CN104091226A - Information model quality evaluation method for operator OSS domain - Google Patents
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Abstract
The invention discloses an information model quality evaluation method for an operator OSS domain, and relates to an information model quality evaluation method based on network management. A complexity index and a coupling index in an information model are selected and respectively graded, and the comprehensive grade is obtained after the complexity index grade value and the coupling index grade value obtained through grading are added, wherein the larger the comprehensive grade value is, the higher the quality of the information model is. The evaluation method is completely suitable for objectively evaluating China telecom operators and is more objective due to the fact that no manual participation is needed in the evaluation process. The information model quality evaluation method plays a guide role in unified description, modeling management, resource data sharing standard optimization and operation supporting system optimization of network resource data of the telecom operators.
Description
Technical field
The present invention relates to the information model quality evaluation method of management Network Based, exactly relate to the information model quality evaluation method in a kind of operatable object business OSS territory.
Background technology
Flourish along with new generation network, the object of the required management of network management system becomes a complex gigantic system, and it is contained face and has comprised entity nearly all in network, such as network equipment, application program, server system etc.Management system itself is also complex gigantic system, between guard system and management system, is also had complicated relation simultaneously, and under such network management environment, it is a challenging job that network management information is carried out to modelling.And the quality of information model directly affects the information quality of network management, and further affect exploitation and the application of whole network management system.
Information model quality evaluation is one of main contents of network management basics research, and current network management and system also could not solve information model quality evaluation problem well.In the network management of new generation network, it is more outstanding that this problem will seem.This problem does not solve, and the many problems in the research of model for information about, exploitation and construction are all difficult to carry out.For example, lack index existing information model is evaluated, lack index and multiple information models are carried out to evaluation comparison be more suitable for coming into operation so which to be determined, lack index or method the modeling process of implementing is controlled etc.Can say, the current demand of information model quality evaluation study is very urgent, and meanwhile, this research also has larger theory value.
Operation support system (OSS), as a comprehensive service operation and management platform, has comprised network management system, is the indispensable part of sensing network operation situation.The evaluation method of the information model quality in OSS territory, has vital effect to the construction of operation support system.
Information model quality evaluation is tolerance and the evaluation and test of the system to information model entirety, and the optimization perfect, operation support system of information model is realized and being played an important role.So information model quality evaluation becomes a kind of necessary.It can be for:
(1) the integrated difficulty of the management system of the different Management Information Models of estimated service life: two Management Information Models are different in main subject area performance, use their system to be more difficult to integrated.Under certain situation, integrated will can realization hardly.
(2) be that known models case is selected a most suitable Management Information Model: appraisement system will provide a checklist, and whether the demand that it is used to find out particular model case can meet with alternative Management Information Model.
(3) for the design of Management Information Model provides a framework: by introducing one group of consistent term, and emphasize branch point potential between different Management Information Models, can help to build and new meet target and with other scheme Management Information Model more easy of integration.Appraisement system can be regarded as designing the masterplate of new administration information model, can strengthen again the model having existed simultaneously.From different visual angles, Evaluation Strategy has again following purposes: first, researcher wants have one better to understand to the characteristic of model, to classify and to improve its information model.Secondly, user wants to select corresponding Management Information Model evaluating as the instrument of practice.Again, model development person wants to understand the relative merits of various different models.By guiding, they design better network management information model for this.Finally, since do not have a kind of model to be all applicable to all situations, we just need to know when use a general model, when use again a concrete model.And the evaluation of information model is just for we provide the feasible way of integrating these information.
At present, the research of related network Management Information Model quality assessment is still in theoretical research stage.The evaluation method of related network Management Information Model quality mainly comprises following several:
1, TRS(Technical Review Session) method
The method is EURESCOM(European Institute for Research and Strategic Studies in Telecommunication, european telecommunication exploitation and Institute for Policy Studies-Transnational) evaluation TMN(Telecommunication Management Network, telecommunication management network) method of information model, it is evaluated from following viewpoint: grammer, ITU(International Telecommunications Union) advise X.722 and GDMO(Guidelines for Definition of Managed Objects, managed object definition guide) correct use, the reasonable intelligent use of GDMO, and the aspect such as the applicability of target.Wherein focus on the quality evaluating method towards GDMO.
