CN117076322A - Method and system for detecting abnormal working mode of research and development technology service provider - Google Patents
Method and system for detecting abnormal working mode of research and development technology service provider Download PDFInfo
- Publication number
- CN117076322A CN117076322A CN202311107338.2A CN202311107338A CN117076322A CN 117076322 A CN117076322 A CN 117076322A CN 202311107338 A CN202311107338 A CN 202311107338A CN 117076322 A CN117076322 A CN 117076322A
- Authority
- CN
- China
- Prior art keywords
- research
- service provider
- technical service
- development technical
- development
- 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
- 238000012827 research and development Methods 0.000 title claims abstract description 276
- 230000002159 abnormal effect Effects 0.000 title claims abstract description 150
- 238000000034 method Methods 0.000 title claims abstract description 55
- 238000005516 engineering process Methods 0.000 title claims description 41
- 238000001514 detection method Methods 0.000 claims abstract description 84
- 239000006185 dispersion Substances 0.000 claims abstract description 11
- 238000000605 extraction Methods 0.000 claims abstract description 11
- 238000007726 management method Methods 0.000 claims description 20
- 230000000694 effects Effects 0.000 claims description 13
- 238000004458 analytical method Methods 0.000 claims description 8
- 239000000725 suspension Substances 0.000 claims description 8
- 230000004931 aggregating effect Effects 0.000 claims description 6
- 238000011161 development Methods 0.000 claims description 5
- 230000002776 aggregation Effects 0.000 claims description 4
- 238000004220 aggregation Methods 0.000 claims description 4
- 230000008569 process Effects 0.000 description 26
- 238000013461 design Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000005856 abnormality Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 238000003066 decision tree Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000000513 principal component analysis Methods 0.000 description 2
- 238000003908 quality control method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3688—Test management for test execution, e.g. scheduling of test suites
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
- G06F18/2135—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/253—Fusion techniques of extracted features
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Quality & Reliability (AREA)
- Computer Hardware Design (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method and a system for detecting abnormal working modes of a research and development technical service provider, comprising the following steps: the method comprises the steps of collecting real-time information of an operation platform, a research and development system and communication software of a research and development technical service provider to be detected, and obtaining multi-dimensional working information of the research and development technical service provider; feature extraction is carried out on multi-dimensional working information of the research and development technical service provider to obtain a plurality of first feature data, and the first feature data are aggregated according to the dispersion between every two first feature data to obtain a plurality of second feature data for detecting abnormal working modes of the research and development technical service provider; and sending out an alarm signal when detecting that the research and development technical service provider is in an abnormal working mode. According to the method and the device, the relevance among the plurality of second characteristic data for detecting the abnormal working mode is reduced, so that the classification statistical flow of the second characteristic data is simplified, and the detection precision of the abnormal working mode is further improved.
Description
Technical Field
The invention relates to the field of quality control of research and development technical service providers, in particular to a method and a system for detecting abnormal working modes of the research and development technical service providers.
Background
The quality control of the existing research and development technology service provider is mainly realized by the following three conventional methods: firstly, determining service range and content according to early negotiated business contracts, technical SOW and other agreements; secondly, task disassembly is carried out according to the research and development flow to form WBS, and working tasks and acceptance criteria which are required to be completed by each milestone are defined; thirdly, the service acceptance is carried out on the delivery conditions of each stage of the milestone according to the service item checklist and acceptance criteria.
However, some developing technical service providers have a slow response and a progress arrest, which is liable to cause a risk of delay in the delivery, and need to recognize and take countermeasures as early as possible. However, continuous tracking and feedback cannot be quantified in the process only through protocols, systems, processes and acceptance of the soft skills, and the opaque condition of the process causes that data information cannot be collected to find problems in time, analyze reasons, discuss countermeasures, rationalize and improve and continuously iterate to form closed loop management.
Disclosure of Invention
The embodiment of the invention provides a method and a system for detecting an abnormal working mode of a research and development technical service provider, which are used for reducing the relevance among a plurality of second characteristic data for detecting the abnormal working mode after main characteristic extraction is completed so as to simplify the classification statistical flow of the second characteristic data, thereby improving the detection precision and the detection efficiency of the abnormal working mode.
In order to solve the above technical problems, an embodiment of the present invention provides a method for detecting an abnormal working mode of a research and development technical service provider, including:
the method comprises the steps of collecting real-time information of an operation platform, a research and development system and communication software of a research and development technical service provider to be detected, and obtaining multi-dimensional working information of the research and development technical service provider;
performing feature extraction on the multidimensional working information of the research and development technical service provider by adopting a main component analysis method to obtain a plurality of first feature data;
according to the dispersion degree between every two first characteristic data, the first characteristic data are aggregated to obtain a plurality of second characteristic data;
and detecting the abnormal working mode of the research and development technical service provider according to a preset abnormal working mode detection rule and a plurality of second characteristic data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal working mode.
According to the embodiment of the invention, the discrete operation platform, the research and development system and the communication software in the research and development technical service provider to be detected are subjected to real-time information acquisition to obtain the multi-dimensional work information of the research and development technical service provider, then the multi-dimensional work information of the research and development technical service provider is subjected to feature extraction to extract main features as a plurality of first feature data, the first feature data are aggregated according to the dispersion between every two first feature data, so that the dimensionality of the first feature data of the research and development technical service provider is reduced, the relevance between each second feature data is reduced, so that all the second feature data can be classified and counted more easily in the subsequent abnormal work mode detection process, the abnormal work mode detection of the research and development technical service provider is realized, and the detection precision and the detection efficiency of the abnormal work mode are improved. In addition, when detecting that the research and development technical service provider is in an abnormal working mode, an alarm signal is sent out so as to remind a user or a manager to correspondingly adjust the working mode, and problems of slow project progress, delay of a wrong exchange period and the like are avoided.
