bluuebunny/crossref_metadata_2025_split huggingface dataset:
Short-term Traffic Flow Forecast Based on DE-RBF Fussion Model
Authors: Hao Shurong , Zhang Mingming , Hou Anping 
Published: May 2021

Abstract
The road traffic system is a time-varying, complex nonlinear system. Real-time and accurate road short-term traffic flow prediction is the key to realizing the traffic flow guidance system. In order to improve the prediction accuracy of short-term traffic flow, this paper proposes an algorithm based on the fusion model of differential evolution algorithm (DE) and radial basis function (RBF). This method takes the fitness function as the measurement standard, and uses the DE algorithm to optimize the RBF parameters to obtain the optimal short-term traffic flow prediction value. Through MATLAB simulation experiments, a relatively accurate prediction of the short-term traffic flow of the DE-RBF fusion model is realized. The mean square error (MSE) and the average absolute error percentage of actual and predicted values (MAPE) analysis index are introduced as the evaluation index of the prediction model. After comparing with the two prediction network models of radial basis function (RBF) and wavelet function (WNN), the results show that the DE-RBF fusion model proposed in this paper is effective and feasible for short-term traffic flow prediction.
Research on Equipment Maintenance Support Technology Based on Multi-agent
Authors: Chen Jianping , Li Suhang , Yang Yijun , Ni Ming , Wang Xunbao 
Published: May 2021

Abstract
The maintenance of weapons and equipment currently is mainly regular maintenance. Due to the different running time, working conditions and personnel operation level of each equipment, the uniform maintenance requirements are not scientific. At the same time, the time, place and quantity of equipment failures are lack of effective prediction methods, therefore, the current working state of equipment maintenance is usually called “fire fighting” maintenance. With the increasing number of weapons and equipment, and the increasing complexity of technology, the existing maintenance and support methods have been unable to meet the needs of continuous intact of equipment and rapid troubleshooting. Multi-agent-based equipment maintenance support technology comprehensively considers factors such as mission requirements, equipment distribution, and equipment status, and treat each maintenance resource as an agent. Then use artificial neural network (ANN), reinforcement learning and other intelligent algorithms to realize the overall planning of maintenance and support resources. It can reduce the equipment failure rate and maintenance costs and solve the problem of unreasonable resource allocation.
Research on Filling of Large Coastal LNG Fuel Powered Ships
Authors: Geng Jiezhe , Chao Han 
Published: May 2021

Abstract
With the implementation of MARPOL convention and related environmental protection policies, LNG as fuel power has become an important technical means to promote the green development of shipping. The construction and operation of large ocean-going ships in the world put forward an urgent demand for LNG filling. This paper points out that there is an urgent need to issue the design and technical standards of shore-based filling stations, the approval and operation of filling stations, the regulations on ship navigation management, and the related research on safety and emergency, etc., which puts forward the work direction for the future coastal LNG filling work.
Research on Pricing Strategy of Three-echelon Dual-channel Supply Chain under Market Equilibrium
Authors: Sha Jin , Zheng Sisi 
Published: May 2021

Abstract
The healthy and sustainable development of supply chain must be based on the consideration of both enterprise profit and consumer benefit and only the market behavior under perfect competition environment might maximize the social total welfare. The market equilibrium in perfect competition market is the premise of maximizing the sum of consumer and producer surplus. Taking the pricing strategies of supplier, manufacturer and retailer as research objects, market demand and supply functions considering the effect of different channel prices is built, and a three-echelon dual-channel supply chain model is constructed. Then, the optimal pricing strategies of decentralized and integrated three-echelon dual-channel supply chain are developed by applying two-stage stackelberg game theory and overall revenue maximization principle. Furthermore, the conditions of optimal equilibrium prices existing with the restriction of market equilibrium are discussed, and the expressions of the optimal equilibrium prices about different supply chain structures are analyzed. Eventually, we use method of numerical analysis to explain the pricing strategy we analyze.
Research on Decision and Coordination Model of Fresh Products Supply Chain with Quality and Price
Authors: Liu Qianwen , Zhang Shun , Zhao Chen 
Published: May 2021