2, the evaluation method based on GDMO
GDMO (Guidelines for Definition of Managed Objects) be one group for defining the standard of Management Information Model.External author Przemyslaw Czamecki, propose a set of standard of comparison with people such as Andrzej Jajszczyk based on GDMO framework and evaluated 3 Management Information Models (MIM) based on GDMO: NMF network model, ITU-TM.3100[104] model and ETSI GOM model, and analyze as an example with a simple SDH network.In this paper, propose an index system, formed by 24 indexs that are divided into A, B, C, D, five classifications of E, for the evaluation contrast of Management Information Model.
3, general evaluation model
Author Wu Gehan, Meng Luoming and Qiu Xuesong have delivered the periodical literature of " Network Management Information Models quality definition and evaluation model " on the periodical of periodical " Beijing University of Post & Telecommunication's journal " by name in Dec, 2003, wherein Network Management Information Models quality is defined, the index of quality assessment in quality model is disclosed, this information model quality appraisement system is divided into three grades (L1-L3), quality evaluating method is that each layer of all kinds of evaluation index value carried out comprehensively, finally forming comprehensive evaluation result.
4, towards the information model appraisement system of NGOSS
In conjunction with feature and the demand of operation support system of new generation, one in order to comprehensive, complete fuzzy comprehensive evaluation system, this assessment indicator system is deferred to NGOSS(New Generation Operations Systems and Software, operation system of new generation and software) 4 views: the satisfaction degree by service view evaluation and test information model for operation demand; System view completes the tolerance of model self character; Realize the validity of view for testing model, to realizing the support of aspect; Index of correlation when Deployment view evaluation operation.Can be from different views to the evaluation of information model, the selective dependency of the concrete final information model of operation system is in its emphasis.
5, body Evaluation Strategy
The people such as foreign scholar Wand and Weber have proposed to come by the concept of body the method for evaluation information model.They think should there is man-to-man mapping between this body frame and model architecture, and its basic concept is to evaluate existing methods framework by the coupling based on this body frame.Doing one of advantage of evaluating with ontology model is that at least it is to come from a solid theoretical foundation, there is certain versatility, but what emphasize is the grammer of information model, integrality and the sharpness of body, still lacks the successful assessment case of OSS information model combination.
6, AHP(Analytic Hierarchy Process, analytical hierarchy process)
A kind of decision-making technique of fixed guantity combining with fixed quality.It is by problem stratification, quantification, and the certain step of foundation obtains decision conclusions.
Above-mentioned several method, immediate with the application is the 3rd kind of method, still, the 3rd kind of method is not still suitable for the objective evaluation of Chinese operator network management information model, if directly apply the method, can have following technical matters:
(1), objective evaluation scarce capacity.A lot of indexs in this model are subjective index, that is: the evaluation procedure expert that need to be correlated with participates in, and evaluation score derives from expert's subjectivity marking, does not possess in actual applications the objective evaluation ability of automated analysis, Automation grade point.
(2), there is the conceptual index that is difficult to practical application.This model comprises some conceptual indexs, although that is: these evaluation indexes are defined, lacks the detailed design of evaluating detailed rules and regulations and code of points, does not possess in actual applications operability.
Summary of the invention
For solving the technical matters of above-mentioned prior art existing " the conceptual index that objective evaluation scarce capacity, existence are difficult to practical application ", the present invention proposes the information model quality evaluation method in a kind of operatable object business OSS territory, this evaluation method is applicable to the objective evaluation of Chinese Telecommunication Operator completely, this evaluation method is more objective, and evaluation procedure does not need artificial participation.For the network resource data of operator unified described, the optimization of the share standard of modelling management and resource data, operation support system realizes and plays directive function.
