bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Blocking Time Problem Based on Fuzzy Comprehensive Evaluation Method
Authors: Dai Peng 
Published: April 2021

Abstract
In this paper, we use the first-level fuzzy comprehensive evaluation, entropy method and other algorithms to establish a correction optimization theory based on GPS measurement speed inaccuracy, which is aimed at the problem of inaccurate estimation of vehicle speed when GPS speed is slow. A first-level comprehensive fuzzy evaluation model, an entropy value estimation weight model and a modified optimization model for calculating the maximum traffic volume are constructed. The relationship between the evaluation index data is skillfully used to solve the problem, and the blocking time at different peak periods is obtained. The relationship between the four factors affecting the evaluation criteria, the weighting value of each factor in the degree of congestion and the. actual time of the model after optimization, and finally the perfect prediction of the GPS to measure the speed of the vehicle is too slow. The deviation rate of the predicted value will give the relationship between the actual predicted value and the predicted value
An Efficient Heuristic Algorithm for Solving 0-1 Knapsack Problem
Authors: Yang Hong , Guo Xiong 
Published: April 2021

Abstract
The model for 0-1 knapsack problem based on greedy strategy and expectation efficiency has some advantages, e.g., quick convergence and low complexity, but it also inherently exists some limitations to be enhanced and improved, such as the restricted greedy and the overmuch calculation on expectation efficiency. To this end, an efficient algorithm is proposed to optimize the previous model. At first, the greedy degree is maximized, that is, some items are permanently loaded into knapsack in advance as many as possible. Then, the conventional expectation efficiency model is improved greatly, at the same time, the number of calculations with respect to expectation efficiency is decreased by ignoring some unnecessary items. Compared to the previous algorithm, the experimental results reveal that the proposed optimization algorithm has the significant advantages in time.
Research on Commodity Recommendation System Based on Deep Learning
Authors: Qian Chenyue , Jin Yanjuan , Teng Xiaobing 
Published: April 2021

Abstract
The traditional matrix factorization model cannot effectively extract the features of users and items, but the feature information can be extracted well based on the deep learning model. At present, the mainstream recommendation algorithms based on deep learning only make recommendation prediction in the form of the product of neural network output or item features and user features, and cannot fully mine the relationship between users and items. Based on this, this paper proposes a recommendation algorithm based on the combination of text convolution neural network and singular value decomposition (Bias SVD) with biased terms. The text convolution neural network (Text CNN) is used to fully extract the feature information of users and items, and then the singular value decomposition method is used to make recommendations to deeply understand the document context information and further improve the accuracy of recommendation. The algorithm is widely evaluated and analyzed on two real data sets of MovieLens, and the accuracy of recommendation is obviously better than that of ConvMF algorithm and mainstream deep learning recommendation algorithm.
The Intelligent Bookcase System Based on RFID Positioning Technology
Authors: Du Xiaolong , He Menghan 
Published: April 2021

Abstract
This paper introduces a kind of intelligent bookcase system based on radio frequency positioning technology, and introduces a kind of intelligent bookcase system by discussing the misplacing of books in the library in reality. This paper also introduces the related technology of intelligent bookcase system, and proposes and designs an intelligent bookcase system.
Smart Bookcase Based on Image Recognition Technology
Authors: Liu Jiaxin , Song Wei 
Published: April 2021

Abstract
In order to improve the efficiency of readers’ book borrowing and book management, research and create the intelligent bookcase, which is based on image recognition technology, supplemented by WeChat applet. Through the research on the relevant background and the technology used, we have inspired an intelligent bookcase based on image recognition technology, and made a prospect.
Players’ Value Prediction Based on Machine Learning Method
Authors: Zhang Daokang , Kang Caixin 
Published: April 2021

Abstract
It is important to predict football players’ value, especially during transfer period. This paper uses the player information and value data of the game FIFA 18 as data source. It is able to realize the prediction of its players’ best positions and values. After reducing the dimensionality of the value prediction model, a cluster analysis on the player’s position is introduced, and then grid search method is adopted to adjust the Xgboost parameters, Finally, Xgboost method is used to predict the player’s worth. The experimental results show that certain accuracy is achieved, but t there is still room for improvement in the accuracy of prediction. Discussions based on experiment results are made.
Research on Automatic Recognition of Pointer Meter Reading Based on Deep Learning Algorithm
Authors: Yan Xianwei , Wei Lai , Li Jing , Jia Gang , Yang Juan 
Published: April 2021

