bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influencing Factors of Urban Residents’ Garbage Classification and Recycling Behavior Driving Mechanism in Artificial Intelligence Environment
Authors: Gan Baiqiang , Zhang Chi 
Published: December 2020

Abstract
With the rapid development of urbanization, urban domestic waste is also increasing, if the garbage cannot be effectively classified, there will be a dilemma of garbage siege. In recent years, artificial intelligence technology has been applied in the field of garbage classification, which provides a convenient means for garbage classification. However, technological innovation can only alleviate the accumulated total amount of garbage, and finding the source of garbage generation is the key to solve the problem. Therefore, based on the theory of planned behavior, A-B-C theory and interpersonal behavior theory, from the policy level, the social level and the individual level, this paper puts forward some suggestions, it is composed of government, society, individual and other organizations, and puts forward the corresponding research hypotheses. Through interviewing and questionnaire survey in Guangzhou, the sample data are collected, and then regression analysis and structural equation model analysis are used to obtain the influence degree value of residents’ attitude towards garbage classification, subjective norms, perceived behavior control, situational factors, and government legal regulation on residents’ living garbage classification willingness. The results show that residents’ attitude towards domestic waste classification is significant and the government’s legal control factors are the key factors affecting the residents’ willingness of garbage classification.
Ecological Port And Navigation Engineering Evaluation Principle And Standard
Authors: Yan Chen , Yao Tianzhi 
Published: December 2020

Abstract
How to evaluate the ecological port and navigation project? What is the principle of evaluation? What are the criteria for evaluation? This paper discusses the evaluation principle and standard of ecological port and navigation engineering, and puts forward the evaluation principle of ecological port and navigation engineering. Then with the standard, the construction of ecological port and navigation project has certain guiding significance.
A novel synthesis of Nb2O5@N-CNF nanocomposite as anode material for superior sodium storage
Authors: Zhang Yu , Fang Li 
Published: December 2020

Abstract
The development of a novel anode material with excellent cycle performance is of great significance to the promotion of the sodium ion battery. Adopting the renewable material BC as raw material, Nitrogen-doped Nb2O5-three-dimensional porous carbon fiber network composite (Nb2O5@N-CNF) is prepared by a low-cost approach in the paper. The in-situ growth of Nb2O5 nano-particles on the carbon fiber surface inhibits the agglomeration of particles. The porous structure of carbon fiber promotes ionic transfer. Meanwhile, the structure of pyridine nitrogen, which is formed by the doping of N atoms, further enhances sodium storage. After 1000 times of cycle under the current density of 2 A g−1, the capacity of the Nb2O5@N-CNF electrode is 79 mAh g−1, its capacity retention increasing significantly, with great application prospect.
Development and Construction Management System of Pumped-Storage Power Plants in China
Authors: Chen Zhihe , Guozhong Liu 
Published: December 2020

Abstract
Pumped-storage power plant(PSPP) is a special form of power supply. It is expected that the installed capacity of PSPP in China will reach 90GW by 2025. This paper summarizes the development of PSPP in China, and analysis the influencing factors of the configuration of PSPP, introduces the typical operation mode of PSPP and the existing problems in its development, and puts forward relevant policy suggestions for the development of PSPP.
The knowledge spillover effects of green technology innovation of low carbon regulation
Authors: Ding Youqiang , Xiong Aihua 
Published: December 2020

Abstract
The green technology spillover (GTS) is conducive to follower’s innovation opportunities but harmful to pioneer’s innovation advantages. Based on the knowledge production function and the panel data of cities in China, this paper discusses the effects of GTS on the relationship between the low carbon regulation (LCR) and the green technology innovation (GTI) by using the Spatial Durbin Model. We found that LCR makes a decrease-increase effect of the pioneer’s GTI different from an increase-decrease effect of the follower’s GTI.
Research on Location and Recognition Method of Voltage Sag Disturbance
Authors: Chen Xiaodong , Li Duo , Zhang Jun , Ning Kejia 
Published: December 2020