Abstract
With the adding emphasis on the fresh products quality, the competition among suppliers has been expanded from pure price competition to the competition of the quality and price of fresh products. By introducing the price impact coefficient and the influence coefficient of quality of two variables, this paper analyzes the game equilibrium of a supply chain respectively in the centralized, decentralized and coordination decision-making model. Through numerical analysis, the paper analyzes the retailers, manufacturers and the change of each decision variable value of the supply chain. The results indicate that the price of sales and the quality of fresh food are related to the variables in the three different decision-making model, and when the revenue sharing coefficient and cost coefficient are in a rational range, after revenue sharing cost sharing contract is coordinated, retailers must pay fixed costs to compensate for manufacturers. The whole supply chain profit is greater than the decentralized decision-making gains after the coordination.
Stability of Linearly Switched Demand Dynamics in Supply Chain Based on Inventory
Authors: Wang Yubao , Wang Weihua 
Published: May 2021

Abstract
The organized supply chain is one of the best competitive ways for the retailer. The dynamics and stability of a supply chain under inventory and price with the feature of piecewise linearity is analysed. This switched linear model composed of four subsystems for the first time. On the basis of linear switched model, some stabilities are derived and the global dynamic behavior is theoretically examined. It is illustrated that the combination of the stock-dependent demand function and inventory can bring about the stability result under, but also arise more complicated nonlinear fluctuations under bη ≥ 1
Research on Multi-criteria Material Selection of Automobile in Full Cycle under the Background of Green Manufacturing
Authors: Ding Zhensen , Fang Haifeng , Yao Zhanhui , Liu Jinzhou , Wang Jia 
Published: May 2021

Abstract
Under the background of the continuous strengthening of green manufacturing, the automobile industry, as a typical representative of the industry, will be an important battlefield for the green development of China’s industry. In addition, with the emergence of new alternative materials for automobiles, the selection range of materials for automobile parts is gradually expanding. Literature from year 2009 until year 2019 were collected which is focused on related automotive material selection. It’s worth noting that the concept of “green manufacturing” was proposed in 2018. It is found that the selection criteria of automobile materials have been expanded from only focusing on mechanical properties to economic performance, technological performance and environmental performance. The multi-attribute material selection method is emerging because of the more complicated material selection caused by the increase of environmental attributes, which also brought manifest divergences in the selection of secondary indicators and the setting of weights. According to the practical application, the optimization measures related on the selection basis of secondary indicators and setting weights from the perspective of producers and consumers in the whole life cycle were proposed.
The Research on Influencing Factors of Autonomous Vehicle Usage Behavior: Root Analysis Based on UTAUT2 Model
Authors: Zheng Hao , Gao Hongyan 
Published: May 2021

Abstract
As a new sustainable means of transportation, how to successfully make autonomous vehicles accepted and used by the public is a key challenge for research. Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, the research took the social media platform as the data source to conduct a grounded analysis, comprehensively considered the interaction of individual internal factors and external environmental factors, and combined the technology acceptance field, user behavior field, sociology, psychology, marketing and other disciplines to build an influencing factors of autonomous vehicle usage behavior model, which is suitable for Chinese market. The study found that performance expectation, effort expectation, social impact, facilitating conditions, price value, hedonic motivation, perceived risk and perceived trust influence individuals’ intention to use autonomous vehicles. Facilitating c zV Conditions, perceived risk and intention affect individual’s usage behavior. The level of individual knowledge plays a regulatory role in the use behavior. The results provide a decision basis for the government and enterprises to effectively promote the use of autonomous vehicles.
Research on C-end Customer Demand Based on Cluster Analysis
Authors: Wei Zhenlin , Wang Lan , Ouyang Yuzi 
Published: May 2021

