bluuebunny/crossref_metadata_2025_split huggingface dataset:
Path Planning for Mobile Robot in 3D Environment Based on Ant Colony Algorithm
Authors: Wenrui Fan 
Published: August 2021

Abstract
This paper introduces the ant colony algorithm to the path planning of mobile robots, and explores the optimal path solution. The definition of path planning was studied firstly. Then modelling method of path planning was discussed. Also, current research status of three-dimensional path planning at home and abroad he existing problems of 3D path planning was analyzed. These basic theoretical knowledge have laid the foundation for the research work of this paper, and we then modelled the three-dimensional terrain environment, and used MATLAB software for simulation experiments to implement the ant colony algorithm to plan the robot’s three-dimensional terrain path, and finally performed fuzzy reinforcement learning method based on ant colony algorithm to find the optimal path for the mobile robot.
Digital Media Image Recognition Method Based on Improved Fuzzy C-means Clustering Analysis
Authors: Yang Yanyan , Wang Zhiping , Liu Kecheng , Zhu Huijun 
Published: August 2021

Abstract
Digital media plays a more and more important role in people’s life. In recent years, as an important part of digital media, image is widely used. It has become a hot spot in image information processing to determine the similarity between images by calculating the perceptual hash. This paper mainly studies the intelligent traceability of digital image based on improved fuzzy c-means clustering analysis. This method can improve the information truth degree identification of data image, which can assist the development of data image information detection and recognition system based on improved fuzzy c-means clustering analysis. Firstly, this paper analyzes the value of image recognition technology in streaming media environment. For the current streaming media image recognition technology, the main application areas and demand state are described. Then, from the perspective of technology, several main technologies in this field are discussed, and the digital image technology of improving fuzzy c-means clustering analysis is analyzed and constructed. Experimental results show that the method can improve the efficiency and accuracy of digital media image recognition. This method has a certain reference value to promote the development of digital image analysis technology.
Hierarchical feature similarity integration method for data sets based on deep learning
Authors: Xiaoli Yu 
Published: August 2021

Abstract
Under the background of the rapid rise of open-source software and the gradual popularization of various software development tools, a large amount of development activity data has been accumulated on the Internet. In the process of using these data to construct data sets, due to their poor traceability and narrow application scope, the quality of data in development activities is not high and the accuracy of analysis results is not high. The application of the hierarchical feature similarity integration method of data sets can make the multi-version and multi-level development smoother and more orderly. In this paper, a hierarchical feature similarity integration method based on hierarchical deep learning is proposed for data sets. Firstly, the dynamic mesh partitioning method is used to divide the sparse and dense regions in the space, which reduces the scale of data detection and shortens the execution time of detection. Then, through the hierarchical deep learning process, the professional knowledge and the distribution information of data attribute value are fused to realize the detection of discrete data in the database. Experimental results show that this method can accurately complete the detection of discrete data in the database in a relatively short time, and has more application advantages than traditional methods.
Research on Performance Monitoring System and Damage Identification Method of Civil Engineering Structure
Authors: Pan Haozhe , Yan Xingpei 
Published: August 2021

Abstract
In order to meet the increasing living needs of urban residents, China’s construction industry began to promote super high-rise buildings and long-span structures in an all-round way, and strengthened the research on performance monitoring and damage identification of civil engineering structures, so as to master the basic performance of structures and put forward effective solutions to the problems existing in their practical application. On the basis of understanding the current monitoring problems of civil engineering structures, according to the artificial neural network method of structural damage identification based on the statistical characteristics of structural dynamic response, this paper makes a concrete research from two aspects: single damage and multiple damage.
A double network structure anti-jamming algorithm based on deep reinforcement learning
Authors: Wang Yifan , Liu Xin , Wang Mei 
Published: August 2021

Abstract
At this stage, when dealing with intelligent jammer with environmental cognition, most anti-jamming methods only consider how to maximize avoidance of it. However, the user’s previous waveform and frequency actions have been leaked. As the intelligent jammer continues to learn, the performance of anti-jamming will decline. Existing literature has proposed the idea of hidden anti-jamming. The user uses rational communication action-making to prevent the jammer from obtaining the information of the user so that the jammer cannot target the user for jamming, but its model is relatively simple and cannot cope with complex jamming types. This paper designs a kind of decision related judgment module between jammer and user based on Generative Adversarial Networks (GAN), which uses the environment state received by the user to reversely infer the user’s decision whether to avoid jammer’s sense. Specifically, the neural network is used to fit the environment state under known user information, and calculate the loss between it and the real environment state to evaluate whether the user’s decision is to avoid jammer’s sense. Then, this paper proposes a deep reinforcement learning algorithm with double-network structure, which can deal with various types of complex jamming while ensuring anti-jamming performance. The final simulation results show that the improved deep reinforcement learning algorithm proposed in this paper can improve the anti-jamming performance, achieve hidden anti-jamming, and have a wider range of applications.
Parallel performance analysis of nonlinear equations algorithm based on hybrid genetic algorithm
Authors: Yang Yunwen 
Published: August 2021