Abstract
The accurate positioning of the voltage sag disturbance source relative to the monitoring point helps to clarify the responsibilities of both parties. This paper proposes a brand-new single-frequency cross S-transform perturbation power positioning method for locating voltage sag disturbance sources. First, the voltage and current signals collected at the monitoring point are transformed into a single fundamental frequency S to obtain a complex vector of the fundamental frequency of the voltage and current; then, the complex vector of the voltage and current fundamental frequency is subjected to a single fundamental frequency cross S transformation. The module extracts the instantaneous apparent power, and then obtains the instantaneous apparent disturbance power; finally, the disturbance power criterion is used to locate the source of the voltage sag disturbance. Through analyzing and judging the monitoring point of the problem caused by short circuit fault, the result proves the accuracy and effectiveness of the proposed method.
Pitch control of wind turbine based on deep neural network
Authors: Jie Wei , Jingchun Chu , Lin Yuan , Wenliang Wang , Jian Dong 
Published: December 2020

Abstract
This paper analyzed the input and output data of wind farm based on deep neural network, developed intelligent model, and realized the predictive modeling of important parameter variables and control of wind turbine. By establishing the Deep Extreme Learning Machine(DELM), the higher-order nonlinear model is simplified. In this structure, unsupervised hierarchical ELM is conducted for feature extraction, and the features of the lower layer are transferred to the higher layer through layer by layer coding to form a relatively complete feature representation. Finally, the Extreme Learning Machine (ELM) is used to complete the mapping of feature representation to target output to minimize the loss of information in the transmission process. The target output is used as reference data for Pitch control of wind turbine, which is proposed by using a radial basis function (REF) neutral network. Simulation results from GH-Bladed show that proposed control algorithm can mitigate the loads effectively. The algorithm provides a practical reference for the design of wind turbine controller.
Short-term electric power demand forecastingusing a hybrid model of SARIMA and SVR
Authors: QiheLou  , QiLyu  , Na Zhixiong , Ma Dayan , Ma Xiaoguang 
Published: December 2020

Abstract
Short-term electric power demand forecasting is the most basic and important application of smart grid. With the rapid development of renewable energy and clean energy in recent years, power demand forecasting gains special attention again. It has a great impact on the planning of power generation units and the purchase and sale of power market. Furthermore, itis also conducive to the realization of demand response and resource allocation efficiency and reliability, thus contributing to the Photovoltaic power generation system as well. Although generous methods have been proposed, it remains to be an open challenge owing to its limited precision. In this paper, a hybrid method of Seasonal Auto-Regressive Integrated Moving Average (SARIMA) and Support Vector Regression (SVR) is proposed for hourly forecasting, which overcomes the difficulty of generalization of a single model. The core thought of this model is using SARIMA to fit the linear part of the series and correcting the deviation by SVR. We tested the accuracy of this method on a public data set, and the result shows that it performs much better than the single SARIMA model on the fitting effect. Also, we compared our model with the recent three works, and it demonstrates a decrease of 18.102%,10.534% and 4.757% in forecasting error respectively. To our surprise, when we usedthe previous four hours of data to predict the current data by the single SVR, we got the best performance of all models. In the end, we analyzed the possible causes for this result.
Overcharge experiment analysis of the LiFePO4/C battery with prelithiation technology
Authors: Gao Fei , Hui Dong , Yang Kai , Zhao Fenggang , Yang Longfei , Wang GuoBao , Wang Shuping , Fan Minghao 
Published: December 2020

