学业述评是我国新时代教育评价改革的新要求,掌握其概念并在实际教学中运用具有重要价值。但在实际应用过程中,学业述评往往与表现性评价、过程性评价、档案袋评价等概念发生混淆。因此,在明确学业述评内涵的基础上,厘清学业述评与其他...学业述评是我国新时代教育评价改革的新要求,掌握其概念并在实际教学中运用具有重要价值。但在实际应用过程中,学业述评往往与表现性评价、过程性评价、档案袋评价等概念发生混淆。因此,在明确学业述评内涵的基础上,厘清学业述评与其他几个相关概念的联系与区别并提出切实可行的应用建议,对于探索建立中小学教师教学述评制度、推动教育评价改革具有积极意义。Academic evaluation is a new requirement of education evaluation reform in the new era. It is of great value to master its concept and apply it in practical teaching. But in the process of practical application, academic evaluation is often confused with the concepts of performance evaluation, process evaluation and portfolio evaluation. Therefore, based on clarifying the connotation of academic evaluation, clarifying the relationship and difference between academic evaluation and other related concepts and putting forward feasible application suggestions are of positive significance to exploring the establishment of teaching evaluation system for primary and secondary school teachers and promoting education evaluation reform.展开更多
已有的轨迹预测算法针对移动对象运动模式,使用数学模型进行交通流模拟,难以对路网中的移动对象进行准确的描述.为了解决这一问题,提出基于隐马尔可夫模型(hidden Markov model,简称HMM)的自适应轨迹预测模型SATP(self-adaptive traject...已有的轨迹预测算法针对移动对象运动模式,使用数学模型进行交通流模拟,难以对路网中的移动对象进行准确的描述.为了解决这一问题,提出基于隐马尔可夫模型(hidden Markov model,简称HMM)的自适应轨迹预测模型SATP(self-adaptive trajectory prediction model based on HMM),对大数据环境下移动对象海量轨迹利用基于密度的聚类方法进行位置密度分区和高效分段处理,减少HMM的状态数量.根据输入轨迹自动选取参数组合,避免HMM模型中隐状态不连续、状态停留等问题.实验结果表明,SATP模型在实验中表现出较高的预测准确性,并维持较低的时间开销.针对速度随机改变的移动对象,其平均预测准确率为84.1%;相同情况下,平均高出朴素预测算法46.7%.展开更多
文摘学业述评是我国新时代教育评价改革的新要求,掌握其概念并在实际教学中运用具有重要价值。但在实际应用过程中,学业述评往往与表现性评价、过程性评价、档案袋评价等概念发生混淆。因此,在明确学业述评内涵的基础上,厘清学业述评与其他几个相关概念的联系与区别并提出切实可行的应用建议,对于探索建立中小学教师教学述评制度、推动教育评价改革具有积极意义。Academic evaluation is a new requirement of education evaluation reform in the new era. It is of great value to master its concept and apply it in practical teaching. But in the process of practical application, academic evaluation is often confused with the concepts of performance evaluation, process evaluation and portfolio evaluation. Therefore, based on clarifying the connotation of academic evaluation, clarifying the relationship and difference between academic evaluation and other related concepts and putting forward feasible application suggestions are of positive significance to exploring the establishment of teaching evaluation system for primary and secondary school teachers and promoting education evaluation reform.
文摘已有的轨迹预测算法针对移动对象运动模式,使用数学模型进行交通流模拟,难以对路网中的移动对象进行准确的描述.为了解决这一问题,提出基于隐马尔可夫模型(hidden Markov model,简称HMM)的自适应轨迹预测模型SATP(self-adaptive trajectory prediction model based on HMM),对大数据环境下移动对象海量轨迹利用基于密度的聚类方法进行位置密度分区和高效分段处理,减少HMM的状态数量.根据输入轨迹自动选取参数组合,避免HMM模型中隐状态不连续、状态停留等问题.实验结果表明,SATP模型在实验中表现出较高的预测准确性,并维持较低的时间开销.针对速度随机改变的移动对象,其平均预测准确率为84.1%;相同情况下,平均高出朴素预测算法46.7%.