Preferably, the detecting a abnormal working mode of the developing technical service provider according to a preset abnormal working mode detecting rule and a plurality of second characteristic data of the developing technical service provider, and sending an alarm signal when detecting that the developing technical service provider is in the abnormal working mode, specifically includes:
acquiring the computer uploading data byte quantity and the computer downloading data byte quantity of staff in the research and development technical service provider in a first time period from a plurality of second characteristic data of the research and development technical service provider, and judging whether the computer uploading data byte quantity and the computer downloading data byte quantity of the staff in the first time period are both larger than a second threshold value;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode;
wherein the staff member includes at least one of a designer, a project management responsible person, and a project technology responsible person.
According to the preferred scheme of the embodiment of the invention, according to the data byte quantity uploaded by the computer and the data byte quantity downloaded by the computer in a first time period of staff in the research and development technical service provider, the resource use condition and the unscrupulous behavior of the research and development technical service provider are monitored, for example, when the computer is used for other staff remotely, a large amount of data is inquired/downloaded in a short time, and an alarm signal is sent out in time, so that information leakage is avoided.
Preferably, the detecting a abnormal working mode of the developing technical service provider according to a preset abnormal working mode detecting rule and a plurality of second characteristic data of the developing technical service provider, and sending an alarm signal when detecting that the developing technical service provider is in the abnormal working mode, specifically includes:
acquiring the computer keyboard use time and the computer screen locking time of a worker in the research and development technical service provider in a second time period from a plurality of second characteristic data of the research and development technical service provider, and judging whether the computer keyboard use time of the worker in the second time period is smaller than a third threshold or whether the computer screen locking time of the worker in the second time period is larger than a fourth threshold;
If yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode;
wherein the staff member includes at least one of a designer, a project management responsible person, and a project technology responsible person.
According to the preferred scheme of the embodiment of the invention, according to the computer keyboard using time and the computer screen locking time of the staff in the research and development technology service provider in the second time period, whether the staff designs and manages according to the original project plan is analyzed, so that the time waste is reduced, and the project process is effectively promoted.
Preferably, the detecting a abnormal working mode of the developing technical service provider according to a preset abnormal working mode detecting rule and a plurality of second characteristic data of the developing technical service provider, and sending an alarm signal when detecting that the developing technical service provider is in the abnormal working mode, specifically includes:
acquiring the total account number of the research and development technical service provider and the active account number of the research and development technical service provider in a third time period from a plurality of second characteristic data of the research and development technical service provider, and judging whether the ratio of the active account number to the total account number is smaller than a fifth threshold value;
If yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode.
According to the preferred scheme of the embodiment of the invention, according to the ratio of the number of the active accounts to the total number of accounts of the research and development technical service provider in the third time period, the account activity condition of the research and development technical service provider is analyzed, and when the ratio of the number of the active accounts to the total number of accounts of the research and development technical service provider in the third time period is smaller than a fifth threshold value, an alarm signal is sent out, so that the influence on the working progress caused by the fact that the number of the active accounts in the third time period is too small is prevented.
Preferably, the detecting a abnormal working mode of the developing technical service provider according to a preset abnormal working mode detecting rule and a plurality of second characteristic data of the developing technical service provider, and sending an alarm signal when detecting that the developing technical service provider is in the abnormal working mode, specifically includes:
obtaining the types of all EDA software and the use time of each EDA software used by the research and development technical service provider in the same time period from a plurality of second characteristic data of the research and development technical service provider, and analyzing to obtain the software activity gap between the research and development technical service provider and other research and development technical service providers according to the types of all EDA software and the use time of each EDA software used by the research and development technical service provider in the same time period and the use time of each EDA software used by other research and development technical service provider;
Judging whether the software activity gap between the research and development technical service provider and other research and development technical service providers is larger than a sixth threshold value;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode.
According to the preferred scheme of implementing the embodiment of the invention, according to the types of all EDA software and the use time of each EDA software used by the research and development technical service provider to be detected in the same time period, and the types of all EDA software and the use time of each EDA software used by other research and development technical service providers in the same time period, the software activity difference between the research and development technical service provider to be detected and other research and development technical service providers is analyzed, and an alarm signal is sent when the software activity difference between the research and development technical service provider to be detected and other research and development technical service providers is larger than a sixth threshold value so as to confirm the task execution curve difference and discharge the research and development technical service provider with slower research and development progress.
Preferably, the detecting a abnormal working mode of the developing technical service provider according to a preset abnormal working mode detecting rule and a plurality of second characteristic data of the developing technical service provider, and sending an alarm signal when detecting that the developing technical service provider is in the abnormal working mode, specifically includes:
acquiring the total working time length and the EDA software using time length of a designer in the research and development technical service provider from a plurality of second characteristic data of the research and development technical service provider, and judging whether the ratio of the EDA software using time length to the total working time length of the designer is smaller than a seventh threshold;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode.
According to the preferred scheme of the embodiment of the invention, according to the ratio of the time length of using EDA software by a designer in a research and development technical service provider to the total working time length, whether the designer uses the EDA software abnormally or not is analyzed, and an alarm signal is sent out when the ratio of the time length of using EDA software by the designer to the total working time length is smaller than a seventh threshold value, so that the designer is prevented from using wrong software in the working process, and the working gravity center of the designer is ensured not to deviate.
