| 具有动态自适应学习机制的教与学优化算法 |
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| 引用本文： | 李丽荣,李木子,李崔灿,王培崇. 具有动态自适应学习机制的教与学优化算法[J]. 计算机工程与应用, 2020, 56(19): 62-67. DOI: 10.3778/j.issn.1002-8331.1910-0012 |
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| 作者姓名： | 李丽荣 李木子 李崔灿 王培崇 |
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| 作者单位： | 1.河北地质大学 艺术设计学院，石家庄 050031 2.河北地质大学 信息工程学院，石家庄 0500313.河北地质大学 人工智能与机器学习研究所，石家庄 050031 |
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| 基金项目： | 高等学校科研项目;河北省社会科学基金 |
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| 摘 要： | 为了克服教与学优化（TLBO）算法容易出现早熟和解精度低的问题，提出了一种动态自适应学习的改进教与学优化（DSLTLBO）算法。在DSLTLBO算法的“教”阶段，引入一个自适应变化的因子，使当前个体在早期主要向最优个体学习，后期能够较好地维持自身状态，种群多样性得以保持。在算法的后期，教师个体通过执行动态随机搜索算法，提高最优个体勘探新解的能力。在10个经典的Benchmark函数上的实验表明，该算法具有较好的收敛速度和解精度，较标准TLBO有较大能力提升，适合于求解较高维度的优化问题。
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| 关 键 词： | 教与学优化（TLBO） 动态自适应 学习因子 动态随机搜索（DRS） |
Teaching and Learning Based Optimization with Dynamic Self-Adaptive Learning |
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| LI Lirong,LI Muzi,LI Cuican,WANG Peichong. Teaching and Learning Based Optimization with Dynamic Self-Adaptive Learning[J]. Computer Engineering and Applications, 2020, 56(19): 62-67. DOI: 10.3778/j.issn.1002-8331.1910-0012 |
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| Authors: | LI Lirong LI Muzi LI Cuican WANG Peichong |
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| Affiliation: | 1.College of Art Design, Hebei GEO University, Shijiazhuang 050031, China2.College of Information and Engineering, Hebei GEO University, Shijiazhuang 050031, China3.Laboratory of AI and Machine Learning, Hebei GEO University, Shijiazhuang 050031, China |
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| Abstract: | To overcome the problem of premature and low precision in Teaching and Learning Based Optimization（TLBO） algorithm, this paper proposes an improved TLBO with Dynamic Self-adapting Learning（DSLTLBO）. In the “teaching” phase of DSLTLBO, a factor based on the self-adaptive is introduced, which makes the current individual learn mainly from the best individual in the early stage and Maintain one’s own state in the later for keeping the diversity of population. Later stage in iteration, teacher individual excutes the Dynamic Random Searching（DRS）to improve its ablity of exploring the new solutions around them. Experiments on 10 classical Benchmark functions show that DSLTLBO has better convergence speed and solution accuracy than TLBO, and is suitable for solving higher dimensional optimization problems. |
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| Keywords: | Teaching and Learning Based Optimization（TLBO） dynamic self-adaptive learning factor Dynamic Random Searching（DRS） |
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