A statistical multivariable optimization method using improved orthogonal algorithm based on large data

Multivariable optimization under large data environment concerns with how to reliably obtain a set of optimization results from a mass of data that influence the object function complexly. This is an important issue in statistical calculation because the complexity between variable parameters leads to repeated statistical calculation analysis and a significant amount of data waste. A statistical multivariable optimization method using improved orthogonal algorithm based on large data is proposed. Considering the optimization problem with multi-parameters under large data environment, a multi-parameter optimization model used for improved orthogonal algorithm is established based on large data. Furthermore, an extensive simulation study on temperature field distribution of anti-/de-icing component was conducted to verify the validity of the statistical calculation analysis optimization method. The optimized temperature field distribution meets the anti-/de-icing requirements through numerical simulation. Simulation results show that the optimization effect is more evident and accurate than the non-optimized temperature distribution with the optimized results of the proposed method. Results verify the effectiveness of the proposed method.     

幼儿园艺术领域教学活动中师幼言语互动的静态—动态分析——基于改进型弗兰德斯互动分析系统

幼儿园艺术领域中良好的师幼互动可以有效提高教学质量，促进幼儿关键经验的掌握。本研究采取改进型弗兰德斯互 动分析系统，通过观看5节艺术领域课程录像进行课堂编码，采用矩阵分析、比率分析和绘制动态特征曲线图对集体教学活动 中的师幼互动情况进行分析。研究发现：从教师语言占比及问题类型判断，教师高控行为明显；从幼儿语言占比及活动中幼儿 的艺术表现力判断，幼儿自主行为缺乏。由此针对教师提出以下建议:突破自我，注重艺术领域教育活动表现性特征；打破常 规，凸显艺术领域教育活动发散性特征。