Preferably, the detecting a abnormal working mode of the developing technical service provider according to a preset abnormal working mode detecting rule and a plurality of second characteristic data of the developing technical service provider, and sending an alarm signal when detecting that the developing technical service provider is in the abnormal working mode, specifically includes:
acquiring the software task suspension duration of a designer in the research and development technical service provider from a plurality of second characteristic data of the research and development technical service provider, and judging whether the software task suspension duration of the designer is greater than an eighth threshold;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode.
When the software task suspension time of a designer in the research and development technical service provider is longer than the eighth threshold, the detection result is judged to be in an abnormal working mode of the research and development technical service provider, and an alarm signal is sent out so as to prevent the designer from forgetting the suspended software task, remind a project management responsible person, a project technical responsible person or other management personnel to re-evaluate the machine resource requirement or adjust the execution strategy, and ensure that the task cannot be normally executed due to insufficient server resources, thereby effectively promoting the working process.
Preferably, the detecting a abnormal working mode of the developing technical service provider according to a preset abnormal working mode detecting rule and a plurality of second characteristic data of the developing technical service provider, and sending an alarm signal when detecting that the developing technical service provider is in the abnormal working mode, specifically includes:
acquiring the conference participation times and conference participation time of staff in a research and development technical service provider in a fourth time period from a plurality of second characteristic data of the research and development technical service provider, and judging whether the conference participation times of the staff in the fourth time period are in a first interval range or whether the conference participation time of the staff in the fourth time period is in a second interval range;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode;
wherein the staff member includes at least one of a designer, a project management responsible person, and a project technology responsible person.
By implementing the preferred scheme of the embodiment of the invention, according to the conference participation times and conference participation time of staff in a research and development technology service provider in a fourth time period, whether the participation condition of the staff meets the preset project work requirement is analyzed, so that project information can not be updated in time due to too few participants and normal work time is influenced due to too many participants, and further, the influence on project work is reduced.
As a preferred solution, the method for detecting abnormal working modes of a research and development technical service provider further includes:
and when the research and development technical service provider is detected to be in the abnormal working mode, acquiring the reason that the research and development technical service provider is in the abnormal working mode, and optimizing and updating the abnormal working mode detection rule by utilizing the reason that the research and development technical service provider is in the abnormal working mode.
When the optimal scheme of the embodiment of the invention is implemented, the reason that the research and development technical service provider is in the abnormal working mode is obtained when the research and development technical service provider is detected to be in the abnormal working mode, and the detection rule is optimized and updated by utilizing the reason that the research and development technical service provider is in the abnormal working mode, so that the detection precision is further optimized.
In order to solve the same technical problem, the embodiment of the invention further provides a system for detecting abnormal working modes of a research and development technical service provider, which comprises:
the data acquisition module is used for acquiring real-time information of an operation platform, a research and development system and communication software of a research and development technical service provider to be detected to obtain multi-dimensional working information of the research and development technical service provider;
the feature extraction module is used for carrying out feature extraction on the multi-dimensional work information of the research and development technical service provider by adopting a main component analysis method to obtain a plurality of first feature data;
the aggregation module is used for aggregating the first characteristic data according to the dispersion degree between every two first characteristic data to obtain a plurality of second characteristic data;
the abnormal detection module is used for detecting the abnormal working mode of the research and development technical service provider according to a preset abnormal working mode detection rule and a plurality of second characteristic data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal working mode.
Drawings
Fig. 1: a flowchart of a method for detecting abnormal working modes of a research and development technical service provider is provided in the first embodiment of the present invention;
Fig. 2: a schematic flow chart of data acquisition and processing is provided for the first embodiment of the present invention;
fig. 3: a feedback logic diagram of a method for detecting abnormal working modes of a research and development technical service provider is provided for the first embodiment of the invention;
fig. 4: the first embodiment of the invention provides a structural schematic diagram of a detection system for abnormal working modes of a research and development technical service provider.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one:
referring to fig. 1, a method for detecting abnormal operation modes of a research and development technical service provider according to an embodiment of the present invention includes steps S1 to S3, which are specifically as follows:
step S1, collecting real-time information of an operation platform, a research and development system and communication software of a research and development technical service provider to be detected, and obtaining multi-dimensional working information of the research and development technical service provider.
It should be noted that, the operation platform, the development system and the communication software are used as information collection dimensions, so that the working information corresponding to the development technology service provider to be detected is obtained according to the actual requirements. Referring to fig. 2, through an operation platform, the data byte amount, the computer keyboard usage time and the computer screen locking time (the computer enters the screen locking state when the computer is not operated for 5 minutes) of a specified object in a provider network of a research and development technology service provider to be detected can be collected, and through real-time capturing of data of a research and development system (including research and development systems of various EDA software and project management software), information is collected in real time in communication software (a third party service system) such as a research and development conference system and a real-time communication tool, and then all the collected data is put into a data warehouse through a data access point. Additionally, referring to fig. 2 and 3, after the step S1 is performed to obtain the multi-dimensional work information of the research and development technical service provider to be detected, the method further includes preprocessing the multi-dimensional work information for data cleaning.
And S2, performing feature extraction on multi-dimensional work information of a research and development technical service provider to be detected by adopting a main component analysis method to obtain a plurality of first feature data.
In this embodiment, step S2 specifically includes extracting main features from multidimensional working information of a research and development technical service provider to be detected by using a Principal Component Analysis (PCA) method, and using the main features as a plurality of first feature data corresponding to the multidimensional working information.