The present invention is by adopting following technical proposals to realize:
The information model quality evaluation method in a kind of operatable object business OSS territory, it is characterized in that: complexity profile and the coupling index chosen in information model are marked respectively, the complexity profile score value that scoring is obtained and coupling index score value obtain comprehensive grading after being added, and the quality of the higher descriptive information model of comprehensive grading score value is higher.
For multiple information models, respectively the comprehensive grading value of each information model gained to be compared, the high information model quality of marking is higher.
The scoring of described complexity profile is made up of four quality metrics, respectively: the redundance scoring of information model, the complexity scoring of all managed object classes in information model, the depth over width ratio scoring of the inheritance tree of information model, the degree of depth that comprises tree scoring with information model, after these four scorings are added, get average, obtain the scoring of described complexity profile.
Described inheritance tree refers to the diagrammatic representation of the inheritance between the managed object class of information model, and the tree structure that has the managed object class of inheritance to form, is the technical term in object-oriented;
Set the diagrammatic representation that refers to relation of inclusion between managed object class example described comprising, and is the technical term in object-oriented.
The concrete grammar of the redundance scoring of described information model is:
1) the ratio P of the managed object class quantity CC in computing information model Managed Resource quantity SC and information model, computing formula is:
Wherein, the part Internet resources that Managed Resource quantity SC is concerned about for management function, such as failure monitor function is paid close attention to router, switch etc. the network equipment; Equally, managed object class quantity CC utilizes the quantity of object-oriented method to the abstract object out of the related Internet resources of management function.The abstract method generally adopting is at present UML modeling, and UML specification, modeling process and modeling tool are technology existing and that generally apply, mostly adopt the modeling tools such as Rose, Managed Resource is defined as to object, and describes these objects in the mode of UML document.
2) computing formula of the redundance of information model scoring RS is as follows:
Whether the RS value obtaining there is redundancy for determination information model, and RS value is 0 or 1, if RS=1 illustrates that this information model exists redundancy, does not exist redundancy if instead RS=0 illustrates.
Because resource and object are two set, between object and resource, may not relation one to one, in the design of model, may have the object of redundancy, the account form of RS can judge whether administrative model exists redundancy substantially.
The concrete grammar of the complexity scoring of all managed object classes in described information model is:
By the element count of all n managed object class inside, obtain R
1, R
2..., R
n, be calculated as follows the complexity K of managed object class:
Wherein, R
irepresent i management object inner element and; D is variance, the modeling granularity that represents all managed object classes in information model whether substantially in same grade, i.e. dispersion degree; R is the average of n management object inner element, represents the modeling granularity degree of consistency; K is larger, and standard deviation more approaches the average level of management object, represents that the modeling granularity degree of consistency is better;
Described element comprises attribute, action and notice, and the complexity of described managed object class is modeling granularity consistance, and what modeling granularity referred to is exactly the member's of a class in object-oriented number, thinner more at most, is the technical term in object-oriented.
The concrete grammar of the depth over width ratio scoring of the inheritance tree of described information model is:
1) the depth over width ratio DB of calculating inheritance tree:
Wherein H represents the degree of depth of inheritance tree, and W represents the breadth extreme of inheritance tree;
2) getting a depth desired width suitable for user is 0.1-0.3 than the suggestion span of DBO(DBO), the depth over width ratio scoring DS of calculating inheritance tree:
The value of DS is for reacting the degree of closeness between calculated depth over width ratio and the desirable value of user, and thinks that it is unacceptable while exceeding the twice of desired value; DB represents the depth over width ratio of inheritance tree.
