scholarly journals Design and Research of Mathematics Teaching Intelligent Classroom Based on PCA-NN Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Baozhen Li ◽  
Lina Zhang
Keyword(s):  
Mathematics Teaching ◽  
Basic Education ◽  
Mathematics Classroom ◽  
Principal Component ◽  
Adaptive Strategy ◽  
Teaching Quality ◽  
Classroom Teaching ◽  
Classroom Design ◽  
Factors Affecting ◽  
Intelligent Classroom

With the increasing importance of mathematics in basic education, how to evaluate and analyze the intelligent effect of mathematics teaching classroom through scientific methods has become one of the indicators to evaluate the intelligent classroom. This paper studies the design and application of mathematics teaching intelligent classroom based on the PCA-NN (principal component analysis-neural network) algorithm. Firstly, this paper briefly describes the current research status of mathematics teaching intelligent classroom design and PCA-NN algorithm. Secondly, combined with the key factors of mathematics teaching, it formulates specific standards and puts forward an adaptive strategy of intelligent and personalized intelligent mathematics teaching classroom. Finally, the algorithm is verified by experiments. The results show that, for students with different mathematics basic levels, the mathematics teaching intelligent classroom based on the PCA-NN algorithm can effectively improve the quality of mathematics classroom teaching. Through the research on the factors such as teaching quality, effect, and interaction mode involved in the process of mathematics teaching classroom design, the intelligent classroom design factors affecting teaching quality are determined. This paper analyzes and studies the system from different angles. The research results provide some help for the current quality evaluation of classroom teaching and use the PCA-NN algorithm to make quantitative analysis and multivariate verification of mathematics classroom teaching effect.

Model Design of Universal Open Intelligent Classroom Teaching Software

2012 ◽  
Vol 566 ◽  
pp. 207-212 ◽  
Author(s):  
Yan Yu ◽  
Jian Hua Wang
Keyword(s):  
Computer Technology ◽  
Teaching Effectiveness ◽  
Teaching Quality ◽  
Classroom Teaching ◽  
Model Structure ◽  
Model Design ◽  
Existing Problems ◽  
Teaching Efficiency ◽  
Education In China ◽  
Intelligent Classroom

This paper discusses the development of CAI and finds out the existing problems through the analysis of usage of teaching courseware in the class in the school education in China as well as the application of computer technology in current teaching. Meanwhile, it proposes the promotion of this universal open intelligent classroom teaching software in classroom teaching and a number of principles to follow in its design. Furthermore, the paper elaborates the model structure and detailed functions of each model of this software after full evaluation. The application of this universal open intelligent classroom teaching software will certainly improve teaching efficiency and enhance teaching effectiveness and teaching quality further.

scholarly journals Fuzzy Cluster Analysis on Influencing Factors of College Student Scores

2020 ◽  
Vol 34 (5) ◽  
pp. 607-616
Author(s):  
Jia Wen ◽  
Xiaochong Wei ◽  
Haipeng Liu ◽  
Yiyuan Rong
Keyword(s):  
Cluster Analysis ◽  
College Student ◽  
Principal Component ◽  
Teaching Quality ◽  
Fuzzy Cluster ◽  
Key Factors ◽  
Fuzzy Cluster Analysis ◽  
Factors Affecting ◽  
Family Factor ◽  
Teachers And Students

In the age of the Internet, the learning environment is increasingly diversified. It is of great importance to explore the factors that truly affect the college student scores. Focusing on 13 factors that potentially influence college student scores, this paper carries out a questionnaire survey on students of different grades from different colleges, conducts fuzzy processing of the collected data, randomly selects the processed data for initialization of attribute values. Then, the initialized data were subject to principal component analysis (PCA), fuzzy cluster analysis (FCA), and analysis of variance (ANOVA). Through the analysis, six factors were identified as the key factors affecting college student scores: family factor, Exam factor, exchange factor, learner factor, classmate factor, and campus factor. On this basis, the authors called for the concerted efforts from the school, teachers, and students for improving the teaching quality in colleges.

Reliability Parameters Forecasting for Transmission Lines Based on Principal Component Regression

2013 ◽  
Vol 291-294 ◽  
pp. 2381-2386 ◽  
Author(s):  
Wen Xia Liu ◽  
Ji Kai Xu ◽  
Hong Yuan Jiang ◽  
Yong Tao Shen
Keyword(s):  
Principal Component Analysis ◽  
Transmission Lines ◽  
Principal Component Regression ◽  
Principal Component ◽  
Forecasting Accuracy ◽  
Factors Affecting ◽  
Reliability Parameters ◽  
Impacting Factors ◽  
Simulation Results

It is the foundation for evaluating the reliability of transmission lines to obtain and analyze the original reliability parameters. However, these parameters depend on long- term statistic and calculation. In the case of lacking such parameters in a new project , this paper proposes a method of Principal Component Analysis to obtain the principal component of the impacting factors ,in which various factors affecting reliability parameters are taken into account. Through this method, we can use PCR to obtain the failure rate of the unknown transmission lines on the base of the known credible lines’ rates. The simulation results show that the proposed approach possesses higher forecasting accuracy and provides references for the power system dispatching departments and transmission lines maintenance departments.

scholarly journals CONTRIBUTIONS OF FIGURES NUMBERS IN THE DEVELOPMENT OF GEOMETRIC THOUGHT

2019 ◽  
Vol 7 (1) ◽  
pp. 16-30
Author(s):  
Maria José Costa dos Santos ◽  
Arnaldo Lopes Bezerra
Keyword(s):  
Mathematics Teaching ◽  
Teaching And Learning ◽  
Basic Education ◽  
Mathematical Thinking ◽  
Algebraic Thinking ◽  
Ethical Awareness ◽  
Pedagogical Tools ◽  
Geometric Thinking ◽  
Virtual Libraries ◽  
Abstract Content

This study was constituted with the purpose of promoting reflections on Mathematics of basic education, from a transdisciplinary view of teaching and learning processes. To do so, we aim to analyze the contributions of figures in the development of geometric thinking. We characterize this research in empirical-exploratory, because for Lakatos and Marconi (2017), this type of research distinguishes itself as a scientific process of investigation that allows the researcher to formulate questions, with three purposes: to raise hypotheses, to increase the familiarization of the researcher in order to research, modify or clarify concepts, based on a qualitative and quantitative approach, according to the depth of the discussion about the object in question. For this, we look for information in other researches, databases of universities and virtual libraries, periodicals.  We hope that the results contribute to the critical and ethical awareness from views of the importance of the development of mathematical thinking, but specifically of geometric thinking, aiming at non-rupture with arithmetic thinking, in order to interweave with algebraic thinking . We consider this research relevant because mathematics teaching is based on abstract content that often makes no sense to the student, and here we show a part of mathematics that is formal but can be fun when well crafted in the classroom. Finally, we present pedagogical tools of innovation, aimed at contributing to the emancipation of the knowledge of this science, without ruptures. Keywords: Geometric thinking. Figurative numbers. Mathematics Teaching.

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