And S3, aggregating the first characteristic data according to the dispersion degree between every two first characteristic data to obtain a plurality of second characteristic data.
In this embodiment, step S3 specifically includes analyzing all the first feature data by using a Linear Discriminant Analysis (LDA) method to determine a dispersion between every two first feature data, and aggregating two first feature data with a dispersion smaller than a first threshold value to obtain a plurality of second feature data.
Additionally, the use of office software may also be collected as another detection criterion for abnormal operation patterns. Specifically, the new number and the updated number of personal computer documents (including various document types) are counted in a unit of day, then related attribute information in the documents is extracted, information such as total editing time length, increase, decrease, change and the like of byte number is counted, then a current active window is extracted from an operating system, and document/page viewing time length is counted.
And S4, detecting an abnormal working mode of the research and development technical service provider to be detected according to a preset abnormal working mode detection rule and a plurality of second characteristic data of the research and development technical service provider to be detected, and sending an alarm signal when the research and development technical service provider to be detected is detected to be in the abnormal working mode.
It should be noted that, referring to fig. 3, after the alarm signal is sent, a specific abnormal cause needs to be confirmed by manual intervention. If the alarm signal is too many, the preset detection rule of the updating step S4 may need to be optimized according to the manually judged alarm true and false result. For example, the designer alarms abnormally according to the meeting quantity, the software use condition and the like, the information acquired by the leave system related to personnel is required to be confirmed, at the moment, no authority is required to acquire leave system data of the provider, and the provider lacks necessary information sources for leave and working time, so that the abnormal reasons can only be confirmed manually, and the detection result of the abnormal working mode can be caused by subjective reasons and objective task differences. In addition, according to a plurality of second characteristic data of the research and development technical service provider to be detected, the work activity and the work saturation of each worker in the research and development technical service provider to be detected can be analyzed.
As a preferable mode, step S4 includes steps S401 to S403, and each step is specifically as follows:
step S401, acquiring the computer uploading data byte quantity and the computer downloading data byte quantity of a worker in the research and development technical service provider to be detected in a first time period from a plurality of second characteristic data of the research and development technical service provider to be detected, and judging whether the computer uploading data byte quantity and the computer downloading data byte quantity of the worker in the first time period are both larger than a second threshold value; if yes, it indicates that the uploading/downloading data is excessive, and step S402 is executed; if not, step S403 is executed.
In a preferred aspect of the present embodiment, the staff member includes at least one of a designer, a project manager, and a project technology manager.
As an example, the second time period is one day.
Step S402, determining that the detection result is that the research and development technology service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
Step S403, determining that the detected result is that the research and development technical service provider to be detected is in the normal working mode.
As a preferable scheme, step S4 includes steps S404 to S406, and each step is specifically as follows:
Step S404, acquiring the computer keyboard use time and the computer screen locking time of the staff in the research and development technical service provider to be detected in a second time period from a plurality of second characteristic data of the research and development technical service provider to be detected, and judging whether the computer keyboard use time of the staff in the second time period is smaller than a third threshold or whether the computer screen locking time of the staff in the second time period is larger than a fourth threshold; if yes, go to step S405; if not, step S406 is performed.
In a preferred aspect of the present embodiment, the staff member includes at least one of a designer, a project manager, and a project technology manager.
As an example, the second time period is one day, the third threshold is 4 hours, and the fourth threshold is 2 hours.
It should be noted that, through the information such as the computer keyboard using time and the computer screen locking time, the basic work activity of each staff can be known, and then the human input state of the research and development technical service provider to be detected is confirmed.
Step S405, determining that the detected result is that the research and development technology service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
In step S406, it is determined that the detected result is that the research and development technical service provider to be detected is in the normal working mode.
As a preferable mode, step S4 includes steps S407 to S409, and each step is specifically as follows:
step S407, obtaining the total account number of the research and development technical service provider to be detected and the active account number of the research and development technical service provider to be detected in a third time period from a plurality of second characteristic data of the research and development technical service provider to be detected, and judging whether the ratio of the active account number to the total account number is smaller than a fifth threshold value; if yes, go to step S408; if not, step S409 is performed.
As an example, the third time period is one day and the fifth threshold is 80%.
Step S408, determining that the detected result is that the research and development technology service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
Step S409, determining that the detected result is that the research and development technology service provider to be detected is in the normal working mode.
As a preferable scheme, step S4 includes steps S410 to S413, and each step is specifically as follows:
step S410, obtaining the types of all EDA software and the use duration of all EDA software used by the research and development technical service providers to be detected in the same time period from a plurality of second characteristic data of all the research and development technical service providers to be detected, and analyzing to obtain the software activity gap between the research and development technical service providers to be detected and other research and development technical service providers according to the types of all EDA software and the use duration of all EDA software used by the research and development technical service providers to be detected in the same time period and the use duration of all EDA software used by other research and development technical service providers in the same time period.
Step S411, judging whether the software activity gap between the to-be-detected development technical service provider and other to-be-detected development technical service providers is greater than a sixth threshold; if yes, go to step S412; if not, step S413 is performed.
As an example, the sixth threshold is 30%.
Step S412, determining that the detected result is that the research and development technology service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
In step S413, it is determined that the research and development technology service provider to be detected is in the normal operation mode.
As a preferable scheme, step S4 includes steps S414 to S416, and each step is specifically as follows:
step S414, obtaining the total working time length of the designer and the EDA software using time length in the research and development technical service provider to be detected from a plurality of second characteristic data of the research and development technical service provider to be detected, and judging whether the ratio of the EDA software using time length to the total working time length of the designer is smaller than a seventh threshold; if yes, go to step S415; if not, step S416 is performed.