The concrete grammar of the degree of depth that the comprises tree scoring of described information model is:
The scoring ITS computing formula that comprises tree is as follows:
Wherein, n represents the degree of depth that comprises tree in information model, and D is that degree of depth optimal value (span is 1-5) is set in default comprising, and n is more close to D, and the degree of depth that comprises tree is more reasonable, and ITS scoring is higher; Otherwise it is far away that n departs from D, the degree of depth that explanation comprises tree is more unreasonable, and ITS scoring is lower.The value of ITS is for reacting the calculated degree of closeness comprising between the tree degree of depth and the value of default optimal value, and thinks that it is unacceptable while exceeding the twice of desired value.
After described four scorings are added, get average, the concrete formula that obtains the scoring of described complexity profile is:
Wherein: RS represents the redundance scoring of information model, K represents the complexity scoring of managed object class, and DS represents the depth over width ratio scoring of inheritance tree, and ITS represents the degree of depth that the comprises tree scoring of information model, and CS represents complexity profile scoring.
The scoring of described coupling index is made up of a quality metric, i.e. the degree of coupling between class, is the scoring of coupling index to the scoring of the degree of coupling between class, and its concrete grammar is:
1) find out the number RE of the managed object class relevant with certain managed object class;
The described relevant strong dependence referring between class, shows code aspect, and associated class B appears in association class A with the form of the attribute of class, or association class A has quoted a member variable that type is associated class B;
2) each managed object class in information model is adopted to step 1) method, obtain RE
1, RE
2... RE
n, represent degree of coupling value between overall class with R:
Wherein: REi represents in information model, the number of the managed object class relevant with i managed object class, n represents the total quantity of managed object class in information model.
R is the smaller the better, as follows to the score calculation method of the degree of coupling between class:
COS=1-R/n
Degree of coupling value between the overall class that wherein: the scoring of the degree of coupling between COS representation class is also the scoring of coupling index, and R is step 2) described formula calculates, n represents the total quantity of managed object class in information model.
The complexity profile score value that scoring is obtained and coupling index score value obtain comprehensive grading concrete formula after being added is:
COM=CS+COS
Wherein: COM represents comprehensive grading, CS represents complexity profile scoring, the scoring of COS coupling index.
Compared with prior art, the beneficial effect that the present invention reaches is as follows: 1, in the present invention, " complexity profile and the coupling index chosen in information model are marked respectively in employing, will scoring obtain complexity profile score value and coupling index score value be added after obtain comprehensive grading " mode, compared with prior art, specifically only select this two scorings of marking of complexity profile and coupling index, without remaining index, save operation steps, method is simpler, but result is really more objective and accurate, evaluation procedure does not need artificial participation, for the unified of network resource data of telecom operators described, the share standard of modelling management and resource data, the optimization of operation support system realizes and plays directive function.Be particularly useful for the objective evaluation of Chinese Telecommunication Operator, use the method can judge information model OK, for multiple models, the method can be selected individual best, again or be exactly design or when Optimized model, can be with reference to the Score index of the method, know from which side face and go design or optimize.
2, in the present invention, the scoring of complexity profile is made up of four quality metrics, the selection of these four quality metrics is the needs based on objective evaluation, that is: these four quality metrics are objective evaluation index, do not need subjective assessment, empirical learning or contrast reference model, can obtain evaluation result.Compared with existing other appraisement systems, more simple efficient, less to the dependence of external condition.
3, in the present invention, the scoring of coupling index is made up of a quality metric, i.e. the degree of coupling between class has two benefits like this: 1) using single quality metric as coupling index, and the tolerance result difference of having avoided multiple indexs to bring; 2) this quality metric is simple objective indicator, does not rely on other external conditions and initiatively evaluation procedure, more directly simple.
4,, in the present invention, except above-mentioned 3 advantages, can also effectively overcome ubiquitous in existing appraisement system " the conceptual index that objective evaluation scarce capacity, existence are difficult to practical application " problem.Adopting after this programme, is simple objective evaluation to the evaluation procedure of information model, without any need for manual intervention; Simultaneously the index in this programme is index that can practical operation, and algorithm is clear and definite, and according to this programme, developer can design automated information model evaluation software easily.
