Study on the Indicator System of Oilfield Equipment Manufacturing Enterprise Marketing Security Early Warning

2014 ◽  
Vol 3 (1) ◽  
pp. 33
Author(s):  
Minchang Xin ◽  
Yanbin Sun
Keyword(s):  
Early Warning ◽  
Indicator System ◽  
Manufacturing Enterprise ◽  
Equipment Manufacturing ◽  
Oilfield Equipment

scholarly journals The Research of Coal and Gas Outburst Warning Based on Logistic Regression and Geographic Information System

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Bo You ◽  
Bo Li ◽  
Shi Liang Shi ◽  
He Qing Liu ◽  
Yi Lu ◽  
...  
Keyword(s):  
Information System ◽  
Logistic Regression ◽  
Geographic Information System ◽  
Early Warning ◽  
Warning System ◽  
Indicator System ◽  
Geographic Information ◽  
Coal And Gas Outburst ◽  
Gas Outburst ◽  
Early Warning Indicator

Coal and gas outburst is one of the major disasters in the safety production of coal mine. According to the mechanism of coal and gas outburst, based on the comprehensive analysis of various influencing factors of coal and gas outburst, with the principles of selected early warning indicator, the basic information database of coal and gas outburst warning is constructed, and the information data query function is realized. The mathematical model of coal and gas outburst warning is established by the logistic regression analysis based on the gas concentration, the gas desorption index of drill cuttings, and the initial velocity of gas emission from the borehole. The multivariate information coupled warning was conducted according to the selected early warning indicator system, and the early warning level was divided with the result of early warning. The design and research of the coal and gas outburst warning system are carried out based on the geographic information system (GIS). The coal and gas outburst warning system was verified by taking the Tunliu mine of Lu’an Group as an example. The establishment of the early warning system is a new technical way to the early warning management of coal and gas outburst and can provide a guarantee for coal and gas outburst prevention.

scholarly journals An Empirical Study on the Employment Monitoring and Early Warning Mechanism of Medical Graduates in Universities with Big Data and Complex Computing System

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Haixia Wu ◽  
Sang-Bing Tsai
Keyword(s):  
Big Data ◽  
Early Warning ◽  
Indicator System ◽  
Good Effect ◽  
Business Decision ◽  
Graduate Employment ◽  
Regulatory Measures ◽  
Employment Evaluation ◽  
Employment Cycle ◽  
Monitoring And Early Warning

Based on the management of big data, the analysis and forecast of the employment demand cycle business situation studied in this article is based on the employment cycle theory and a complete set of employment monitoring, employment evaluation, employment forecasting, and policy selection theories and strategies developed around the employment cycle fluctuations, a specific employment phenomenon. First, systematically evaluate the current state of the employment demand boom, appropriately reflect the hot and cold degree of the employment demand boom, and provide necessary information for the government’s regulatory measures, content, and timing. Secondly, it reflects the regulatory effects of graduate employment monitoring, judging whether graduate employment monitoring measures are properly applied, whether they have the effect of smoothing out employment fluctuations, and promoting the country’s employment demand; in addition, business decision makers can take advantage of the employment demand boom, by monitoring the information provided by the early warning system and timely foreseeing the upcoming macrocontrol measures, so that enterprises’ labor adjustments can adapt to the government’s regulatory measures. At the same time, the model proposes a prosperity index method for monitoring and early warning of the employment demand cycle. After selecting and dividing three types of prosperity indicators, the DI index reflecting the trend of the prosperity change and the CI index reflecting the strength of the prosperity change are calculated and constructed. The national employment demand boom monitoring and early warning signal system predicts the trend of the employment boom cycle outside the sample period. The experimental results show that the cyclic prosperity forecast results are consistent not only with the national employment demand prosperity in recent months, but also with the use of the structural measurement ARIMA (p, d, q) model. The alertness value is close, indicating that this indicator system has a good effect on the national employment demand boom monitoring and early warning.

Research on construction of anti-dumping early warning model based on BP neural network

2020 ◽  
Vol 39 (4) ◽  
pp. 5649-5659
Author(s):  
Jun Chen ◽  
Ying Xu ◽  
Shiyan Xu ◽  
Chenyang Zhao ◽  
Hui Chen
Keyword(s):  
Neural Network ◽  
Early Warning ◽  
Bp Neural Network ◽  
The United States ◽  
Indicator System ◽  
Actual Case ◽  
The Sustainable Development ◽  
Early Warning Model ◽  
Input Layer ◽  
Warning Model

China has now become the country with the most anti-dumping lawsuits in the world, and the trade protection of anti-dumping measures has become a huge obstacle to the sustainable development of China’s foreign trade. In view of the current situation of anti-dumping in the United States, this study combines BP neural network to construct an anti-dumping early warning model. In order to predict the longer-term future based on the existing database, the BP neural network should be used to predict the indicators in the existing index database, and then the predicted warning indicator system is used as the input layer to warn the future police. Moreover, this study conducts research on the performance of the algorithm based on the actual case analysis. The research shows that the algorithm has certain effects and can provide theoretical reference for subsequent related research.