As an example, the seventh threshold is 60%. If the designer uses the corresponding EDA software time rate is too low (e.g., less than 60% of the operating time period) an alarm needs to be issued to confirm the cause.
It should be noted that, according to the design flow, different task roles (designers with different job levels, project management responsible persons and project technology responsible persons) use different EDA software at different stages, so that the types and durations of software used by the research and development technical service provider to be detected and other research and development technical service providers in the same time period can be compared, and therefore, the situation of confirming the task execution curve is compared, and if a large gap exists, rationality needs to be analyzed to confirm whether delay risks exist.
Step S415, determining that the detected result is that the research and development technology service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
Step S416, determining that the detected result is that the developing technical service provider to be detected is in the normal working mode.
As a preferable mode, step S4 includes steps S417 to S419, and each step is specifically as follows:
step S417, obtaining the software task suspension duration of the designer in the research and development technical service provider to be detected from a plurality of second feature data of the research and development technical service provider to be detected, and judging whether the software task suspension duration of the designer is greater than an eighth threshold; if yes, go to step S418; if not, step S419 is performed.
As an example, the eighth threshold is 18 hours. When the software task is suspended for too long (for example, more than 18 hours), an alarm prompt needs to be sent out, so that a project management responsible person, a project technology responsible person or other management personnel can confirm whether the task is executed abnormally (for example, the resource is insufficient or the like), whether intervention is needed, an execution strategy is adjusted or the like.
Step S418, determining that the detected result is that the research and development technology service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
In step S419, it is determined that the detected result is that the research and development technical service provider to be detected is in the normal operation mode.
As a preferable scheme, step S4 includes steps S420 to S422, and each step is specifically as follows:
step S420, acquiring the conference participation times and conference participation time of the staff in the research and development technical service provider to be detected in a fourth time period from a plurality of second characteristic data of the research and development technical service provider to be detected, and judging whether the conference participation times of the staff in the fourth time period are in a first interval range or whether the conference participation time of the staff in the fourth time period is in a second interval range; if yes, go to step S421; if not, step S422 is performed.
As an example, if the staff is a designer, the fourth time period is one week, the first interval range is an open interval (5, ++), and the second interval range is an open interval (8 hours, ++). If the number of meetings a designer takes into within a week is excessive (e.g., more than 5 meetings a week) or the duration is excessive (e.g., more than 8 hours a week), an alarm needs to be raised to confirm the necessity of the meeting and whether the progress of the design effort is affected.
As another example, if the staff member is a project management responsible person or a project technology responsible person, the fourth time period is one week, and the first interval range is a closed interval [0,1]. If the number of conferences attended by the project management responsible person or the project technology responsible person is too small (for example, less than 2 conferences per week), it is also necessary to confirm whether there is a situation of insufficient communication.
In addition, the real-time information collection is carried out on the communication software, the number of times of meeting participation and the duration of meeting participation of the staff in the research and development technology service provider to be detected in the fourth time period can be obtained, the information quantity replied by the staff on the communication software can be obtained, and the information processing quantity of the staff is obtained through analysis according to the information quantity replied by the staff on the communication software and is used as another detection standard of the abnormal working mode.
In a preferred embodiment of the present embodiment, the staff includes a designer, a project manager, and a project technology manager.
Step S421, determining that the detected result is that the research and development technical service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
Step S422, determining that the detected result is that the developing technical service provider to be detected is in the normal working mode.
In this embodiment, step S4 may be performed by using a decision tree and a K-means. As a specific implementation process of this embodiment, various preferred schemes corresponding to step S4 are associated, and a decision tree is adopted, when the detection result of the preferred scheme is that the research and development technical service provider to be detected is in a normal working mode, the next preferred scheme is executed until all the preferred schemes corresponding to step S4 are executed, so that whether each item of second feature data of the research and development technical service provider to be detected meets the preset requirement can be sequentially judged, and daily supervision management and modification of the research and development technical service provider are realized. The process comprises the steps 1) to 15), and the steps are specifically as follows:
step 1), after step S1 to step S3 are performed, step S401 is performed.
Step 2), in the process of executing step S401, if the byte amount of data uploaded by the computer and the byte amount of data downloaded by the computer in one day are both greater than the second threshold, determining that the detection result is that the research and development technology service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
Step 3), in the process of executing step S401, if the byte amount of the computer uploading data and the byte amount of the computer downloading data of the staff in one day are not both greater than the second threshold, determining that the detection result is that the research and development technology service provider to be detected is in the normal working mode, and continuing to execute step S404.
Step 4), in the process of executing step 404, if the time of using the computer keyboard in one day is less than 4 hours or the time of locking the computer screen in one day is more than 2 hours, determining that the detection result is that the research and development technical service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
Step 5), in the process of executing step S404, if the time of using the computer keyboard by the staff in one day is not less than 4 hours and the time of locking the computer screen by the staff in one day is not more than 2 hours, determining that the detection result is that the research and development technical service provider to be detected is in a normal working mode, and continuing to execute step S407.
Step 6), in the process of executing step 407, if the ratio of the number of active accounts to the number of total accounts is less than 80%, determining that the detection result is that the research and development technical service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
Step 7), in the process of executing step S407, if the ratio of the number of active accounts to the total number of accounts is not less than 80%, determining that the detection result is that the research and development technical service provider to be detected is in the normal working mode, and continuing to execute step S410.
