关键词： 游戏教学法   小学   数学   算法多样化  

摘要： 计算是小学数学教学的基础内容,是学生完成各个阶段数学学习任务的必备能力。但是如今的计算课程却是很多小学生倍感头疼的课程,这主要与教师运用的教学方法比较单一,不能调动学生的计算兴趣有关,而能够让小学生产生数学计算兴趣的方法之一就是游戏教学法。算法多样化是《义务教育数学课程标准》中的一个关键理念,从本质上看就是尊重学生的个性化发展,倡导个性化学习,鼓励学生运用自己熟悉且感兴趣的思维方法解决问题。在促进小学数学算法多样化的教学中,教师可以引入游戏教学方案,让学生对课程学习表现出更强的适应能力和主动性。

关键词： Wind power  

摘要： In order to solve the problems of training data selection and parameter optimization of the prediction model, this paper introduces a method of the short-term prediction of wind power generating capacity based on mathematical morphology cluster analysis and fruit fly optimization algorithm. Mathematical morphology cluster analysis automatically divides numerical weather prediction data into several clusters according to dilation and erosion operation, and similar days with the predicted day are searched as training sample. Fruit fly optimization algorithm can determine quickly the optimization parameters of the prediction model. Simulation is performed to the wind power generation of Yilan wind farm. The results show that the method is effective and its precision is higher than that of the prediction model based on k-mean cluster analysis or particle swarm optimization algorithm. The effect of training data on model accuracy is higher than that of model optimization. © 2019, Editorial Board of Acta Energiae Solaris Sinica. All right reserved.

关键词： 边缘检测   数学形态学   车牌定位  

摘要： 车牌识别系统已经成功进入智能交通领域,其中车牌定位是车牌分割和车牌识别能顺利展开的基础。首先使用边缘检测改进canny算子进行一次粗定位,大致确定车牌所在区域;再对边缘检测后的二值图像进行膨胀、腐蚀等一系列数学形态学操作,完成车牌二次精确定位。根据实验结果表明,这种算法能够避免一定的噪声影响,解决目标图像噪声干扰及边缘模糊的问题,具有一定的鲁棒性。

关键词： 数学形态   图像处理   算法  

摘要： 文章主要研究数学形态学,利用学科特点在图像处理进行处理。通过形态学膨胀、细化、腐蚀、开闭等算法,使得图像处理简明及严谨,提升有效数据,去除冗余数据,提升图像处理效率,达到使用者预期。

关键词： 数学形态学   起搏脉冲   心电信号  

摘要： 心电通道起搏脉冲处理是心电信号处理方面的一个重要研究课题,针对心电通道上的起搏脉冲会造成QRS波的误识别以及波形分类错误等复杂问题,本文提出一种采用数学形态算法在心电QRS波识别之前对心电通道的心电信号进行处理,在保留心电QRS波的同时能够去掉起搏脉冲。实验表明,该方法能够有效的去掉心电通道上的起搏脉冲,提高心电通道QRS识别的准确率。

关键词： 分布式计算体系   任务调度   帕累托最优   多目标优化   粒子群算法   蚁群算法  

摘要： 航天器对大容量高效计算的要求越来越高,现有的星载计算体系的能力已经难以满足其需求,需要建立具有自组织能力的智能计算体系,还要实现高效的任务调度.给出了航天器分布式智能计算体系的模型和任务调度问题的多目标优化模型,并根据该模型设计了改进粒子群算法和改进蚁群算法结合的DPSO-EACO算法,先利用粒子群算法生成初始调度方案,再用该方案初始化蚁群算法,利用蚁群算法生成最终调度结果.仿真结果表明,该算法的性能与改进粒子群算法和改进蚁群算法相比具有明显的性能优势.

关键词： 小学数学   算法   多样化  

摘要： 算法多样化的思想强调的是尊重学生的独立思考,鼓励学生探索不同的方法,并不是让学生掌握多种方法,教师应该在课堂中鼓励、尊重学生思维的结果,引导学生进行讨论和交流,适时点拨,肯定有价值、有创意的方法,从而培养学生良好的思维习惯和探索创新的精神。

关键词： 数学解题   运算能力   低效算法   优化算法  

摘要： 运算能力主要是指能够根据法则和运算律正确地进行运算的能力,也是数学最重要的核心素养之一,优化运算能力对提高学生数学素养有重要的作用和意义。通过对中学课堂不同类型问题的低效算法和优化算法的解法对比分析,加深了对教材的挖掘拓展。最后,探讨了课堂例题学习的模式和数学师范生运算能力的培养,并对师范生未来的教师专业化发展给出了一些教学建议。

ISBN: (纸本)9787308199247

关键词： Interprocedural analysis   constant treewidth graphs   dataflow analysis   reachability and shortest path   reachability and distance oracles  

摘要： Interprocedural analysis is at the heart of numerous applications in programming languages, such as alias analysis, constant propagation, and so on. Recursive state machines (RSMs) are standard models for interprocedural analysis. We consider a general framework with RSMs where the transitions are labeled from a semiring and path properties are algebraic with semiring operations. RSMs with algebraic path properties can model interprocedural dataflow analysis problems, the shortest path problem, the most probable path problem, and so on. The traditional algorithms for interprocedural analysis focus on path properties where the starting point is fixed as the entry point of a specific method. In this work, we consider possible multiple queries as required in many applications such as in alias analysis. The study of multiple queries allows us to bring in an important algorithmic distinction between the resource usage of the one-time preprocessing vs for each individual query. The second aspect we consider is that the control flow graphs for most programs have constant treewidth. Our main contributions are simple and implementable algorithms that support multiple queries for algebraic path properties for RSMs that have constant treewidth. Our theoretical results show that our algorithms have small additional one-time preprocessing but can answer subsequent queries significantly faster as compared to the current algorithmic solutions for interprocedural dataflow analysis. We have also implemented our algorithms and evaluated their performance for performing on-demand interprocedural dataflow analysis on various domains, such as for live variable analysis and reaching definitions, on a standard benchmark set. Our experimental results align with our theoretical statements and show that after a lightweight preprocessing, on-demand queries are answered much faster than the standard existing algorithmic approaches.