Multi-strategy enhanced artificial rabbits optimization for prediction of grades in tourism service communication courses.

IF 3.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Xiaodan Qu, Zhuyin Jia
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引用次数: 0

Abstract

Predicting students' grades through their classroom behavior has been a longstanding concern in education. Recently, artificial intelligence has demonstrated remarkable potential in this area. In this study, the Artificial Rabbits Optimization Algorithm is selected to enhance the predictor's capabilities. This algorithm, a recently proposed and popular metaheuristic method, is known for its simple and straightforward structure. However, like other metaheuristic algorithms, it often falls into local optima, and as iterations increase, the convergence speed slows down, leading to reduced convergence accuracy. To address this issue, a Multi-Strategy Enhanced Artificial Rabbits Optimization Algorithm (MEARO) is introduced. MEARO first employs a Nonlinear Exploration and Exploitation Transition Factor (NL) to improve the balance between exploration and exploitation. Additionally, a Stochastic Centroid Backward Learning approach (SOBL) is applied to enhance both the quality and diversity of the population, ensuring a broader optimization of the search area and increasing the chances of locating the global optimum. Finally, a Dynamic Changing Step Length Development strategy is incorporated to enhance the randomness and development capability. The efficiency of MEARO is confirmed by comparing its performance with eight other sophisticated algorithms using the CEC2017 benchmark. The number of wins/Ties/losses in the three dimensions of cec2017 are (223/0/17), (221/0/19) and (230/0/10) respectively. Results indicate that MEARO outperforms these algorithms. Furthermore, MEARO is used to optimize two critical parameters of the Kernel Extreme Learning Machine (KELM), significantly improving its classification performance. Experimental results on the collected student performance dataset demonstrate that the KELM model optimized by MEARO surpasses other benchmark models across various metrics. Additionally, factors such as interest in the course, frequency of classroom discussion, and access to supplementary knowledge and information related to the course are identified as significant contributors to performance.

旅游服务传播课程成绩预测的多策略增强人工兔子优化。
通过学生的课堂行为来预测学生的成绩一直是教育界长期关注的问题。最近,人工智能在这一领域显示出了惊人的潜力。在本研究中,选择人工兔子优化算法来提高预测器的能力。该算法是最近提出的一种流行的元启发式算法,其结构简单明了。然而,与其他元启发式算法一样,它经常陷入局部最优,并且随着迭代次数的增加,收敛速度减慢,导致收敛精度降低。针对这一问题,提出了一种多策略增强型人工兔子优化算法(MEARO)。MEARO首先采用非线性勘探与开采过渡系数(NL)来改善勘探与开采之间的平衡。此外,应用随机质心向后学习方法(SOBL)来提高种群的质量和多样性,确保更广泛的搜索区域优化,增加找到全局最优的机会。最后,引入动态变化步长开发策略,增强系统的随机性和开发能力。通过使用CEC2017基准将MEARO的性能与其他八种复杂算法进行比较,证实了MEARO的效率。cec2017三个维度的胜/平/输次数分别为(223/0/17)、(221/0/19)和(230/0/10)。结果表明,MEARO算法优于这些算法。利用MEARO算法对KELM的两个关键参数进行了优化,显著提高了KELM的分类性能。在收集的学生成绩数据集上的实验结果表明,MEARO优化的KELM模型在各种指标上优于其他基准模型。此外,对课程的兴趣、课堂讨论的频率、获得与课程相关的补充知识和信息等因素也被认为是影响成绩的重要因素。
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来源期刊
Scientific Reports
Scientific Reports Natural Science Disciplines-
CiteScore
7.50
自引率
4.30%
发文量
19567
审稿时长
3.9 months
期刊介绍: We publish original research from all areas of the natural sciences, psychology, medicine and engineering. You can learn more about what we publish by browsing our specific scientific subject areas below or explore Scientific Reports by browsing all articles and collections. Scientific Reports has a 2-year impact factor: 4.380 (2021), and is the 6th most-cited journal in the world, with more than 540,000 citations in 2020 (Clarivate Analytics, 2021). •Engineering Engineering covers all aspects of engineering, technology, and applied science. It plays a crucial role in the development of technologies to address some of the world''s biggest challenges, helping to save lives and improve the way we live. •Physical sciences Physical sciences are those academic disciplines that aim to uncover the underlying laws of nature — often written in the language of mathematics. It is a collective term for areas of study including astronomy, chemistry, materials science and physics. •Earth and environmental sciences Earth and environmental sciences cover all aspects of Earth and planetary science and broadly encompass solid Earth processes, surface and atmospheric dynamics, Earth system history, climate and climate change, marine and freshwater systems, and ecology. It also considers the interactions between humans and these systems. •Biological sciences Biological sciences encompass all the divisions of natural sciences examining various aspects of vital processes. The concept includes anatomy, physiology, cell biology, biochemistry and biophysics, and covers all organisms from microorganisms, animals to plants. •Health sciences The health sciences study health, disease and healthcare. This field of study aims to develop knowledge, interventions and technology for use in healthcare to improve the treatment of patients.
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