Abstract
For a long time, people have done a lot of research on nonlinear equations in theory and numerical calculation. In this paper, the basic theories and methods of genetic algorithm and traditional algorithm are expounded, and the advantages of genetic algorithm and quasi-Newton algorithm are analyzed, thus a new hybrid genetic algorithm for solving nonlinear numerical problems is proposed, and the effectiveness of the algorithm is verified by numerical examples. The hybrid algorithm gives full play to the group search and global convergence of genetic algorithm, and effectively overcomes the initial point sensitivity problem of classical algorithm At the same time, the classical algorithm is introduced into genetic algorithm for local search, which overcomes the shortcomings of slow convergence speed and poor accuracy of genetic algorithm. The algorithm in this paper provides an effective way to solve nonlinear equations from another angle.
Research on Online Autonomous Learning Support System of Advanced Mathematics Based on Feature Extraction Algorithm
Authors: Su Li 
Published: August 2021

Abstract
One of the key problems in researching and developing online autonomous learning support system of advanced mathematics which adapts to learners’ personality characteristics is to acquire learners’ characteristics. According to the theory of teaching structure and network teaching mode, based on analyzing the syllabus and teaching materials of higher mathematics, this paper puts forward the overall goal and design principle of the system, redesigns the teaching expression form, and designs an online autonomous learning support system of higher mathematics based on feature extraction algorithm. In the design of the system, the teaching idea of taking teachers as the leading factor and students as the main body runs through, so that students can arrange their own study plans, actively explore knowledge, actively participate in interaction and get feedback in time, thus improving the learning effect.
Big data cloud platform server load balancing algorithm based on improved chaotic partition algorithm
Authors: Xiang Hao , Zhang Ting , Li Zhewen 
Published: August 2021

Abstract
Due to the heterogeneity of big data cloud platform and the uneven distribution of data between cloud servers, when cloud server cluster processes a large number of tasks, the node load is often uneven. To solve this problem, a load balancing algorithm based on improved chaotic partition algorithm for big data cloud platform server is proposed. According to the statistics of the average resource consumption of various services provided by the cluster, combined with the running time and resource occupation of tasks on the server, the total remaining task load of the server at a certain time point is predicted, so as to obtain the actual task load status of the node, and correct the task load in time. Experiments show that the load balancing algorithm of big data cloud platform server based on improved chaotic partition algorithm can effectively balance the load of multi task heterogeneous cloud servers, and has high feasibility, Then, based on this improved load balancing algorithm, we can also extend it to the application of multi-objective algorithm, such as robot path planning, target allocation scheduling algorithm and so on. There will be similar and reasonable performance compared with the same period last year.
Research on Network Intrusion Detection Method Based on Deep Learning Algorithm
Authors: Liao Xinhai , Xie Jianguo 
Published: August 2021

Abstract
Information security is very important in enterprises. Under the tide of modern network informationization, especially intrusion detection is facing great challenges. The rise of technologies such as big data and artificial intelligence, on the one hand, helps to strengthen information security, on the other hand, it also brings great challenges to information security. Everything has two sides, and the Internet is no exception. While the network has brought us a richer and faster life, the problem of network security has become increasingly prominent, and network security risks pose new challenges to the fields of politics, economy, culture, national defense, ecology and society. The active defense strategy using intrusion detection technology can actively discover attacks when they occur or attempt to attack, realize real-time response, and provide real-time protection for network systems. This paper starts from the field of intrusion detection and combines deep learning technology to design an efficient and intelligent intrusion detection model which can be used in the field of network intrusion detection.
Automatic keying algorithm for multi-category target recognition
Authors: Mao Liping 
Published: August 2021