Embodiment
The present invention carries out comprehensive grading by representational two indexs in OSS information model being carried out to objectively calculating, and the quality of the higher descriptive information model of score value is higher; Plural information model is itemized relatively and scoring, and the high model quality of marking is higher.Indices concrete meaning and computing method are as follows:
(1) complexity profile scoring
The capacity of single managed object class in the complicacy of model and modeling granularity reflection information model.Whether the granularity that complicacy is intended to examine or check managed object class in information model is suitable, and the redundance of information, and this is to judge that information model is to the abstract whether rational key factor of management resource.Concrete quality metric has four.1-2 step is calculated redundance scoring, the 3rd step is calculated the complexity scoring of all managed object classes, the depth over width ratio scoring of the inheritance tree of 4-5 step computing information model, the degree of depth that the comprises tree scoring of the 6th step computing information model, the 7th step computational complexity comprehensive grading.
1) the ratio P of the managed object class quantity CC in computation model Managed Resource quantity SC and model.Computing formula is as follows:
Wherein, be managed the part internet resource that resource quantity SC is concerned about for management function, such as failure monitor function is paid close attention to router, switch etc. the network equipment.Equally, management object quantity CC utilizes the quantity of object-oriented method to the abstract object out of the related Internet resources of management function.
2) computing method of the redundance of information scoring RS are as follows:
Because resource and object are two set, between object and resource, may not relation one to one, in the design of model, may have the object of redundancy, the account form of RS can judge whether administrative model exists redundancy substantially.
3) by the element of all n managed object class inside (as attribute, action, notice etc.) counting, obtain R
1, R
2..., R
n, be calculated as follows complexity (the modeling granularity consistance) K of class:
Wherein, D represents variance, the modeling granularity that represents all managed object classes in information model whether substantially in same grade, i.e. dispersion degree.R represents the average of n management object inner element.Represent the modeling granularity degree of consistency, K larger (being the average level that standard deviation more approaches management object) represents that consistance is better.
4) the depth over width ratio DB of calculating inheritance tree (being the diagrammatic representation of inheritance between managed object class).
Wherein H represents the degree of depth of inheritance tree, and W represents the breadth extreme of inheritance tree.
5) get a depth over width ratio DB0(DBO=0.3 suitable for user) the scoring DS of calculating to its depth over width ratio:
DS has reflected the degree of closeness between depth-to-width ratio and the desirable value of user of calculating, and thinks that it is unacceptable while exceeding the twice of desired value.
6) calculate the degree of depth n that comprises tree (diagrammatic representation of relation of inclusion between managed object class example), and a suitable value D(D=5 for management resource and user's requirement), as follows to the score calculation method that comprises tree:
ITS has reflected the degree of closeness between the tree degree of depth and the desirable value of user that comprises of calculating, and thinks that it is unacceptable while exceeding the twice of desired value.
7) complicacy comprehensive grading account form is as follows:
It is the average of four tolerance in computational complexity index.
(2) coupling index scoring
An Important Thought of Object-Oriented Design is to pursue high cohesion, the low coupling of object class, and managed object class is no exception.Poly-degree of coupling of spending between interior poly-degree and the MOC that is intended to investigate MOC self in coupling.Concrete quality metric only has one at present: the degree of coupling between class, is the scoring of coupling index to the scoring of the degree of coupling between class.
Finding out relevant with certain managed object class (is the strong dependence between class, show code aspect, associated class B appears in association class A with the form of the attribute of class, may be also that association class A has quoted a member variable that type is associated class B) other classes (managed object class) number R;
Be that managed object class adopts method above to each MOC in information model, obtain RE
1, RE
2... RE
n, represent degree of coupling value between overall class with R,
Wherein: REi represents in information model, the number of the managed object class relevant with i managed object class, n represents the total quantity of managed object class in information model.
R is the smaller the better, as follows to the score calculation method of the degree of coupling between class:
COS=1-R/n
Comprehensive grading
Calculate comprehensive scoring according to following formula:
COM=CS+COS。
Wherein: COM represents comprehensive grading, CS represents complexity profile scoring, the scoring of COS coupling index.
