CN102542356A - Early alarming model for self repairing of enterprise internal supervision system - Google Patents
Early alarming model for self repairing of enterprise internal supervision system Download PDFInfo
- Publication number
- CN102542356A CN102542356A CN2011103710352A CN201110371035A CN102542356A CN 102542356 A CN102542356 A CN 102542356A CN 2011103710352 A CN2011103710352 A CN 2011103710352A CN 201110371035 A CN201110371035 A CN 201110371035A CN 102542356 A CN102542356 A CN 102542356A
- Authority
- CN
- China
- Prior art keywords
- early
- filter
- data
- alarming model
- early alarming
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004458 analytical method Methods 0.000 claims description 10
- 238000001914 filtration Methods 0.000 claims description 9
- 230000015572 biosynthetic process Effects 0.000 claims description 3
- 230000004060 metabolic process Effects 0.000 claims description 3
- 238000007619 statistical method Methods 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 abstract 1
- 238000000034 method Methods 0.000 description 4
- 235000019504 cigarettes Nutrition 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 241000208125 Nicotiana Species 0.000 description 1
- 235000002637 Nicotiana tabacum Nutrition 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
Images
Abstract
The invention discloses an early alarming model for self repairing of an enterprise internal supervision system, which belongs to the field of computer software. The thinking of the early alarming model uses a filter, and the filter filters by adopting a ring-shaped circuiting mechanism which is formed on the positive and the reverse directions. The early alarming model filters and positions levels for supervise objects according combination of filter conditions, and gives different degrees of attentions to the supervise objects in actual supervision according to levels. Compared with the prior art, the early alarming model for self repairing of the enterprise internal supervision system provides a scientific and reasonable modeling for supervise issues in enterprise management. The early alarming model for self repairing of the enterprise internal supervision system greatly increases scientificity and convenience of supervise work of enterprises through the simple and visual filter to set function.
Description
Technical field
The present invention relates to computer software fields, the Early-warning Model that specifically a kind of enterprises supervisory systems oneself revises.
Background technology
Under the overall background of enterprise management informatization, data analysis technique has become the focus that enterprise application is paid close attention to.Can help enterprise that data are carried out statistics, analysis, the comprehensive and reasoning of microcosmic, middle sight and even macroscopic view, thereby utilize data with existing to monitor the problem that exists in the current management.Use suitable modeling technique, set up the analytical model, assessment models of enterprise management system etc., finally progressively realize data mining, for management provides more authority's data foundation.
Summary of the invention
Technical assignment of the present invention is the deficiency to above-mentioned prior art, the Early-warning Model that provides a kind of enterprises supervisory systems oneself to revise.
Technical assignment of the present invention is realized by following mode: the Early-warning Model that enterprises supervisory systems oneself revises; Adopt the thinking of filter; The annular circulative metabolism that has adopted forward, reverse formation is set in the filtration to filter; That is the condition that this analysis result was analyzed as next time; Filter for supervised entities and rank location based on the combination of filter condition, in onsite supervision, give and in various degree concern for supervised entities based on rank.
The condition that filter filters adopts probabilistic statistical method; Comprise historical point view analysis and colony's angle analysis: when historical point view is analyzed,, calculate the confidential interval (a of M% based on the probability distribution that historical data is obeyed; B), judge that this secondary data is whether in confidential interval;
During from colony's angle analysis, go out the average μ and the standard deviation sigma of this population data, judge that individual data is whether in [μ-3 σ, μ+3 σ] according to statistical computation.
Compared with prior art, the Early-warning Model that enterprises supervisory systems oneself of the present invention revises provides scientific and reasonable modeling to the supervision problem in the business administration, and model has the ability that the oneself revises on time dimension.Simultaneously through succinctly intuitively filtrator function is set, greatly improved science, the convenience of the supervision of enterprise.Can realize filtering, adopt the filtrator thinking, be fit to each enterprise management system for the reasonable analysis of management data.
Description of drawings
Accompanying drawing 1 is the filtering process synoptic diagram of the Early-warning Model of enterprises supervisory systems oneself of the present invention correction;
Accompanying drawing 2 is filtering rule synoptic diagram of the Early-warning Model of enterprises supervisory systems oneself of the present invention correction;
Accompanying drawing 3 is marketing model figure of the embodiment of the invention.
Embodiment
Explanation at length below the Early-warning Model of enterprises supervisory systems of the present invention oneself being revised with specific embodiment is done.
Embodiment:
Enterprises supervisory systems Early-warning Model scheme of the present invention adopts the thinking of filtrator, in the filtration to filtrator the annular circulative metabolism that has adopted forward, reverse formation is set, a condition can this analysis result being analyzed as next time.Filter for supervised entities and rank location based on the combination of filter condition, in onsite supervision, give and in various degree concern for supervised entities based on rank.
The condition of filtering adopts probabilistic statistical method, combines data are analyzed with two angles of colony from history.From historical point view, according to the probability distribution that historical data is obeyed, (a b), judges that this secondary data is whether in fiducial interval to calculate the fiducial interval of M%.From colony's angle, go out the average μ and the standard deviation sigma of this population data according to statistical computation, judge that individual data is whether in [μ-3 σ, μ+3 σ].