Abstract
In this paper, through an in-depth study of the automatic keying algorithm for target recognition and using multi-class algorithms for its analysis, a saliency detection model based on the hypercomplex Fourier transform is proposed, which can quickly search for information related to the current task requirements. The problem of sample imbalance in deep neural network training exists, the module is used many times to fuse multi-scale features, the loss function uses weighted cross-entropy loss, and the weights are determined according to the proportion of samples in the training sample, which can solve the problem of the model tends to fit the category with more samples. After analysis, the proposed hyperspectral image fast feature enhancement algorithm based on guided filtering can effectively solve the problem of “the same object, different spectrum”, and the classification accuracy of small sample high-dimensional data is improved greatly. At the same time, the complexity of processing high-dimensional data such as hyperspectral remote sensing images is greatly reduced. The experimental results show that the processing time of the proposed fast feature enhancement process for hyperspectral remote sensing images in this paper decreases than that of the direct use of guided filtering.
Graph algorithm optimization techniques for high-throughput computers in weakly supervised scenarios
Authors: Mao Liping 
Published: August 2021

Abstract
In this paper, a weakly supervised recognition model is used to provide approximate position constraints for object transformation in the source and target domains, and to guide the generator to generate images that differ less from the real ones. The cross-modal synthesis technique is incorporated to take advantage of the data differences between different modalities to constrain the mapping functions, thus ensuring that the learned mapping functions are always performed on the paired data. The full version of the proposed method achieves a 3.6 % performance improvement compared to the benchmark network. Richly controlled experiments demonstrate the effectiveness of each improvement. It is found that the intrinsic correlation of query graphs provides complementary information for better performance of semantic segmentation with few samples, and the proposed network structure in this paper effectively exploits this information.
Design of Networked Intelligent Translation System Based on Machine Learning Algorithm
Authors: Hong Liu 
Published: August 2021

Abstract
China’s social and economic development is relatively rapid, and China’s opening to the outside world is further expanding. Under this background, the demand for foreign language professionals is also expanding. This paper designs a networked intelligent translation system based on machine learning algorithm, and proposes a cross-language information extraction method based on bilingual word representation. The learning of bilingual word representation can be divided into two stages: unsupervised and supervised. Capturing Chinese and English bilingual semantic information. The cross-language information extraction method based on machine learning algorithm reduces the impact of translation errors and language gaps on cross-language classification performance, obtains effective bilingual semantic information and annotation information, and improves the cross-language information extraction performance. The test results show that the designed automatic English translation system can effectively and quickly realize intelligent English translation of memory-assisted long characters, with high data recall rate, good accuracy and reliability, and good system compatibility, which is worthy of popularization and practical application.
Application of Computer Control System in Electrical Automation
Authors: Wang Xinxiang 
Published: August 2021

Abstract
With the improvement of information technology, China has continuously promoted the development of computer control system of electrical engineering and electrical automation in the current development process. In enterprise production, computer technology can be integrated into electrical engineering and electrical automation to realize real-time monitoring of controlled objects. Electrical engineering automation belongs to the field of modern electrical information, which is widely used in military, aerospace and industry. However, due to the late formation of China’s industrial system, there are still some problems in electrical engineering automation, resulting in serious energy consumption problems. In order to improve the application level of electrical automation control system and create greater benefits for enterprises and society, it is necessary to strengthen the application research of electrical engineering and automation computer control system. Based on the application status of computer control system in electrical automation, this paper discusses the application strategy of computer control system in electrical engineering and electrical automation to promote the further development of electrical engineering technology in China.
Research on Improvement of Computer Software Technology Based on Internet Technology
Authors: Luo Weizhang , Lin Jie 
Published: August 2021

Abstract
The rapid development of computer technology is an important symbol of human development and progress. With the continuous improvement of informatization, modern society has entered the era of big data. People’s daily life, work and study are inseparable from the assistance of computer software technology, and the social progress, the development of science and technology, and the trade of enterprises are also inseparable from the support of computer software technology. Based on the background of Internet era, this paper focuses on the analysis of the concept, classification and application of computer software technology in the current environment, and explores the development direction and positive influence of computer software technology. The application process of computer software development technology needs to find out the important factors that restrict the development of computer software development technology according to the actual situation, and constantly improve and innovate, so that computer software development technology can meet the needs of the development of the information age, and better provide safe and reliable technical support for China’s economic development and social progress.
Development and design of three-dimensional display system of visual design works based on virtual reality technology
Authors: Zhang Kai , Wang Yu 
Published: August 2021