Abstract
With the rapid development of Internet economy, the problem of “last kilometer” distribution difficulty in B2C e-commerce has become one of the pain points of the whole industry, and improving the customer service level of C-end has become an important content of enterprise development. The change of C-end demand distribution will have a significant impact on the location of end-of-line service outlets, so this paper studies the spatial distribution of C-end customer demand points. According to the significant spatial clustering of C-end customer demand points in geographical space, K-means algorithm and DBSCAN algorithm are selected to cluster the demand points. The clustering results of the two algorithms are evaluated by the internal distance and the average distance between clusters. The comparison results show that k-means algorithm has better clustering effect on the demand points, and its clustering results can also be used as the end the main measurement index of service network layout provides services for terminal service network location.
Comparative Analysis of Prophet and LSTM Model in Drug Sales Forecasting
Authors: Meng Jie , Yang Xiao , Yang Chengwei , Liu Yang 
Published: May 2021

Abstract
With the rapid development of China’s pharmaceutical industry, accurate prediction of drug sales has become the key to enterprises’ competitiveness. Sales forecasting research has very important value for strategic decisions and improvement measures made by enterprises. We studied mainly two machine learning methods of pharmaceutical sales prediction in this paper, analyzed deeply the prophet model and LSTM, and carried out a comparative experiment on these two methods using real sales data. The experimental results show that the LSTM model is more accurate than the Prophet model on drug sales forecasting.
Study of Eco-evolution Path of Home Textile Industry under the Background of Internet Plus
Authors: Zhao Hongshan , Ma Lin 
Published: May 2021

Abstract
Under the background of “Internet+”, home textile industry witnesses the revolutionary stages of value creation, value realization and value transmission. During the revolution, the industrial value chain has been reset, all-media transmission, C2B mass customization, O2O mode and collaborative creation of intelligent value, and other innovative development paths have emerged. Through the study of the eco-evolution path of home-textile industry, the current paper explores how traditional home-textile enterprises upgrade themselves properly in the Internet era, which can provide references to other traditional enterprises in need of upgrading and development.
Typical Zone Division of Karst Kevelopment in China
Authors: Liu Yukang , Li Hailing , He Yingding , Cao Xianfa 
Published: May 2021

Abstract
Determining the typical area of karst development in China would provide positive reference for theoretical research of engineering geology in karst areas in China. By quantitative or semi-quantitative analyzing on the distribution characteristics, climatic conditions and formation lithology of carbonate rocks in China, regional difference characteristics of karst development in carbonate rock regions in China is evaluated, and finnally the representative karst zone in China is reasonably and theoretically delineated and demonstrated. Results show that: the pure Carbonate rocks in southwest of China in tropical and subtropical climate zone which are very favorable for karst development, distributes continuously and massively, and therefore can be considered as the most typical karst area,. this is also a very explanation that karst morphology develops completely. Especially, karst in the zone including Guangxi Zhuang Autonomous Region, southeast and north-east of Guizhou province, and southeastern of Chongqing Municipality, is the most representative karst region in southwest of china because of its the purest carbonate rocks.
Multifractal analysis of spatial–temporal characteristics in the Alpine–Himalayan seismic zone
Authors: Chen Jiemin , Yan Zelin , Xu Linfeng , Liu Zhixin , Liu Yan , Tian Jiawei 
Published: May 2021

Abstract
The occurrence regularity and propagation mechanism of seismic activity are complicated and variable to be described by existing models. This paper presents a multifractal analysis of the Alpine–Himalayan seismic zone in time–space series. The multifractal spectrum of energy released from the seismic zone is obtained from different angles. Results show that earthquakes in the seismic zone possess complex multifractal characteristics in time–space series. Moreover, the clustering feature of the seismic activity intensity in the seismic zone is similar among the time–space series.
Artificial Neural Network Plan for Transmission Tower Structure Safety Assessment
Authors: Sun Mi , Xie Jinghai , Jiang Yu , Su Dongyu , Lu Shihua , Guo Jia 
Published: May 2021