Abstract
With the rapid development of computer technology and intelligent high-performance hardware, deep learning algorithm plays an increasingly important role in society. The development of automatic identification method of instrument and instrument based on deep learning can effectively improve the working efficiency of the basic power grid operation and maintenance personnel, avoid personnel approaching the high-risk operation area, and ensure the continuous monitoring of the readings of key instruments all day. In this paper, a recognition algorithm of pointer types circular instrument based on deep learning algorithm is proposed. Gaussian filter and binary method are used to achieve better recognition effect, which lays a good theoretical foundation for further practical application.
Bank Loan Strategy Based on Evaluation and Decision Model
Authors: Ge Yiyuan , Song Haoran , Li Bingkuan 
Published: April 2021

Abstract
In real life, in the face of small and medium-sized enterprises lacking mortgage assets, banks usually provide loans to enterprises with strong strength and stable supply-demand relationship according to credit policies, transaction notes information of enterprises and influence of upstream and downstream enterprises, and can give preferential interest rate to enterprises with high reputation and small credit risk. In order to better meet the application of the model in real life, the enterprise loan mode is introduced, and the risk assessment of each loan mode is carried out according to the actual situation. Finally, the fuzzy neural network model is introduced. The enterprise loan mode and three secondary indicators are taken as the input of the fuzzy neural network. Finally, a three-level index: loan risk assessment is obtained. Using Python program to preprocess the data, the original indicators in the given materials are extracted as the first level indicators, and then on the basis of the first level indicators, the main factor analysis and other methods are used to analyze the characteristics and scoring of the second level indicators. Then, the entropy weight is established to obtain the higher-level index loan tendency, and the loan propensity and enterprise reputation are used as parameters to establish the decision-making Model, step by step to get the bank’s quota allocation, interest rate, and finally get the bank allocation plan. In order to supplement the unknown data, this paper uses the known information to forecast the whole process of the unknown quantity, and then uses the data to forecast. First of all, it forecasts whether the default occurs, adds the predicted value to the whole eigenvalue, then forecasts the reputation rating, and finally completes the reasonable supplement of location data. TOPSIS model, SPSS software simulation machine learning, Fisher discriminant analysis
RETRACTED: Cloud Intelligent Parking Management System Based on Internet of Things Technology
Authors: Yao Ru , Yang Jinhua , Liu Meizhen 
Published: April 2021

Abstract
In recent years, with the rapid development of the national economy, the penetration rate of domestic private cars has risen rapidly. There are too many cars with fewer parking spaces, so many people choose to park their cars on roads. It has caused traffic jams and brought security risks, finally it puts a huge pressure on vehicle management. It requires more parking lots and more effective and convenient parking management and operation methods to improve the service level of parking lots [6]. It is necessary to design an intelligent parking system based on the Internet of Things technology and cloud platform to achieve the highest utilization of space resources and the largest allocation rate of personnel deployment. The intelligent parking lot management system of the Internet of Things is designed and developed to meet the goals of enterprise informatization management and efficient operation and implementation. The web platform conducts the joint operation of users and administrators to realize online reservation, parking at any time, and online payment for car pickup at any time.
A Rate Control Algorithm Based on Psnr-Hvs For Hevc
Authors: Du Yunfei 
Published: April 2021

Abstract
HEVC/H.265 is the latest video coding standard. It has a higher compression rate under the requirement of ensuring video image quality. However, the currently used video image quality evaluation indicators cannot better fit the subjective perception of the human visual system and cannot effectively allocate target bits and update parameters so that results in reduced video image coding quality. This paper proposes a CTU-level rate control algorithm based on the image quality evaluation factor PSNR-HVS which is more in line with the perception of the human visual system. According to the PSNR-HVS of the CTU as the weight, the target bit is assigned to the current frame to be encoded. Then calculate the actual bits and PSNR-HVS after encoding the current CTU to update the parameters of the CTU at the same position in the next frame. The experimental results show that compared with HM16.20, the subjective performance of the video after encoding is improved, and the image details are more delicate, BD-Rate = -4.6, BD-PSNR-HVS = 0.17, ΔT = 4.6%.
Remote Sensing Image Zero-Watermark Algorithm Based on Bemd
Authors: Xing Siming , Cheng Zhilin , Ji ChunYu , Chen Jiaying , Qi Luyu 
Published: April 2021

