Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 6
1718-1724

Improved student psychology based optimization algorithm using hybrid strategy

Zhang Weia
Wang Yonga,b,c
Zhang Ninga
a. School of Artificial Intelligence, b. Guangxi Key Laboratory of Hybrid Computation & IC Design Analysis, c. Guangxi High School Key Laboratory of Complex Systems & Intelligent Computing, China Guangxi University for Nationalities, Nanning 530006, China
DOI: 10.19734/j.issn.1001-3695.2021.11.0630

Abstract

Aiming at the shortcomings of normal SPBO, this paper analyzed the psychological characteristics of students' learning, and put forward an improved student psychology based optimization algorithm(HSSPBO) using hybrid strategy. Firstly, it took the inverse value of student's test scores as the fitness value of the student, and took the fitness value of the best students in the class as the benchmark, and then divided the students in the class into four categories: the best students, the good students, the ordinary students and the students who tried random improvement. Secondly, it used the dynamic swi-tching probability of sine square and cosine square to balance global exploration and local development, so that the global exploration ability and local exploitation ability of the algorithm were improved effectively. Thirdly, by introducing Cauchy mutation strategy to change the local search step size, it improved effectively the local search ability of the algorithm and enhanced the ability of the algorithm to jump out of the local optimization. Finally, the HSSPBO algorithm used Lévy flight strategy to make the individual search step length more random and flexible, which effectively enhanced the individual's searching abi-lity, and further improved the optimization speed of the algorithm. Through simulation experiments of 12 benchmark functions and comparison with six optimization algorithms, the results show that HSSPBO's global search ability has been significantly improved, and it has faster global convergence speed, better optimization accuracy and stability in function optimization.

Foundation Support

国家自然科学基金资助项目(61662005)
广西自然科学基金资助项目(2021JJA170094)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.11.0630
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 6
Section: Algorithm Research & Explore
Pages: 1718-1724
Serial Number: 1001-3695(2022)06-020-1718-07

Publish History

[2022-01-25] Accepted Paper
[2022-06-05] Printed Article

Cite This Article

张伟, 王勇, 张宁. 采用混合策略的改进学生心理优化算法 [J]. 计算机应用研究, 2022, 39 (6): 1718-1724. (Zhang Wei, Wang Yong, Zhang Ning. Improved student psychology based optimization algorithm using hybrid strategy [J]. Application Research of Computers, 2022, 39 (6): 1718-1724. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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