Final scoring is more high better, and the method is selected the highest model of comprehensive grading.
Claims (10)
1. the information model quality evaluation method in an operatable object business OSS territory, it is characterized in that: complexity profile and the coupling index chosen in information model are marked respectively, the complexity profile score value that scoring is obtained and coupling index score value obtain comprehensive grading after being added, and the quality of the higher descriptive information model of comprehensive grading score value is higher.
2. the information model quality evaluation method in a kind of operatable object business OSS according to claim 1 territory, is characterized in that: for multiple information models, respectively the comprehensive grading value of each information model gained is compared, the high information model quality of marking is higher.
3. the information model quality evaluation method in a kind of operatable object business OSS according to claim 1 and 2 territory, it is characterized in that: the scoring of described complexity profile is made up of four quality metrics, respectively: the redundance scoring of information model, the complexity scoring of all managed object classes in information model, the depth over width ratio scoring of the inheritance tree of information model, the degree of depth that comprises tree scoring with information model, after these four scorings are added, get average, obtain the scoring of described complexity profile.
4. the information model quality evaluation method in a kind of operatable object business OSS according to claim 3 territory, is characterized in that: the concrete grammar of the redundance scoring of described information model is:
1) the ratio P of the managed object class quantity CC in computing information model Managed Resource quantity SC and information model, computing formula is:
Wherein, the part internet resource that Managed Resource quantity SC is concerned about for management function, managed object class quantity CC utilizes the quantity of object-oriented method to the abstract object out of the related Internet resources of management function;
2) computing formula of the redundance of information model scoring RS is as follows:
Whether the RS value obtaining there is redundancy for determination information model, and RS value is 0 or 1; RS=1, illustrates that this information model exists redundancy, and RS=0 illustrates and do not have redundancy.
5. the information model quality evaluation method in a kind of operatable object business OSS according to claim 3 territory, is characterized in that: the concrete grammar of the complexity scoring of all managed object classes in described information model is:
By the element count of all n managed object class inside, obtain R
1, R
2..., R
n, be calculated as follows the complexity K of managed object class:
Wherein, R
irepresent i management object inner element and; D is variance, the modeling granularity that represents all managed object classes in information model whether substantially in same grade, i.e. dispersion degree; R is the average of n management object inner element, represents the modeling granularity degree of consistency; K is larger, and standard deviation more approaches the average level of management object, represents that the modeling granularity degree of consistency is better;
Described element comprises attribute, action and notice, and the complexity of described managed object class is modeling granularity consistance, and what modeling granularity referred to is exactly the member's of a class in object-oriented number, thinner more at most.
6. the information model quality evaluation method in a kind of operatable object business OSS according to claim 3 territory, is characterized in that: the concrete grammar of the depth over width ratio scoring of the inheritance tree of described information model is:
1) the depth over width ratio DB of calculating inheritance tree:
Wherein H represents the degree of depth of inheritance tree, and W represents the breadth extreme of inheritance tree;
2) get a depth desired width suitable for user than DBO, the suggestion span of DBO is 0.1-0.3, calculates the depth over width ratio scoring DS of inheritance tree:
Degree of closeness between depth over width ratio and the desirable value of user that the value of DS is used for reacting calculated; DB represents the depth over width ratio of inheritance tree.
7. the information model quality evaluation method in a kind of operatable object business OSS according to claim 3 territory, is characterized in that: the concrete grammar of the degree of depth that the comprises tree scoring of described information model is:
The scoring ITS computing formula that comprises tree is as follows:
Wherein, n represents the degree of depth that comprises tree in information model, and D is that degree of depth optimal value is set in default comprising, and span is 1-5, and n is more close to D, and the degree of depth that comprises tree is more reasonable, and ITS scoring is higher; Otherwise it is far away that n departs from D, the degree of depth that explanation comprises tree is more unreasonable, and ITS scoring is lower; The value of ITS is for reacting the calculated degree of closeness between the tree degree of depth and the value of default optimal value that comprises.