Abstract
The security of transmission tower structure is the foundation to ensure the safe operation of power grid. The research of fuzzy qualitative assessment method for the structural health of transmission towers is the basic work of large-scale digital power grid engineering. In this paper, artificial neural network (ANN) is used as a generalized tool for structural health assessment of transmission towers. The feasibility of using artificial neural network to qualitatively evaluate the structural health of transmission towers is verified by numerical simulation data. In order to train the artificial neural network, the displacement, stress and other signals generated by the finite element model are calculated and used as the training input of the artificial neural network. The detailed stress results of the finite element model are calculated as the qualitative evaluation basis of the structural health, and the training output of the artificial neural network is generated. By the same method, the test set is generated, and it is found that the artificial neural network is feasible for the fuzzy qualitative assessment of the structural health of transmission tower, and the misstatement rate is less than 5%.
Research on the energy efficiency of the multiphase nanosecond pulsed discharge system with TiO2 photocatalysis
Authors: Che Rui , Sun Ming , Xu Haiyang 
Published: May 2021

Abstract
Energy efficiency of the system is always paid more attention in the research of the discharge plasma’s application technology. Based on the project of ballast water treatment technology by multiphase nanosecond pulse discharge cooperated with photocatalysis, the nozzles-plate electrode was adopted, system energy and energy efficiency were investigated with different discharge factors and compared when the nozzles were coated with the titanium dioxide (TiO2) film or not. The results show that cooperating with the photocatalysis, pulsed discharge system power and energy efficiency were not significantly affected. Reactor power increases with the absolute value of the input high voltage and pulse repetition frequency and decreases with the distance between the nozzles and the plate. There are no obvious effects of the numbers of the nozzles and the air flow rate. Energy efficiency of the system increases with the absolute value of the input high voltage, firstly, then decreases. It changes inversely with the air flow rate. The energy efficiency of the system decreases with the pulsed repetition rate and the distance between the nozzles-plate. It was up to 25.7% with the input voltage of - 30 kV, and the air flow rate of 80 mL/min, pulse repetition frequency of 50 Hz and 6 nozzles- plate distance of 0.5 cm.
Study on the application of multi-channel isolation power supply in non-equipotential circuits
Authors: Zhao Yuzhuo , Zang Yanchi , Xie Da , Li Xiang , Zhao Bowen 
Published: May 2021

Abstract
In non-equipotential circuits, there is the problem that the switching tubes do not share a common ground. This paper therefore addresses this problem by designing a multi-channel isolation power supply (MCIPS). It mainly includes the square wave generation circuit, the high-frequency transformer and three-terminal stabilized circuit. This paper provides a detailed theoretical analysis of the design and principles of these three circuits. Using Multisim to model a MCIPS simulation circuit and derive the output waveforms of each circuit. The correctness of this solution was ultimately verified. The study of this power supply is of great importance for bridge circuits.
Control Strategy of Plug-in Fuel Cell Hybrid Vehicle Based on Drive Cycle Recognition
Authors: Zhang Yanyi , Hao Dong , Meng Xiangfei , Wang Renguang 
Published: May 2021

Abstract
A control strategy based on drive-cycle recognition is proposed for the energy management control of plug-in fuel cell hybrid vehicle. Firstly, the drive-cycle recognition fuzzy controller was designed and the battery target SOC was adjusted according to the drive-cycle recognition results; Secondly, with the goal of improving the economy of the vehicle and the durability of the fuel cell, the energy management fuzzy controller and the fuel cell switch controller were designed, energy distribution of dual power source was realized combined with the target SOC control result; Finally, the comprehensive drive-cycle condition was established, the drive-cycle recognition strategy was simulated and verified basing on the MATLAB/Simulink simulation platform. The results show that the strategy achieves a reasonable adjustment to the target SOC of the battery, compared with the power following strategy, the hydrogen consumption is reduced by 7.8%, which reduces the occurrences of factors which affect negatively durability of fuel cell.
A new multilevel compensation system for neutral active grounding in distribution grid
Authors: Chen Zhongren , Lu Yipeng , He Yejun , Huang Jian 
Published: May 2021