Export injury early warning of the new energy industries in China

2017 ◽  
Vol 7 (2) ◽  
pp. 272-285 ◽  
Author(s):  
Jinjin Wang ◽  
Zhengxin Wang ◽  
Qin Li
Keyword(s):  
Smart Grid ◽  
Early Warning ◽  
Nuclear Power ◽  
Indicator System ◽  
Small Sample ◽  
Energy Industry ◽  
Actual Condition ◽  
Content Type ◽  
Forecast Result ◽  
New Energy

Purpose In recent years, continuous expansion of the scale of the new energy export industry in China caused a boycott of American and European countries. Export injury early warning research is an urgent task to develop the new energy industry in China. The purpose of this paper is to build an indicator system of exports injury early warning of the new energy industry in China and corresponding quantitative early warning models. Design/methodology/approach In consideration of the actual condition of the new energy industry in China, this paper establishes an indicator system according to four aspects: export price, export quantity, impact on domestic industry and impact on macro economy. Based on the actual data of new energy industry and its five sub-industries (solar, wind, nuclear power, smart grid and biomass) in China from 2003 to 2013, GM (1,1) model is used to predict early warning index values for 2014-2018. Then, the principal component analysis (PCA) is used to obtain the comprehensive early warning index values for 2003-2018. The 3-sigma principle is used to divide the early warning intervals according to the comprehensive early warning index values for 2003-2018 and their standard deviation. Finally, this paper determines alarm degrees for 2003-2018. Findings Overall export condition of the new energy industry in China is a process from cold to normal in 2003-2013, and the forecast result shows that it will be normal from 2014 to 2018. The export condition of the solar energy industry experienced a warming process, tended to be normal, and the forecast result shows that it will also be normal in 2014-2018. The biomass and other new energy industries and nuclear power industry show a similar development process. Export condition of the wind energy industry is relatively unstable, and it will be partially hot in 2014-2018, according to the forecast result. As for the smart grid industry, the overall export condition of it is normal, but it is also unstable, in few years it will be partially hot or partially cold. The forecast result shows that in 2014-2018, it will maintain the normal state. In general, there is a rapid progress in the export competitiveness of the new energy industry in China in the recent decade. Practical implications Export injury early warning research of the new energy industry can help new energy companies to take appropriate measures to reduce trade losses in advance. It can also help the relevant government departments to adjust industrial policies and optimize the new energy industry structure. Originality/value This paper constructs an index system that can measure the alarm degrees of the new energy industry. By combining the GM (1,1) model and the PCA method, the problem of warning condition detection under small sample data sets is solved.

Design and Application of Project Management System for Project-Driven Equipment Manufacturing Enterprise

2013 ◽  
Vol 397-400 ◽  
pp. 2610-2617
Author(s):  
Yan Xia Chen ◽  
Shun Sheng Guo ◽  
Bai Gang Du ◽  
Li Bo Sun
Keyword(s):  
Project Management ◽  
Management System ◽  
Implementation Process ◽  
Sql Server ◽  
Manufacturing Enterprise ◽  
Project Management System ◽  
Single Piece ◽  
Equipment Manufacturing ◽  
Sql Server Database ◽  
Database Technology

The production mode of equipment manufacturing enterprise is large single-piece production driven by project for customer personalization. This is complex in a large project, where having so many involved resources, persons and content can become more difficult to manage. Whereas, the current project management system mainly focuses on some single functions and ignores the requirements of project lifecycle for process tracking management. Therefore, on the foundation of investigation and analysis, the models of material flow and cash flow are proposed to monitor the implementation process of project and developed a lifecycle-oriented Project Management System (PMS) by using ASP.NET platform and SQL SERVER database technology in equipment manufacturing enterprise. Finally, the application effect of PMS software in equipment manufacturing enterprise demonstrates its feasibility and effectiveness.

Construction of Patent Infringement Litigation Early Warning Index System for the Pharmaceutical Enterprises

2012 ◽  
Vol 268-270 ◽  
pp. 2045-2049
Author(s):  
Ying Wang
Keyword(s):  
Early Warning ◽  
Quantitative Methods ◽  
Indicator System ◽  
Patent Infringement ◽  
Qualitative And Quantitative Methods ◽  
Early Warning Indicator ◽  
Target Company ◽  
Target Layer ◽  
Warning Model ◽  
Warning Indicators

Our objective is to establish the patent infringement litigation early warning model and early warning indicator system for pharmaceutical companies. Reversely generate the warning model based on incentives of patent infringement litigation. A combination of qualitative and quantitative methods were used to determine the specific early warning indicators. According to the hierarchical analytical process, the three-tier warning indicator was established system including the target layer and factors, and three stages of the early warning indicator system: were put forward: preliminary warning phase, target company judging phase, and accurate early warning stage. Quantified statement was given to all the warning indicators, to establish a mathematical model.

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