文章主要论述基于成果导向教育(Outcome Based Education)模式的研究、启发反馈式教学方法在数学类专业课程中的探索,分析了当前数学类专业课程教学出现的新特点,引入OBE模式,以培养学生数学思维和应用数学工具解决复杂实际问题的能力...文章主要论述基于成果导向教育(Outcome Based Education)模式的研究、启发反馈式教学方法在数学类专业课程中的探索,分析了当前数学类专业课程教学出现的新特点,引入OBE模式,以培养学生数学思维和应用数学工具解决复杂实际问题的能力为目标,融入研究、启发式教学方法和个性化反馈评价体系。研究、启发式课堂教学环节体现了讲授知识体系的连贯性和前沿性;反馈式上机实践环节体现了学习过程的探究性及个性化。展开更多
Many heuristic search methods exhibit a remarkable variability in the time required to solve some particular problem instances. Their cost distributions are often heavy-tailed. It has been demonstrated that, in most c...Many heuristic search methods exhibit a remarkable variability in the time required to solve some particular problem instances. Their cost distributions are often heavy-tailed. It has been demonstrated that, in most cases, rapid restart (RR) method can prominently suppress the heavy-tailed nature of the instances and improve computation efficiency. However, it is usually time-consuming to check whether an algorithm on a specific instance is heavy-tailed or not. Moreover, if the heavy-tailed distribution is confirmed and the RR method is relevant, an optimal RR threshold should be chosen to facilitate the RR mechanism. In this paper, an approximate approach is proposed to quickly check whether an algorithm on a specific instance is heavy-tailed or not. The method is realized by means of calculating the maximal Lyapunov exponent of its generic running trace. Then a statistical formula to estimate the optimal RR threshold is educed. The method is based on common nonparametric estimation, e.g., Kernel estimation. Two heuristic methods are selected to verify our method. The experimental results are consistent with the theoretical consideration perfectly.展开更多
文摘文章主要论述基于成果导向教育(Outcome Based Education)模式的研究、启发反馈式教学方法在数学类专业课程中的探索,分析了当前数学类专业课程教学出现的新特点,引入OBE模式,以培养学生数学思维和应用数学工具解决复杂实际问题的能力为目标,融入研究、启发式教学方法和个性化反馈评价体系。研究、启发式课堂教学环节体现了讲授知识体系的连贯性和前沿性;反馈式上机实践环节体现了学习过程的探究性及个性化。
文摘Many heuristic search methods exhibit a remarkable variability in the time required to solve some particular problem instances. Their cost distributions are often heavy-tailed. It has been demonstrated that, in most cases, rapid restart (RR) method can prominently suppress the heavy-tailed nature of the instances and improve computation efficiency. However, it is usually time-consuming to check whether an algorithm on a specific instance is heavy-tailed or not. Moreover, if the heavy-tailed distribution is confirmed and the RR method is relevant, an optimal RR threshold should be chosen to facilitate the RR mechanism. In this paper, an approximate approach is proposed to quickly check whether an algorithm on a specific instance is heavy-tailed or not. The method is realized by means of calculating the maximal Lyapunov exponent of its generic running trace. Then a statistical formula to estimate the optimal RR threshold is educed. The method is based on common nonparametric estimation, e.g., Kernel estimation. Two heuristic methods are selected to verify our method. The experimental results are consistent with the theoretical consideration perfectly.