Abstract
Prelithiation technology can improve the service life of batteries, but whether it will affect the safety of batteries has not been studied. In this paper, the temperature differences between LiFePO4/C batteries with prelithiation technology and conventional LiFePO4/C batteries in overcharge test are analysed, the shell deformation values of these two types of batteries are compared, and the influence of battery capacity retention rate on overcharge safety of batteries is discussed. The analysis shows that there is no obvious difference in overcharge safety between two types of batteries, and batteries with prelithiation technology are similar to conventional batteries in terms of shell deformation value, the highest temperature of shell and the temperature fluctuation of flue gas escaping from pressure relief valve.
Research Overview on Numerical Simulation of The Dismantling Process of Large-span Steel Structural Roof
Authors: Xiaochi Yang 
Published: December 2020

Abstract
The dismantling of large-span steel roof is a complex evolutionary process involving redistribution of internal force. In order to ensure conformity of the structural internal forces to the design, safety and reliability during the demolition, it is necessary to make accurate simulation analysis of the dismantling process to determine a reasonable dismantling plan. With a review of the simulation methods adopted in the dismantling process of large-span steel structure and analysis of the relevant research results, this paper elaborates on advantages, disadvantages and adaptability of each method, which can serve as a basis for the study of roof dismantling.
Temperature effect on preparation of water-Storage ceramic foam with vanadium-titanium magnetite tailings
Authors: Li Lin , Jiang Tao , Zhou Mi , Chen Bojian , Chen Chao 
Published: December 2020

Abstract
Massive accumulation of vanadium-titanium magnetite tailings (VTMT)—a kind of common industrial solid wastes—will pose enormous harms to both ecological environment and economic development. Based on the preparation of water-storage ceramic foam by taking full advantages of 50 wt% VTMT and 50 wt% waste glass, the effect of sintering temperature on the sample performance was further investigated through a test, and the foaming mechanism at high temperature was deeply probed. The results show that as the sintering temperature rises, the bulk density and compressive strength of the sample gradually decline, its water absorption per volume reaches the maximum value and the average pore diameter inside the sample is gradually increasing. The optimal sinter temperature is 1,040 °C, and the water absorption, bulk density and compressive strength of the sample are 56.5%, 0.26 g/cm3 and 0.68 MPa, respectively.
Calculation method of production pressure drop based on BP neural network velocity pipe string production in CBM wells
Authors: Zhu Hongying , Qi Yaoguang , Zhang Fenna , YunfeiSong  , LiangLin  , Zhang Jian 
Published: December 2020

Abstract
In the stable production stage CBM wells have the characteristics of high gas production and low water production. The use of continuous velocity tube technology for drainage can achieve better drainage results. Accurate and rapid prediction of the pressure drop of velocity pipe string production in a coalbed methane well has become the key to the operation and management of velocity pipe technology. This paper uses the nonlinear mapping and prediction capabilities of the BP neural network to build a three-layer BP neural network to construct a velocity pipe string production pressure drop prediction model. The model is based on gas production, water production, bottom hole pressure, pipe string diameter, and well depth. The five factors are input, and the pressure drop of the pipe string is the output, which can quickly and accurately realize the pressure drop analysis and calculation of the speed pipe drainage. The analysis shows that it is feasible to use the BP neural network to calculate and analyse the pressure drop of the velocity string of coalbed methane wells.
New Energy Generation Converter Harmonic Evaluation Based on Operation Data
Authors: Nan Wang , Yan Cheng , Ti Guan , Qiang Ma , Yujie Geng , Shibo Wang , Jiawei Xing , Shumin Sun 
Published: December 2020

Abstract
The research on the harmonic mechanism and features of new energy generation units is crucial for ensuring safe and stable operation of new energy generation. In this paper, a big data analysis method suitable for the operation data of new energy power plant is used to analyse the harmonics generated by PWM modulation and dead zone effect of switching devices and the interharmonics generated by DC side voltage fluctuation. The simulation analysis verifies the harmonic characteristics of new energy power converter, the model basis of new energy power generation operation evaluation and power grid connection certification.
A novel approach of Landsat 8 imagery to predict PM2.5 concentrations in a south-eastern coastal city of China
Authors: Yang Lijuan 
Published: December 2020