Abstract
In order to achieve effect of full compensation and zero residual-current, a multilevel compensation system for neutral point active grounding is proposed. The system is composed of three-level compensators. When power grid is grounded, the first level compensates its capacitive current, the second level compensates its active current, and the third level compensates not only its harmonic current, but also the harmonics generated by the former two level compensators, so effect of full compensation is very obvious. When distribution grid is in normal operation, the system uses the asymmetric voltage method to realize accurate detection of capacitive current and active current. In case of single-phase grounded fault, the harmonic current is extracted by fast Fourier algorithm. Then three-level compensators are quickly put into operation for corresponding compensation. A low-voltage simulated power grid is built in the laboratory, and a compensation test is carried out. The test results show that the compensation of capacitive current and harmonic current in grounding fault current is accurate. After further improvement, the system can reach the practical level.
Low frequency vibration test on the loosening performance of bolts for towers of power grids
Authors: Yang Jialun , Xia Lingzhi , Liu Bin , Liu Yaduo , Zhao Bin , Zhang Lichun 
Published: May 2021

Abstract
This paper deals with loosening performance of bolts of transmission towers under low frequency vibration. To evaluate the loosening performance, 30 transverse tests for bolted joint are issued, whose frequency ranges from 1 Hz to 3Hz. The results show that double-nut bolts feature better loosening performance than single-nut bolts, and the loosening performance decreases along with the incensement of vibration frequency.
Effect of Particles on Discharge Characteristics of SF6/N2 Mixed Gas under Power Frequency Voltage
Authors: Pang Xianhai , Wang Xiao , Qiao Songsong , Liu Houfa , Long Yuyou , Xiu Shixin 
Published: May 2021

Abstract
Residual metal particles appear in gas-insulated equipment, which may affect the insulation properties of electrical equipment. In this paper, a specific experimental device is designed to study the discharge characteristics of SF6/N2 mixed gas at different pressures and different mixing ratios under power frequency voltage, and the effect of particle shape, particle material type and gas pressure on the discharge characteristics of SF6/N2 mixed gas. The distortion effect of the shape of the particles and the type of the particulate material on the electric field between the electrodes was simulated. It is found that the breakdown voltage of SF6/N2 mixed gas increases with the increase of gas pressure and SF6 concentration. When the particles are present, the nonlinear effect of metal particles on the breakdown characteristics of SF6/N2 mixed gas in-creases with the increase of gas pressure. Obviously; the more irregular the shape of the particles, the greater the uneven-ness of the corresponding electric field, the greater the breakdown voltage of the SF6/N2 mixed gas; the particulate materi-al also affects the breakdown voltage of the SF6/N2 mixed gas, copper particles and The breakdown voltage of aluminum particles is approximately the same at the same gas pressure, and the influence of iron particles on the breakdown voltage is smaller than that of copper particles and aluminum particles. The research results of the paper have reference value for the study of SF6/N2 mixed gas characteristics and its application in electrical equipment such as GIS.
Study on Measurement Error of Power Frequency Electric Field Intensity Caused by Change of Humidity on Surface Resistance of Field Intensity Meter Supports
Authors: Zhang Kai , Zhou Bin , Yang Lan , Li Yu , Ni Jiang 
Published: May 2021

Abstract
This paper analyzes the different measurement results of field intensity meter in different environments, which confirms that humidity has a great influence on the support parameters of field intensity meter. In addition, by testing the actual electric field, the change of dielectric constant and resistance of field intensity meter and its support under different relative humidity conditions, and comparing the simulation results of COMSOL simulation software, it is concluded that the error of field intensity meter measurement results mainly comes from the influence of humidity on the surface resistance of field intensity meter support, and the relationship between the surface resistance of the support and humidity is obtained.