Knowledge Workers’ Competence Evaluation Model Based on Extenics

2013 ◽  
pp. 1017-1026 ◽  
Author(s):  
Liang Tang
Keyword(s):  
Knowledge Workers ◽  
Evaluation Model ◽  
Model Based ◽  
Competence Evaluation

Research on the improvement of teachers’ teaching ability based on machine learning and digital twin technology

2020 ◽  
pp. 1-12
Author(s):  
Chen Siyan ◽  
Wang Tinghuai ◽  
Li Xiaomei ◽  
Zhu Liu ◽  
Wu Danying
Keyword(s):  
Machine Learning ◽  
Professional Competence ◽  
Evaluation Model ◽  
Teacher Competence ◽  
Fusion Model ◽  
Integration Model ◽  
Digital Twin ◽  
Model Based ◽  
Competence Evaluation ◽  
Neural Network Algorithm

The qualitative analysis results of teachers’ abilities are difficult to quantify, and ability problems in the teaching process are difficult to be effectively measured. In order to study methods to improve teachers’ teaching abilities, this paper builds a corresponding teacher competence evaluation model based on machine learning and digital twin technology, establishes a data collection model for teachers’ professional competence, and establishes a data fusion model. It includes data cleaning model based on XML information template, data integration model, multi-index screening mechanism and clustering strategy based on perturbation attributes. On this basis, this paper uses decision tree algorithm, random forest algorithm and neural network algorithm to construct three scheduling rule mining models aiming at teachers’ professional ability. In addition, this paper establishes a digital twin-driven multi-knowledge model scheduling optimization architecture that uses the three scheduling rules mined. The research results show that the model constructed in this paper has good performance.

Load-balancing evaluation model based on pre-defined variability

2009 ◽  
Vol 29 (10) ◽  
pp. 2849-2851
Author(s):  
Li-lun ZHANG ◽  
Jian-ping WU ◽  
Jun-qiang SONG
Keyword(s):  
Load Balancing ◽  
Evaluation Model ◽  
Model Based

Recognition of teaching method effects based on grid model simplification and artificial intelligence

2020 ◽  
pp. 1-11
Author(s):  
Guo Yunfeng ◽  
Li Jing
Keyword(s):  
Artificial Intelligence ◽  
Teaching Method ◽  
Evaluation Model ◽  
Geometric Constraints ◽  
Sorting Algorithm ◽  
Grid Model ◽  
Model Based ◽  
Refinement Method ◽  
Method Effects ◽  
Structure Simplification

In order to improve the effect of the teaching method evaluation model, based on the grid model, this paper constructs an artificial intelligence model based on the grid model. Moreover, this paper proposes a hexahedral grid structure simplification method based on weighted sorting, which comprehensively sorts the elimination order of candidate base complexes in the grid with three sets of sorting items of width, deformation and price improvement. At the same time, for the elimination order of basic complex strings, this paper also proposes a corresponding priority sorting algorithm. In addition, this paper proposes a smoothing regularization method based on the local parameterization method of the improved SLIM algorithm, which uses the regularized unit as the reference unit in the local mapping in the SLIM algorithm. Furthermore, this paper proposes an adaptive refinement method that maintains the uniformity of the grid and reduces the surface error, which can better slow down the occurrence of geometric constraints caused by insufficient number of elements in the process of grid simplification. Finally, this paper designs experiments to study the performance of the model. The research results show that the model constructed in this paper is effective.

Construction of a Statistical Evaluation Model Based on Molecular Centrality to Find Retrosynthetically Important Bonds in Organic Compounds

2008 ◽  
Vol 2008 (35) ◽  
pp. 5995-6007 ◽  
Author(s):  
Akio Tanaka ◽  
Takashi Kawai ◽  
Tsutomu Matsumoto ◽  
Mihoko Fujii ◽  
Tetsuhiko Takabatake ◽  
...  
Keyword(s):  
Organic Compounds ◽  
Statistical Evaluation ◽  
Evaluation Model ◽  
Model Based
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