AbstractExhibition design involves many fields, including many disciplines, such as design psychology, visual communication, ergonomics, etc. Therefore, there are many factors to be considered in the design process, that is, to transform ideological intentions, display information and design views into images that can be received visually. Virtual reality technology is a computer simulation technology that can create and experience a virtual world. It uses computers to generate an interactive 3D dynamic scene, and the simulation system of its physical behavior can immerse users in the environment. In this paper, the 3D model is combined with the physical image, and the visual design works are displayed in a virtual way by using Cult3D technology and virtual reality, so that the visual design works and their scene environment to be displayed can be better presented to users in 3D form, and the realism and visual beauty in the process of product browsing experience can be enhanced through humanized interactive design and artistic interface design. In the development process of the three-dimensional display system of visual design works, the cost accounting and the actual operation effect of the system have been considered, which has met the actual needs of users and has certain theoretical and practical value.
Construction and experimental research of multifunctional hybrid powertrain test bench
Authors: Yan Yi , Chen Bin , Liu Zhi Yang , Huang Bo 
Published: August 2021

Abstract
With the development of hybrid electric vehicles, the demand for test benches is becoming more and more vigorous. Based on the traditional engine test bench, this paper builds a multifunctional hybrid powertrain test bench by matching appropriate equipment such as battery simulators, power analyzers, fuel consumption meters, and air flow meters. The test bench has the characteristics of modularization, flexibility, and multi-function. It can be used for testing single engine, single generator and hybrid power system. Finally, the range extender produced by a domestic manufacturer was used as the test object, and the endurance test was carried out on the modified test bench. The test further verified the reliability and feasibility of the multifunctional hybrid powertrain test bench.
Research on Application of Computer Technology in the Optimization of Department Information System
Authors: Shen Haohui , Wang Juan 
Published: August 2021

Abstract
Aiming at the problems of weak financial management foundation, lack or failure of internal financial accounting management, etc., the characteristics of financial management of SMEs are analysed. The article develops a reasonable financial enterprise management system, which can promote the long-term development of the enterprise. The graphical user interface developed based on SWT realizes the main functions of enterprise financial management. Practice shows that the system is not only easy to operate, but also has a friendly interface. It is a flexible, reliable, fully functional, and practical information management system.
Research on Advantages and Difficulties of Implementing Full-cost Comprehensive Information System in Power Engineering
Authors: Wen Yanping , Su Xiaoxue , Zhang Rong , Wen Wei , Wang Zheng 
Published: August 2021

Abstract
The article analyses the current status and existing problems of the current pricing model of electric power projects in our country, introduces the advantages of the full-cost comprehensive unit price method, and demonstrates that the implementation of the full-cost comprehensive unit price method for project pricing is simple, operability, and meets market needs. The market pricing principle is more conducive to the reasonable determination and effective control of the project cost. Finally, it expounds the difficulties that need to be studied to solve the current implementation of this model, and proposes corresponding countermeasures. At the same time, we applied the full-cost comprehensive unit price to actual cases, and demonstrated the effectiveness of the full-cost comprehensive unit price in power engineering management through modelling and simulation.
Large-Scale Scientific Research Instrument Resource Information Sharing Platform through O2O Mode
Authors: Bao Jidong , Su Hailong , Yin Xinhong , Meng Jie , Liu Fei 
Published: August 2021

Abstract
Through the collection and integration of scientific instrument resources and scientific research services across the province, a scientific instrument public service system based on the O2O model will be constructed. The system takes the one-stop retrieval of scientific and technological resources as the hub, and provides accurate and convenient intelligent services for scientific and technological information for universities, scientific research institutes, key laboratories, high-tech enterprises, incubators and other units, realizing the co-construction and sharing of scientific instrument resources, Improve the utilization rate of scientific and technological resources, effectively improve the level of comprehensive sharing and efficient use of scientific instruments.
Design and Research of Wuhan Urban Railway Network Simulation Calculation Information System Utilizing Big Data
Authors: Zou Han , Liu Shujun 
Published: August 2021

Abstract
Based on the big data-assisted algorithm, the paper uses the dynamic relationship data of railway passenger flow as a research case, adopts the urban network chain model, and uses the mobility and agglomeration of railway passenger flow between cities as the research entry point to analyse the network connection strength of provincial cities and spatial organization structure characteristics. At the same time, it puts forward the idea of using Wuhan’s rich railway resources as the framework of urban railway network passenger flow intensity simulation calculation system, demonstrates the necessity and feasibility of its construction, and puts forward an implementation plan based on the characteristics of the railway network and urban development for the reference of relevant decision makers.