi Zisen , Wang Shaobo
Published: November 2019

For the problem of low recognition rate and large computational complexity of frequency hopping radio stations, a blended subtle characteristic extraction method based on energy spectrum is proposed. Considering that the time-frequency energy distribution is widely used in individual feature extraction, the time-frequency energy spectrum of the frequency hopping signal is obtained by the sparse reconstruction method firstly. Then the fractal theory is used to extract the feature vector set including time-frequency energy spectrum Rayleigh entropy, multi-fractal dimension and difference box dimension with multi-scale block extraction. Finally, the support vector machine classifier is used to train, classify and identify the feature set to realize the individual identification of the frequency hopping station. The recognition performance of the proposed method and the other two methods are compared and verified through the frequency hopping signals of four stations. The experimental results show that compared with the other two methods, the proposed method has higher recognition rate under low SNR and a small number of training samples.
Design of weak signal detection circuit of CMOS detector with large dynamic range by twice sampling method
Authors: Weiming Wang , Yuanqing Gu , Xiangdong Luo
Published: November 2019

In the field of detecting weak signals with large dynamic range, CMOS image sensor, as an optical sensor component, has the advantages of large dynamic range and wide spectral response range, and is often used to detect weak signals. The commercial CMOS image sensor system usually adopts the ADC with 16-bit accuracy, which can not satisfy the detection of weak signal in some cases. In this study, CMOS image sensor S10122 chip from Hammatsu company of Japan was used as the core device. ADI company’s 16-bit ADC chip LTC2182 and 16-bit DAC chip LTC1668 were used. The circuit was designed according to twice sampling principles to improve ADC accuracy. The results show that the accuracy of ADC can be improved from 16 to 18 bits under certain conditions.