Abstract
Satellite remote sensing data with moderate-to high-resolution has been commonly used in deriving spatial coverage of PM2.5 concentrations in urban areas. Previous studies focusing on city-scale PM2.5 estimation mainly retrieved aerosol optical depth from moderate-to high-resolution remote sensing data. In this study, the spectral response experiment was carried out to explore the sensitivity of spectral wavelengths to PM2.5 concentrations in Fuzhou, China. The results showed that the near-infrared reflectance was much more sensitive to PM2.5 than other wavelengths. We also found that the difference vegetation index (DVI) presented higher correlation with PM2.5 than other indexes. A linear mixed effects (LME) model was then developed to explain the variability of PM2.5, and the results showed that the overall R2
of LME model using DVI and meteorological parameters reached 0.80 with RMSE of 7.82 μg/m3. The results suggested that the proposed LME model using DVI from Landsat 8 OLI could be effectively used for predicting PM2.5 in a city scale.
Comparative Study on Performance of SOFC/GT and SOFC/SCO2 Turbine Combined Cycle System
Authors: Xingsheng Lao , Mengran Liao , MaCan  , Chunhui Dai 
Published: December 2020

Abstract
In order to compare and study the performance of SOFC/SCO2 cycle and SOFC/GT cycle, the efficiency of SOFC/GT cycle under the same working temperature and the middle temperature and low temperature SOFC/SCO2 combined cycle system was compared and analyzed. The cycle parameters of the non-pressurized SOFC/SCO2 system at the highest efficiency are retrieved by genetic algorithm. The research results show that the efficiency of the SOFC/SCO2 combined cycle is about 5% lower than the efficiency of the SOFC/GT cycle under medium temperature conditions. Under low temperature conditions, the efficiency of the SOFC/SCO2 combined cycle is about 4% higher than the efficiency of the SOFC/GT cycle in all operating conditions.
A simple analysis of the relationship between Taiyuan pollutant concentration and time
Authors: Cai YiLuo , Wang ChuHan 
Published: December 2020

Abstract
In the context of today’s growing emphasis on environmental issues, the paper analyses 2018 pollutant data from eight sites in Taiyuan. The relationship between PM2.5 concentration and time (season, month, week) was analyzed by the R language, and the reason for PM2.5 concentration variation was inferred. Air Pressure, wind speed, precipitation, and vehicle restrictions all affect the concentration of pollutants.
Study on the control strategy of chaotic oscillation of synchronous generator based on the linear feedback adaptive fuzzy sliding mode control
Authors: ZhuoqunZhao  , HongjunWang  , HuiZhao  
Published: December 2020

Abstract
In the case of periodic load disturbance, the chaos oscillation phenomena may be caused by synchronous generator to threaten the safety operation of the network. In order to solve this problem, this paper presents the strategy on the control of linear feedback adaptive fuzzy siding mode. Under the action of the controller, the system output track the desired trajectory, and the fuzzy control rules are used to suppress the high frequency chattering in conventional sliding mode controller. The theoretical analysis and simulation results show that the designed controller can effectively control the power system oscillation, and it has certain robustness.
Comprehensive Evaluation of Power Grid Security and Benefit Based on BWM Entropy Weight TOPSIS Method
Authors: Zhao Lang , Li Hui , Wang Zhidong , Peng Dong , Xue Yawei , Ai Xin 
Published: December 2020

Abstract
With the gradual integration of various forms of energy, the energy utilization rate has increased and it also brings great challenges to grid evaluation. Therefore, the use of scientific and reasonable comprehensive evaluation method can provide effective help for the development of power grid. In order to solve the problem that the traditional single evaluation method is used in the comprehensive evaluation of power grid, resulting in too strong subjective awareness and lack of evaluation of the objective original data itself and uneven weight distribution, this paper proposes that Nash equilibrium solution is introduced into BWM entropy weight as the goal of coordination and optimization. In the method, the comprehensive weight is calculated, and the distance between the selected scheme and the ideal scheme is sorted by TOPSIS. This method combines all the information of objective data to balance the subjective and objective weight. Through this method, 16 indicators of safety and benefit in 25 provinces in 2017 of State Grid Economic Research Institute are analyzed, and the feasibility of this method is verified.
A Virtual Power Plant Load Curve Clustering Method Based on Improved K-means Algorithm and Its Application
Authors: Li Hui , Zhao Lang , Peng Dong , Wang Zhidong , Wang Xueying , Ai Xin 
Published: December 2020