Step 8), in the process of executing step S410, if the software activity gap between the research and development technical service provider to be detected and other research and development technical service providers to be detected is greater than 30%, determining that the detection result is that the research and development technical service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
Step 9), in the process of executing step S410, if the software activity gap between the research and development technical service provider to be detected and other research and development technical service providers to be detected is not greater than 30%, determining that the detection result is that the research and development technical service provider to be detected is in the normal working mode, and continuing to execute step S414.
Step 10), in the process of executing step S414, if the ratio of the duration of using EDA software to the total duration of work of the designer is less than 60%, determining that the detection result is that the research and development technology service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
Step 11), in the process of executing step S414, if the ratio of the duration of use of the EDA software by the designer to the total duration of work is not less than 60%, it is determined that the detected result is that the research and development technology service provider to be detected is in the normal working mode, and step S417 is continuously executed.
Step 12), in the process of executing step S417, if the software task of the designer is suspended for longer than 18 hours, then it is determined that the detection result is that the research and development technical service provider to be detected is in an abnormal working mode, and an alarm signal is sent out.
Step 13), in the process of executing step S417, if the software task suspension duration of the designer is not greater than 18 hours, then it is determined that the detection result is that the research and development technical service provider to be detected is in the normal working mode, and step S420 is continuously executed.
Step 14), in the process of executing step S420, if the number of times of participation of the designer in the conference in a week is greater than 5 times or the time of participation of the designer in the conference in a week is greater than 8 hours, determining that the detection result is that the research and development technical service provider to be detected is in an abnormal working mode, and sending out an alarm signal.
Step 15), in the process of executing step S420, if the number of times of meeting participation of the designer in a week is not more than 5 times and the duration of meeting participation of the designer in a week is not more than 8 hours, judging whether the number of times of meeting participation of the project management responsible person and the project technology responsible person in a week is more than 5 times or whether the duration of meeting participation of the designer in a week is more than 8 hours; if the number of times of meeting participation of the project management responsible person or the project technology responsible person in a week is more than 5 times or the number of times of meeting participation of the project management responsible person or the project technology responsible person in a week is more than 8 hours, judging that the detection result is that the research and development technology service provider to be detected is in an abnormal working mode, and sending an alarm signal; if the number of times of meeting participation of the project management responsible person and the project technology responsible person in a week is not more than 5 times, and the duration of meeting participation of the project management responsible person and the project technology responsible person in a week is not more than 8 hours, judging that the detection result is that the research and development technology service provider to be detected is in a normal working mode, and indicating that the research and development technology service provider to be detected is generally normal.
As a preferred solution, the method for detecting abnormal working modes of a research and development technical service provider to be detected provided by the embodiment of the present invention further includes step S5, where the step is specifically as follows:
Step S5, referring to fig. 3, when any one of the to-be-detected research and development technical service providers is detected to be in the abnormal working mode, the cause (i.e., the evaluation result) of the to-be-detected research and development technical service provider in the abnormal working mode is obtained, and the detection rule is optimized and updated (i.e., feedback improvement) by using the cause of the to-be-detected research and development technical service provider in the abnormal working mode.
Referring to fig. 2, a schematic structural diagram of a system for detecting abnormal working modes of a research and development technical service provider to be detected according to an embodiment of the present invention includes a data acquisition module M1, a data analysis module M2, an aggregation module M3, and an abnormality detection module M4, where each module is specifically as follows:
the data acquisition module M1 is used for respectively carrying out real-time information acquisition on the operation platforms, the research and development systems and the communication software of all research and development technical service providers to be detected to obtain multi-dimensional work information of the research and development technical service providers to be detected;
the data analysis module M2 is used for carrying out feature extraction on multi-dimensional work information of a research and development technical service provider to be detected by adopting a main component analysis method to obtain a plurality of first feature data;
The aggregation module M3 is used for aggregating the first characteristic data according to the dispersion degree between every two first characteristic data to obtain a plurality of second characteristic data;
the abnormality detection module M4 is configured to detect an abnormal working mode of the research and development technical service provider to be detected according to a preset abnormal working mode detection rule and a plurality of second feature data of the research and development technical service provider to be detected, and send an alarm signal when detecting that the research and development technical service provider to be detected is in the abnormal working mode.
It will be clear to those skilled in the art that, for convenience and brevity of description, reference may be made to the corresponding process in the foregoing method embodiment for the specific working process of the above-described system, which is not described herein again.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
the invention provides a method and a system for detecting abnormal working modes of a research and development technical service provider, which are used for acquiring information of discrete operation platforms, a research and development system and communication software in real time in the research and development technical service provider to be detected so as to obtain multi-dimensional working information of the research and development technical service provider, extracting characteristics of the multi-dimensional working information of the research and development technical service provider to extract main characteristics, aggregating the first characteristic data according to the dispersion between every two first characteristic data, reducing the dimension of the first characteristic data of the research and development technical service provider, and reducing the relevance between every two second characteristic data, so that classification statistics can be carried out on all the second characteristic data in the subsequent abnormal working mode detection process more easily, and the abnormal working mode detection of the research and development technical service provider is realized, thereby improving the detection precision and the detection efficiency of the abnormal working mode. In addition, when detecting that the research and development technical service provider is in an abnormal working mode, an alarm signal is sent out so as to remind a user or a manager to correspondingly adjust the working mode, and problems of slow project progress, delay of a wrong exchange period and the like are avoided.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are not to be construed as limiting the scope of the invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.