Abstract
In order to solve the problem of information security when acquiring and disseminating images and improve the performance of digital watermarking, this paper proposes a remote sensing image zero-watermarking algorithm based on Bidimensional Empirical Mode Decomposition (BEMD). Initially, to perform this algorithm the DCT transform is used to extract the characteristic image of the host image. In the next step, BEMD decomposition on the grayscaled image need to be performed. The number of watermarks embedding layers is determined according to the NC value of the original image without the i-th IMF layer and the original image. The information matrix of the watermark embedding layer is XORed with the characteristic image to obtain the image embedded with the watermark. The extraction of the watermark image is the XOR result of the first XOR and the attacked image. After the watermark is embedded, the image is processed with noise, enhanced processing attacks, etc., and the NC value of the extracted watermark and embedded watermark is mostly above 0.9. The experimental results show that the watermarking algorithm proposed in this paper has better anti-attack performance, stronger invisibility and robustness.
Analysis and Research on Influencing Factors of University Teachers and Students Management Based on Computer System
Authors: Wang Ming , Ni Ziqi , Zhou Xiaoxi , Shi Xiaoxue 
Published: April 2021

Abstract
Teacher computer application is the responsibility and mission of colleges and universities, whether Internet university teachers are willing to contribute much to student management and social progress. It is the responsibility and mission of colleges and universities to do well in Internet university teachers to perform their duties, play a good role, and establish moral education the important driving force and source of the key role of cultivating people are directly related to the healthy development of college student management. With the continuous development of technology. It is a basic skill for university teachers to master computer applications. The paper analyzes the most influential factors of university construction on student management through analysis and its own management experience, and explores an effective way and influencing factors to realize teacher and student management with the help of app management software downloads on the university Internet. The influencing factors in various aspects of student management are analyzed.
Application of artificial intelligence in computer network security
Authors: Zhang lei , Chen Zening , Yang Shufeng 
Published: April 2021

AbstractAt present, artificial intelligence technology is more and more common, and has a very broad development prospect. Nowadays, in people’s daily work and life cannot do without artificial intelligence devices, such as intelligent home appliances, intelligent society greatly improves the quality of life and work efficiency of people. At the same time, with the continuous improvement of the development level of information technology, the application of artificial intelligence technology has gradually expanded to all walks of life in the society, and plays a positive role in promoting and value, improving people’s lives, changing society, and gradually changing the world. In the computer network technology, the full use of artificial intelligence technology, can promote the computer network function more rich and powerful, improve the efficiency of the use of computer network.
Research on Multi-sensor Path Planning Based on Corridor Environment
Authors: Wang Fei , Song Ruilan , Zhao Qingshuai 
Published: April 2021

Abstract
Aiming at the problems of traditional A* algorithm with many inflection points, large turning angles and not adapting to dynamic environment, the current optimized A* algorithm is analyzed and researched. Designed and built a wheeled robot platform with 4WD trolley as the carrier, single-line lidar Rplidar_A3, depth camera Kinect V2 and ultrasonic sensor TeraRanger one as environmental detection sensors. The platform conducted simulation research on the three optimized A* algorithms in the indoor corridor environment, compared the pros and cons of the planned paths, and set up path planning experiments based on the static network improved A* algorithm and dynamic obstacles and static Obstacle avoidance experiment. Experiments prove that the trajectory planned by the improved A* algorithm based on the static network contains 7 inflection points, which is relatively smooth, takes 49.8s and can effectively avoid dynamic and static obstacles.
Research on Educational Information Management System Based on Computer Big Data
Authors: Zhao Xuemin 
Published: April 2021

Abstract
Aiming at the problem of computer network courses with more teaching content and rapid knowledge update, the paper builds a computer network adaptive learning system by collecting learning behaviour data in the education process and using the learning analysis technology of big data. The six modules of prediction and intervention can push learning content in a targeted manner, give feedback on learners’ learning effects in time, and recommend next learning strategies, so as to achieve the effect of teaching students in accordance with their aptitude and cultivating students’ independent learning ability.
Research on the Recent Development of Information Management Technology in the Field of E-commerce
Authors: Zhang Yuxiao 
Published: April 2021