Abstract
In view of how virtual power plants can effectively participate in power grid operation, a method of load curve clustering of virtual power plants based on principal component analysis reduction and aggregation level clustering and k-means clustering is proposed, and the application of clustering results is studied. Firstly, combined with the data obtained from the information physical network, the principal component analysis method is adopted to analyze the characteristics of different loads participating in the virtual power plant aggregation, so as to standardize the data and reduce the dimension. Then, the algorithm combining aggregation hierarchical clustering and k-means clustering is used to cluster all load output curves participating in the aggregation, to obtain load curve clusters of the same class and find out the clustering center. Finally, the clustering results are analyzed, and the corresponding evaluation system is established. Through comprehensive evaluation, appropriate load combinations are selected to participate in the virtual power plant aggregation.
Study of Smoke prevention and Exhaust System for High-rise Buildings
Authors: Kunhua Xiao 
Published: December 2020

Abstract
Nowadays, the smoke prevention and exhaust system has not been effectively taken seriously, but smoke in fire disasters have become an important cause of death. In this paper, some problems still exist in smoke prevention and exhaust system will be concluded including design inspection and maintains. Meanwhile, a new method of calculating volumetric flow rate of smoke exhaust in high-rise building will be shown. The results show that the the existing prevention and exhaust systems in high-rise buildings have some defects and need to be upgraded. Outdoor wind in high-rise buildings is an important effect of fires. Some significant and easily ignored aspects of inspection and maintains will also be summarized.
Research on well pattern optimization for secondary development of new layer system in old oilfield
Authors: Xia Wang , Qihao Hu , Lifang Jiao , Fan Zhang , Xianqiu Chao , Yuhong Du , Yuyang Han 
Published: December 2020

Abstract
The Es3 reservoir of Jin45 fault block has been developed for many years, and now it is faced with problems such as high water content, serious casing damage. In order to change the current development status of Jin45 fault block, the Es2 reservoir is put into development which located in the upper part of Es3 reservoir. The well pattern direction, well pattern form and well pattern density of Es2 reservoir are optimized by various methods in this study. On the basis of Es2 reservoir well pattern optimization study, the new well pattern of Es2 reservoir and the old well pattern of Es3 reservoir are comprehensively considered and compatibly adjusted. While the new well pattern is put into development, the injection-production system of the old well pattern is improved by using the new drilling wells, and the potential remaining oil is exploited, which lays a foundation for the efficient development of the old oilfield.
Experiment Analysis of CAN-FD Factors
Authors: Xu Ye , Cheng Ximing , Ruan Xusong 
Published: December 2020

Abstract
With the growing number of onboard ECUs, the load of classical CAN (Controller Area Network) is aggravated to produce transmission delay issue. A new protocol CAN-FD (Controller Area Network with Flexible Data-Rate) was presented by the BOSCH company to meet the high speed and real-time data exchange needs of the intelligent vehicles and ITS (Intelligent Transport System). For the vehicle electronics, the CAN-FD data network is still growing up. In this paper, the classical CAN and CAN-FD in protocol are compared through experiments. Results show that: (1) the terminal resistors have more effects on the CAN-FD than the CAN; (2) the bit rate of the CAN-FD can be ten times of that of the CAN; and (3) the data transmission efficiency of the CAN-FD network is affected by both the bit rate and the data length. Additionally, the physical network configuration takes decisive effect on the minimum frame interval of the CAN-FD frame.