Filtering process is shown in accompanying drawing 1, and the filtering rule example is shown in accompanying drawing 2.
Whether the sales volume of for example checking 201109 months certain tobacco company China cigarettes is normal.The historical sample data are the sales volume data of the said firm China cigarette 200801 months to 201108 month every months.It is 95%, 99% that threshold value is set.Analyze through model (shown in the accompanying drawing 3), according to the historical sales rule, 201109 months sales volume has in 99% the scope that possibly drop on [201.8,490.2] ten thousand, and 95% possibly drop in [230.3,470.5] scope arranged.If 201109 sales volume drop on [0,201.8] or [490.2 ,+∞) between; Then this brand sales situation need be paid close attention to, if drop on (201.8,230.3] with [470.5; 490.2) between, then this brand sales situation needs common concern, if drop on (230.3; 470.5) between, then this brand sales situation is normal.
Claims (2)
1. the Early-warning Model revised of enterprises supervisory systems oneself is characterized in that: adopt the thinking of filtrator, the annular circulative metabolism that has adopted forward, reverse formation is set in the filtration to filtrator; Filter for supervised entities and rank location according to the combination of filter condition, in onsite supervision, give and in various degree concern for supervised entities according to rank.
2. the Early-warning Model that a kind of inner supervisory systems oneself according to claim 1 revises, it is characterized in that: the condition that filtrator filters adopts probabilistic statistical method, comprises historical point view analysis and colony's angle analysis,
When historical point view was analyzed, according to the probability distribution that historical data is obeyed, (a b), judged that this secondary data is whether in fiducial interval to calculate the fiducial interval of M%;
During from colony's angle analysis, go out the average μ and the standard deviation sigma of this population data, judge that individual data is whether in [μ-3 σ, μ+3 σ] according to statistical computation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011103710352A CN102542356A (en) | 2011-11-21 | 2011-11-21 | Early alarming model for self repairing of enterprise internal supervision system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011103710352A CN102542356A (en) | 2011-11-21 | 2011-11-21 | Early alarming model for self repairing of enterprise internal supervision system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102542356A true CN102542356A (en) | 2012-07-04 |
Family
ID=46349201
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2011103710352A Pending CN102542356A (en) | 2011-11-21 | 2011-11-21 | Early alarming model for self repairing of enterprise internal supervision system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102542356A (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6003011A (en) * | 1998-01-07 | 1999-12-14 | Xerox Corporation | Workflow management system wherein ad-hoc process instances can be generalized |
| CN101996366A (en) * | 2010-12-08 | 2011-03-30 | 山东浪潮齐鲁软件产业股份有限公司 | Self-correcting early warning model for tobacco internal supervision system |
-
2011
- 2011-11-21 CN CN2011103710352A patent/CN102542356A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6003011A (en) * | 1998-01-07 | 1999-12-14 | Xerox Corporation | Workflow management system wherein ad-hoc process instances can be generalized |
| CN101996366A (en) * | 2010-12-08 | 2011-03-30 | 山东浪潮齐鲁软件产业股份有限公司 | Self-correcting early warning model for tobacco internal supervision system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ren et al. | Design of multi-information fusion based intelligent electrical fire detection system for green buildings | |
| Nayak et al. | Network mining techniques to analyze the risk of the occupational accident via bayesian network | |
| US9070121B2 (en) | Approach for prioritizing network alerts | |
| US20180182472A1 (en) | Method and system for a mobile health platform | |
| WO2007019451A3 (en) | Method and system for monitoring for and reporting of lien distress events | |
| US10909630B2 (en) | System and method for providing risk recommendation, mitigation and prediction | |
| US20210166197A1 (en) | System and method for providing risk recommendation, mitigation and prediction | |
| CN105096057A (en) | Supervision model system of power operation and corruption prevention | |
| CN103856339A (en) | Method and device for compressing alarm information | |
| CN104850913A (en) | Air quality PM2.5 predicating method and air quality PM2.5 predicating system | |
| Chongwatpol | Managing big data in coal-fired power plants: a business intelligence framework | |
| CN109559008A (en) | Construction monitoring method, apparatus and system | |
| WO2015126354A1 (en) | Risk assessment | |
| Yan et al. | Equitensors: Learning fair integrations of heterogeneous urban data | |
| Lee et al. | Enabling blockchain based scm systems with a real time event monitoring function for preemptive risk management | |
| Saleem et al. | Effects of disaster characteristics on twitter event signature | |
| Liu et al. | Modeling and performance analysis of gas leakage emergency disposal process in gas transmission station based on Stochastic Petri nets | |
| CN104579771B (en) | A kind of analysis method for the action trail that application system is published to user | |
| CN101996366A (en) | Self-correcting early warning model for tobacco internal supervision system | |
| US20190087903A1 (en) | System and computer-implemented method for multi-stage processing of sensor data | |
| Barbosa et al. | De-escalation technology: the impact of body-worn cameras on citizen-police interactions | |
| CN102542356A (en) | Early alarming model for self repairing of enterprise internal supervision system | |
| US20180010982A1 (en) | Engine performance modeling based on wash events | |
| CN110047167B (en) | Equivalent statistical method for sharp turn times of vehicle | |
| CN202218244U (en) | Information technology (IT) operation and maintenance system for business system monitoring |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20120704 |