Claims (10)
1. A method for detecting abnormal operation modes of a research and development technical service provider, comprising the steps of:
the method comprises the steps of collecting real-time information of an operation platform, a research and development system and communication software of a research and development technical service provider to be detected, and obtaining multi-dimensional working information of the research and development technical service provider;
performing feature extraction on the multidimensional working information of the research and development technical service provider by adopting a main component analysis method to obtain a plurality of first feature data;
according to the dispersion degree between every two first characteristic data, the first characteristic data are aggregated to obtain a plurality of second characteristic data;
and detecting the abnormal working mode of the research and development technical service provider according to a preset abnormal working mode detection rule and a plurality of second characteristic data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal working mode.
2. The method for detecting abnormal operation mode of a research and development technical service provider according to claim 1, wherein the detecting abnormal operation mode of the research and development technical service provider according to the preset abnormal operation mode detection rule and the second feature data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal operation mode, specifically comprises:
acquiring the computer uploading data byte quantity and the computer downloading data byte quantity of staff in the research and development technical service provider in a first time period from a plurality of second characteristic data of the research and development technical service provider, and judging whether the computer uploading data byte quantity and the computer downloading data byte quantity of the staff in the first time period are both larger than a second threshold value;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode;
wherein the staff member includes at least one of a designer, a project management responsible person, and a project technology responsible person.
3. The method for detecting abnormal operation mode of a research and development technical service provider according to claim 1, wherein the detecting abnormal operation mode of the research and development technical service provider according to the preset abnormal operation mode detection rule and the second feature data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal operation mode, specifically comprises:
acquiring the computer keyboard use time and the computer screen locking time of a worker in the research and development technical service provider in a second time period from a plurality of second characteristic data of the research and development technical service provider, and judging whether the computer keyboard use time of the worker in the second time period is smaller than a third threshold or whether the computer screen locking time of the worker in the second time period is larger than a fourth threshold;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode;
Wherein the staff member includes at least one of a designer, a project management responsible person, and a project technology responsible person.
4. The method for detecting abnormal operation mode of a research and development technical service provider according to claim 1, wherein the detecting abnormal operation mode of the research and development technical service provider according to the preset abnormal operation mode detection rule and the second feature data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal operation mode, specifically comprises:
acquiring the total account number of the research and development technical service provider and the active account number of the research and development technical service provider in a third time period from a plurality of second characteristic data of the research and development technical service provider, and judging whether the ratio of the active account number to the total account number is smaller than a fifth threshold value;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode.
5. The method for detecting abnormal operation mode of a research and development technical service provider according to claim 1, wherein the detecting abnormal operation mode of the research and development technical service provider according to the preset abnormal operation mode detection rule and the second feature data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal operation mode, specifically comprises:
obtaining the types of all EDA software and the use time of each EDA software used by the research and development technical service provider in the same time period from a plurality of second characteristic data of the research and development technical service provider, and analyzing to obtain the software activity gap between the research and development technical service provider and other research and development technical service providers according to the types of all EDA software and the use time of each EDA software used by the research and development technical service provider in the same time period and the use time of each EDA software used by other research and development technical service provider;
Judging whether the software activity gap between the research and development technical service provider and other research and development technical service providers is larger than a sixth threshold value;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode.
6. The method for detecting abnormal operation mode of a research and development technical service provider according to claim 1, wherein the detecting abnormal operation mode of the research and development technical service provider according to the preset abnormal operation mode detection rule and the second feature data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal operation mode, specifically comprises:
acquiring the total working time length and the EDA software using time length of a designer in the research and development technical service provider from a plurality of second characteristic data of the research and development technical service provider, and judging whether the ratio of the EDA software using time length to the total working time length of the designer is smaller than a seventh threshold;
If yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode.
7. The method for detecting abnormal operation mode of a research and development technical service provider according to claim 1, wherein the detecting abnormal operation mode of the research and development technical service provider according to the preset abnormal operation mode detection rule and the second feature data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal operation mode, specifically comprises:
acquiring the software task suspension duration of a designer in the research and development technical service provider from a plurality of second characteristic data of the research and development technical service provider, and judging whether the software task suspension duration of the designer is greater than an eighth threshold;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode.
8. The method for detecting abnormal operation mode of a research and development technical service provider according to claim 1, wherein the detecting abnormal operation mode of the research and development technical service provider according to the preset abnormal operation mode detection rule and the second feature data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal operation mode, specifically comprises:
acquiring the conference participation times and conference participation time of staff in a research and development technical service provider in a fourth time period from a plurality of second characteristic data of the research and development technical service provider, and judging whether the conference participation times of the staff in the fourth time period are in a first interval range or whether the conference participation time of the staff in the fourth time period is in a second interval range;
if yes, judging that the detection result is that the research and development technical service provider is in an abnormal working mode, and sending out an alarm signal;
if not, judging that the detection result is that the research and development technical service provider is in a normal working mode;
Wherein the staff member includes at least one of a designer, a project management responsible person, and a project technology responsible person.
9. The method for detecting abnormal operation patterns of a development technical service provider according to claim 1, further comprising:
and when the research and development technical service provider is detected to be in the abnormal working mode, acquiring the reason that the research and development technical service provider is in the abnormal working mode, and optimizing and updating the abnormal working mode detection rule by utilizing the reason that the research and development technical service provider is in the abnormal working mode.