Abstract
As e-commerce has become the new engine of my country’s economic development, information management technology has increasingly become the focus of various e-commerce platforms. Today’s information management technologies are divided into two categories: enterprise-oriented and user-oriented information management technologies based on their use objects. Specifically, it includes personalized information service technology, user query intention recognition technology, and e-commerce information cross-platform retrieval technology. This article elaborates on the basic principles or framework of the above-mentioned technology, analyzes the development and application of information management technology in the field of e-commerce, in order to promote the development of e-commerce and information management technology to promote each other and make progress together.
Research on The Protection System of Urban Garden Plants Based on Time-Space Analysis
Authors: Cheng Xiao , Hong Xiaoling 
Published: April 2021

Abstract
The paper selects a garden as a typical object to study urban garden plants, and uses methods such as video statistics, digital camera record analysis, manual counting, and questionnaire survey statistics (CTVM) to analyse the laws of garden plants in different time periods Based on the analysis and research, a mathematical model was established to explain the temporal and spatial behaviour of garden plants, so as to evaluate the landscape planning of urban gardens and provide a basis for studying the landscape planning of urban gardens. At the same time, the paper designs a web-based urban garden plant protection management system to improve the level of intelligent management of urban gardens.
Improved SFLA Algorithm with Hybrid SA Strategy for Multi-Objective Reactive Power Planning Optimization of Distribution Network
Authors: Zhang Meilun , Zhang Jin , Xu Maoda , Hao Wenbo 
Published: April 2021

Abstract
Aiming at the characteristics of high target dimensionality, strong nonlinearity and complex constraints of distribution network reactive power optimization problems, this paper proposes an improved shuffled frog leaping algorithm based on SA strategy (ISFLASAS) to solve the problem. Firstly, the algorithm uses the global optimization capability of SFLA to detect the optimal solution, and improves the standard SFLA. Incorporating a reciprocal strategy during population initialization to improve the uniform distribution ability of the initial solution and speed up the search for the optimal solution. Secondly, using the local escape ability of the SA strategy, in the later stage of the SFLA calculation, the SA strategy is assisted to jump out of the local optimum with a certain probability to improve the global detection ability. Finally, the IEEE 33-node system is used to simulate and analyze the proposed model algorithm to verify the proposed control strategy.
Research and Application of Facial recognition Algorithm in Audit Investigation
Authors: Wang Hairong , Li Weibo , Wan Quan , Yan Hua , Xiang Rui 
Published: April 2021

Abstract
Aiming at the application scene of face image recognition in audit investigation, firstly, a face data set with corresponding environmental interference is simulated to increase the diversity of data; in the preprocessing stage, the improved method of adaptive histogram illumination balance and simulated glasses covering is used for image enhancement; in the model training stage, an optimal weight re overloading model training algorithm is proposed. The experimental results show that the accuracy, robustness and efficiency of face recognition in the application scene are improved by the improvement of image enhancement preprocessing and the model training of optimal weight reloading.
Review of 3D reconstruction technology of UAV aerial image
Authors: Zhang Zhiping 
Published: April 2021

Abstract
The construction of “smart city” is the development direction of major cities. It is an important part of the construction of “smart city” to reconstruct urban buildings, land and roads into three-dimensional models through three-dimensional reconstruction technology. In this paper, the image-based three-dimensional reconstruction technology and UAV path planning technology are described, hoping to use UAV aerial images for three-dimensional reconstruction, and carry out relevant research on the three-dimensional reconstruction of outdoor large-scale scenes.
A Fast Audit Doubt Finding Model
Authors: Wan Quan , Li Weibo , Wang Hairong , Yan Hua , Xiang Rui 
Published: April 2021

Abstract
In order to improve the audit efficiency and accuracy under the condition of big data, an audit doubt discovery model (CLOWF) based on an adaptive clustering outlier detection algorithm is proposed. The model first uses the slope ratio method to obtain the K value of the K-means++ algorithm, thereby effectively ensuring the clustering effect; At the same time, for the problem of slow pruning speed, a parallel calculation method for the data radius and centroid of each cluster is proposed and designed; Combined with the weighted local outlier factor detection algorithm to calculate the outlier factor, the data greater than the epsilon threshold of outlier is proposed as an indicator to determine the audit doubt. Through auditing application cases, comparing the local outlier factor detection algorithm and the cluster-based outlier detection algorithm, the results show that the execution time of the CLOWF model is the shortest and the accuracy rate is 97.3%.