8. the information model quality evaluation method in a kind of operatable object business OSS according to claim 3 territory, is characterized in that: after described four scorings are added, get average, the concrete formula that obtains the scoring of described complexity profile is:
Wherein: RS represents the redundance scoring of information model, K represents the complexity scoring of managed object class, and DS represents the depth over width ratio scoring of inheritance tree, and ITS represents the degree of depth that the comprises tree scoring of information model, and CS represents complexity profile scoring.
9. the information model quality evaluation method in a kind of operatable object business OSS according to claim 1 territory, it is characterized in that: the scoring of described coupling index is made up of a quality metric, it is the degree of coupling between class, the scoring of the degree of coupling between class is to the scoring of coupling index, its concrete grammar is:
1) find out the number RE of the managed object class relevant with certain managed object class;
The described relevant strong dependence referring between class, shows code aspect, and associated class B appears in association class A with the form of the attribute of class, or association class A has quoted a member variable that type is associated class B;
2) each managed object class in information model is adopted to step 1) method, obtain RE
1, RE
2... RE
n, represent degree of coupling value between overall class with R:
Wherein: REi represents in information model, the number of the managed object class relevant with i managed object class, n represents the total quantity of managed object class in information model;
R is the smaller the better, as follows to the score calculation method of the degree of coupling between class:
COS=1-R/n
Degree of coupling value between the overall class that wherein: the scoring of the degree of coupling between COS representation class is also the scoring of coupling index, and R is step 2) described formula calculates, n represents the total quantity of managed object class in information model.
10. the information model quality evaluation method in a kind of operatable object business OSS according to claim 1 territory, is characterized in that: the complexity profile score value that scoring is obtained and coupling index score value obtain comprehensive grading concrete formula after being added is:
COM=CS+COS
Wherein: COM represents comprehensive grading, CS represents complexity profile scoring, the scoring of COS coupling index.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105373881A (en) * | 2015-10-15 | 2016-03-02 | 大连海事大学 | Multi-index development coordination degree decision method |
| CN106878089A (en) * | 2017-03-15 | 2017-06-20 | 中国联合网络通信集团有限公司 | The evaluation method of business process, device and system |
| CN107274043A (en) * | 2016-04-07 | 2017-10-20 | 阿里巴巴集团控股有限公司 | Quality evaluating method, device and the electronic equipment of forecast model |
| CN107430398A (en) * | 2015-03-30 | 2017-12-01 | 环球油品公司 | System and method for tuning process modeling |
| US10534329B2 (en) | 2015-03-30 | 2020-01-14 | Uop Llc | System and method for improving performance of a plant with a furnace |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102387049A (en) * | 2011-11-25 | 2012-03-21 | 浪潮电子信息产业股份有限公司 | Cloud service quality evaluation method based on SNMP (simple network management protocol) |
-
2014
- 2014-06-17 CN CN201410268975.2A patent/CN104091226A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102387049A (en) * | 2011-11-25 | 2012-03-21 | 浪潮电子信息产业股份有限公司 | Cloud service quality evaluation method based on SNMP (simple network management protocol) |
Non-Patent Citations (1)
| Title |
|---|
| 吴格含等: "网络管理信息模型质量定义及评价模型", 《北京邮电大学学报》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107430398A (en) * | 2015-03-30 | 2017-12-01 | 环球油品公司 | System and method for tuning process modeling |
| US10534329B2 (en) | 2015-03-30 | 2020-01-14 | Uop Llc | System and method for improving performance of a plant with a furnace |
| CN107430398B (en) * | 2015-03-30 | 2020-12-15 | 环球油品公司 | System and method for tuning a process model |
| CN105373881A (en) * | 2015-10-15 | 2016-03-02 | 大连海事大学 | Multi-index development coordination degree decision method |
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