scholarly journals Evaluation Model of Power Operation and Maintenance Based on Text Emotion Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Wei Wan ◽  
Yuanlong Liu ◽  
Xingwang Han ◽  
Huijian Wang
Keyword(s):  
Data Mining ◽  
Evaluation Model ◽  
Cosine Similarity ◽  
Supplier Evaluation ◽  
Power Equipment ◽  
Analysis Model ◽  
Emotion Analysis ◽  
Semantic Richness ◽  
Operation And Maintenance ◽  
Power Operation

The application of data mining technology in power field mainly focuses on the application of power defect text and dispatching text. However, the power operation and maintenance data contains a lot of information about power equipment suppliers. Taking the operation and maintenance text involving power equipment suppliers as an example, this paper summarizes the theme of operation and maintenance text and studies the evaluation model of power equipment suppliers. The next sentence prediction analysis model of single round dialogue text based on transformer bidirectional encoder prediction and cosine similarity weighting is proposed, which can effectively divide the topic of dialogue text. Aiming at the semantic richness and complexity of power operation and maintenance text, a supplier evaluation model based on text emotion analysis is proposed. Based on the expansion of the entries and attributes of the existing power ontology dictionary, the dialogue emotion analysis rules are established to realize the normal evaluation of power equipment suppliers.

Students’ emotional analysis on ideological and political teaching classes based on artificial intelligence and data mining

2020 ◽  
pp. 1-9
Author(s):  
Hou Yuzhong
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Analysis Model ◽  
Emotion Analysis ◽  
Artificial Intelligence Technology ◽  
The Individual ◽  
Study Designs ◽  
External Stimuli ◽  
Transfer Probability ◽  
Learning Data

Ideological and political teaching emotion is an important reflection of students’ learning achievements. At present, the effect of emotion analysis of ideological and political students is poor. This article builds on the artificial intelligence technology and combines machine learning data mining ideas to construct a student emotion analysis model in the ideological and political classroom. Starting from the individual, based on the individual’s own emotions and external stimuli, this article carries out emotion transfer probability statistics on the dialogues with emotions marked, and obtains the individual’s emotion transfer matrix. After the corresponding model is constructed, it can be applied to practice, and the research is conducted from the aspects of systematic emotion analysis effect and teaching promotion effect. In addition, this study designs a controlled experiment to analyze the effects of the model. The research results show that the model constructed in this paper has good performance.

Research on Related Model for Urban Public Crisis Handle Mechanism

2014 ◽  
Vol 989-994 ◽  
pp. 5540-5543
Author(s):  
Yong Chang Ren
Keyword(s):  
Crisis Management ◽  
Evaluation Model ◽  
Point Of View ◽  
Theoretical Point ◽  
Analysis Model ◽  
The Public ◽  
Public Crisis ◽  
Crisis Events ◽  
Response And Recovery ◽  
The Relationship

China is in a critical period of urbanization, and various social contradictions continue to be accumulated, emerged and enlarged, so public crisis management mechanism has been highly valued by governments at all levels with the public crisis events are occurred frequently. The paper conducts study for the problems in the current urban public crisis handle mechanism. First, the evaluation model of crisis management can be researched, and crisis management can be divided into four stages to evaluate respectively, they are Reduction, Readiness, Response and Recovery; then, we should research crisis prediction model to strengthen prediction, prevention and monitoring of the crisis before the crisis happened; finally, stakeholders analysis model should be studied, and scientific analyzing the interests of the various stakeholders and the relationship among them. From the theoretical point of view, the paper carries on a study for crisis handle mechanism to provide support for improving the crisis handle level.

Research on Combat Effectiveness Evaluation of Radar EW System Based on Bayesian Network

2011 ◽  
Vol 204-210 ◽  
pp. 1697-1700 ◽  
Author(s):  
Yu Jie Zheng
Keyword(s):  
Bayesian Network ◽  
Evaluation Model ◽  
Effectiveness Evaluation ◽  
Analysis Model ◽  
Key Factors ◽  
Bayesian Network Model ◽  
Simulation Data ◽  
Factors Analysis ◽  
Combat Effectiveness ◽  
Hidden Knowledge

Radar EW system combat effectiveness evaluation is a essential link to Radar system Demonstration, mainly give service to selection, optimization and key factors analysis of Weapon equipment scheme. In this paper, we introduce the Bayesian network model into the area of Radar EW system combat effectiveness evaluation and put forward the concept of combat effectiveness evaluation model based on Bayesian network. The ability to express complex relationship, the ability to express the uncertainty of probability, and the reasoning functions. By learning from Expertise and Simulation data, excavating the hidden knowledge included in both of them, we can build the combat efficiency Analysis model, and then carry out efficient analysis.

Application of data mining technology and wireless network sensing technology in sports training index analysis

2020 ◽  
Author(s):  
Liqiu Qian ◽  
Jiatong Liu
Keyword(s):  
Data Mining ◽  
Test Accuracy ◽  
Analysis Method ◽  
Sports Training ◽  
Analysis Model ◽  
Data Types ◽  
Mining Technology ◽  
Accuracy Test ◽  
Index Analysis ◽  
Sensing Technology

Abstract The conventional analysis method can provide a general analysis of sports training index, but its ability is relatively low when analyzing niche data. To solve this problem, this paper proposes data mining technology. First, the indicator parameter classification is determined, then the data mining technology is imported, the sports training analysis mechanism is established through this technology, and the construction of the index analysis model is completed. The model is used to analyze the process of niche data mining, and effective data of training indicators are obtained. Deep learning is a method of machine learning based on representation of data.Through the coverage test, accuracy test and immunity test, the variable parameters of the comprehensive analysis capability are determined. Further calculation of this parameter shows that the comprehensive ability of the data mining application analysis method is improved by 37.14% compared with the conventional method, which is suitable for analysis of niche sports training indicators of different data types.

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