UWB Positioning System Based on Genetic Algorithm

Xia, Bin; Zheng, Xianzhi; Zhang, Liye; Zhao, Lei

doi:10.4236/jcc.2021.94008

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…( 6) After the examination, the Japanese teacher can analyze the results of the examination, such as the score of each chapter and question type, and the score statistics of each class. ( 7) Users logging into the system, including system administrators, teachers, and students, should have different permissions [21]. Different login identities can be selected for system login: super administrator, administrator, teacher, and student.…”

Section: Experiments and Analysismentioning

confidence: 99%

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Dengqing

Zhangwei

2022

Wireless Communications and Mobile Computing

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In order to solve the problem of online inspection of students’ theoretical knowledge of Japanese, this paper further optimizes and adjusts the design of the online Japanese examination system and presents an online Japanese examination system based on genetic algorithm. Taking the Japanese test as the research object, on the basis of comprehensively analyzing the problems of slow test paper composition, low success rate, and low quality of traditional online test systems, an intelligent test composition model based on genetic algorithm is proposed, and the implementation process of genetic algorithm and the key steps are described in detail. The results show that the online Japanese examination system based on genetic algorithm can meet the needs of test paper generation in more complex situations. After a long time of operation and continuous improvement, the online Japanese examination system has obtained the adaptability of the best solution. The value of the fitness is 99.666667; when the fitness is at this value, the error of the question type score of the test paper is 0, the average difficulty error on the test paper is 0, and the error of the section test point distribution is 0.666667. This fully illustrates the stability and effectiveness of the Japanese online examination system, which can meet the needs of daily Japanese majors and improve the efficiency of Japanese teaching.

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Section: Experiments and Analysismentioning

confidence: 99%

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Dengqing

Zhangwei

2022

Wireless Communications and Mobile Computing

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“…During the UWB localization process, the localization problem is treated as an optimization problem. This problem is then commonly solved using genetic optimization algorithms [4] [5] [6] or particle swarm optimization (PSO) algorithms [7] [8] [9]. Genetic optimization algorithms are typically preferred because they offer stronger global convergence and are more robust.…”

Section: Introductionmentioning

confidence: 99%

An Improved Genetic Algorithm for UWB Localization

Zheng¹

2022

JCC

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The UWB localization problem can be mapped as an optimization problem, which can be solved by genetic algorithm. In the localization process, the traditional fitness function does not include the ranging information between tags, resulting in insufficient ranging information and limited improvement of the localization accuracy. In view of this, an improved genetic localization algorithm is proposed. First, a new fitness function is constructed, which not only includes the ranging information between the tag and the base station, but also the ranging information between the tags to ensure that the ranging information is fully utilized in the localization process. Then, the search method based on Brownian motion is adopted to ensure that the improved algorithm can speed up the convergence speed of the localization result. The simulation results show that, compared with the traditional genetic localization algorithm, the improved genetic localization algorithm can reduce the influence of the ranging error on the localization error and improve the localization performance.

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UWB Positioning Analysis and Algorithm Research

Zhang

Chu

et al. 2022

Procedia Computer Science

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UWB Positioning System Based on Genetic Algorithm

Cited by 4 publications

References 18 publications

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

An Improved Genetic Algorithm for UWB Localization

UWB Positioning Analysis and Algorithm Research

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