10. A research and development technical service provider abnormal operation pattern detection system, comprising:
the data acquisition module is used for acquiring real-time information of an operation platform, a research and development system and communication software of a research and development technical service provider to be detected to obtain multi-dimensional working information of the research and development technical service provider;
the feature extraction module is used for carrying out feature extraction on the multi-dimensional work information of the research and development technical service provider by adopting a main component analysis method to obtain a plurality of first feature data;
the aggregation module is used for aggregating the first characteristic data according to the dispersion degree between every two first characteristic data to obtain a plurality of second characteristic data;
The abnormal detection module is used for detecting the abnormal working mode of the research and development technical service provider according to a preset abnormal working mode detection rule and a plurality of second characteristic data of the research and development technical service provider, and sending an alarm signal when detecting that the research and development technical service provider is in the abnormal working mode.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311107338.2A CN117076322A (en) | 2023-08-30 | 2023-08-30 | Method and system for detecting abnormal working mode of research and development technology service provider |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311107338.2A CN117076322A (en) | 2023-08-30 | 2023-08-30 | Method and system for detecting abnormal working mode of research and development technology service provider |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117076322A true CN117076322A (en) | 2023-11-17 |
Family
ID=88715107
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311107338.2A Pending CN117076322A (en) | 2023-08-30 | 2023-08-30 | Method and system for detecting abnormal working mode of research and development technology service provider |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117076322A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101362451B1 (en) * | 2013-03-20 | 2014-02-12 | 국방과학연구소 | Method and device for determining a kind of land mind based on various characteristics |
| CN108309284A (en) * | 2018-03-15 | 2018-07-24 | 广州视源电子科技股份有限公司 | Electrocardiogram T wave end point detection method and device |
| CN108664603A (en) * | 2018-05-09 | 2018-10-16 | 北京奇艺世纪科技有限公司 | A kind of method and device of abnormal polymerization value that repairing time series data |
| CN111175626A (en) * | 2020-03-20 | 2020-05-19 | 广东电网有限责任公司 | Abnormal detection method for insulation state of switch cabinet |
| CN115603955A (en) * | 2022-09-26 | 2023-01-13 | 北京百度网讯科技有限公司（Cn） | Abnormal access object identification method, device, equipment and medium |
| CN116304910A (en) * | 2023-03-15 | 2023-06-23 | 中国工商银行股份有限公司 | Anomaly detection method, device, equipment and storage medium for operation and maintenance data |
-
2023
- 2023-08-30 CN CN202311107338.2A patent/CN117076322A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101362451B1 (en) * | 2013-03-20 | 2014-02-12 | 국방과학연구소 | Method and device for determining a kind of land mind based on various characteristics |
| CN108309284A (en) * | 2018-03-15 | 2018-07-24 | 广州视源电子科技股份有限公司 | Electrocardiogram T wave end point detection method and device |
| CN108664603A (en) * | 2018-05-09 | 2018-10-16 | 北京奇艺世纪科技有限公司 | A kind of method and device of abnormal polymerization value that repairing time series data |
| CN111175626A (en) * | 2020-03-20 | 2020-05-19 | 广东电网有限责任公司 | Abnormal detection method for insulation state of switch cabinet |
| CN115603955A (en) * | 2022-09-26 | 2023-01-13 | 北京百度网讯科技有限公司（Cn） | Abnormal access object identification method, device, equipment and medium |
| CN116304910A (en) * | 2023-03-15 | 2023-06-23 | 中国工商银行股份有限公司 | Anomaly detection method, device, equipment and storage medium for operation and maintenance data |
Non-Patent Citations (1)
| Title |
|---|
| 纪素娟;: "基于主成分分析法的异常数据检测及其应用", 教育教学论坛, no. 02 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109102145B (en) | Process orchestration | |
| US20120054136A1 (en) | System And Method For An Auto-Configurable Architecture For Managing Business Operations Favoring Optimizing Hardware Resources | |
| CN106528850B (en) | Gate inhibition's data exception detection method based on machine learning clustering algorithm | |
| CN106708738B (en) | Software test defect prediction method and system | |
| CN112907356A (en) | Overdue collection method, device and system and computer readable storage medium | |
| CN107977855B (en) | Method and device for managing user information | |
| CN112464818A (en) | Kitchen supervision method, device, equipment and storage medium | |
| CN115719139A (en) | Dispatching self-checking system for power grid dispatching operation management | |
| US20170300837A1 (en) | Business operation evaluation system | |
| CN113421168B (en) | Intelligent machining system for mechanical basic parts | |
| CN111428963B (en) | Data processing method and device | |
| CN117787941A (en) | Conference room use optimization method based on intelligent office | |
| CN117076322A (en) | Method and system for detecting abnormal working mode of research and development technology service provider | |
| WO2024036727A1 (en) | Data anomaly detection method and apparatus, device, medium, and program product | |
| CN112712270B (en) | Information processing method, device, equipment and storage medium | |
| CN114596162A (en) | Intelligent carbon transaction service management system and method | |
| CN114140241A (en) | Abnormity identification method and device for transaction monitoring index | |
| CN109359825B (en) | Bank digital operation product value analysis method | |
| CN113676356A (en) | Alarm information processing method and device, electronic equipment and readable storage medium | |
| CN112463801A (en) | Report form pushing method and device, terminal equipment and storage medium | |
| CN101605339A (en) | Monitoring of network bandwidth resources operating position and prompt system and method | |
| CN117522418B (en) | Student information data management system and method based on SaaS mode | |
| CN117278948B (en) | System and method for discriminating short message type of enterprise short message | |
| CN117745110B (en) | Intelligent campus restaurant operation management and control method and system based on behavior analysis | |
| US20220366462A1 (en) | Recommendation system, and product recommendation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |