CN112732544A - Computer hardware adaptation intelligent analysis system - Google Patents
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- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
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Abstract
The invention relates to a computer hardware adaptation intelligent analysis system, which comprises a load analysis subsystem, a local management subsystem and a hardware selection subsystem, wherein the computer hardware adaptation intelligent analysis system is configured with an application information base, a hardware information base and an associated information base; the local management subsystem can acquire, associate and manage local application and hardware information, can acquire the use habits of users and the requirements of the users on the hardware in the actual operation process, and the load analysis subsystem is used for detecting the load condition of each user terminal.
Description
Technical Field
The invention relates to the technical field of computer data, in particular to an intelligent analysis system for computer hardware adaptation.
Background
The computer is commonly called computer, and is a modern electronic computing machine for high-speed computation, which can perform numerical computation, logic computation and memory function. The intelligent electronic device can be operated according to a program, and can automatically process mass data at a high speed.
A computer that is composed of a hardware system and a software system and does not have any software installed is called a bare metal. The computer can be divided into a super computer, an industrial control computer, a network computer, a personal computer and an embedded computer, and more advanced computers comprise a biological computer, a photon computer, a quantum computer and the like.
With the continuous entering of computers into home scenes and the development of various applications, hardware requirements of users for the computers are higher and are more and more diversified, and if the users do not know each type of hardware, the users are difficult to select a proper machine type, especially the requirements of the users are different, and the required office environments are greatly different, so that only equipment higher than the actual requirements of the users can be purchased, or the applications cannot run efficiently due to a single or a plurality of hardware modules.
Disclosure of Invention
In view of the above, the present invention provides a computer hardware adaptation intelligent analysis system to solve the above problems.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a computer hardware adaptation intelligent analysis system comprises a load analysis subsystem, a local management subsystem and a hardware selection subsystem, wherein the computer hardware adaptation intelligent analysis system is configured with an application information base, a hardware information base and an associated information base; the application information base stores application information, the hardware information base stores hardware information, the hardware information comprises a plurality of hardware data under different hardware types, each hardware data corresponds to hardware load capacity data, the hardware load capacity data reflects the load capacity corresponding to the hardware, the association information base stores association information, and the association information reflects the requirement of the application corresponding to the application information on the hardware information;
the local management subsystem is configured with a local application database and a local hardware database, the local application database stores a plurality of local application data, the local application data corresponds to the application generation of the user terminal, the local hardware database stores a plurality of local hardware data, and the local hardware data corresponds to the hardware generation of the user terminal; the local management subsystem is configured with an application updating module and a hardware updating module, wherein the application updating module is used for detecting an application updating action of the user terminal, generating corresponding local application data according to an application updating result and storing the local application data in a local application database; the hardware updating module is used for detecting the hardware updating action of the user terminal, generating corresponding local hardware data according to the hardware updating result and storing the local hardware data into a local hardware database;
the load analysis subsystem is configured with an information load analysis strategy and an actual load monitoring strategy, the load analysis subsystem is configured with a load association database, the load association database stores a plurality of load association data, and the load association data takes local application data and local hardware data as indexes; the load analysis strategy comprises the steps of obtaining a theoretical load associated value of each corresponding local hardware data according to local application data, generating the theoretical load associated value from corresponding associated information in the associated information base, and generating initial load associated data according to the theoretical associated value; the actual load monitoring strategy is configured with a hardware load sub-strategy and an abnormal monitoring sub-strategy, the hardware load sub-strategy detects the hardware load state in the application running process in real time and generates a corresponding hardware actual measurement load value, and updates corresponding load associated data according to the hardware actual measurement load value, the abnormal monitoring sub-strategy receives running abnormal information generated by a computer, generates a corresponding hardware abnormal load value according to the running abnormal information, and updates the corresponding load associated data according to the hardware abnormal load value;
the hardware selection subsystem is configured with a hardware selection strategy, the hardware selection strategy comprises a load obtaining step, a load calculating step and a hardware selection step, the load obtaining step comprises obtaining load relevant data corresponding to each type of hardware according to application information corresponding to the user to generate a load difference value, the load calculating step comprises calling hardware load capacity data corresponding to the hardware from the hardware information base and generating a hardware load requirement value according to the hardware load capacity data and the load difference value, and the hardware selection step selects hardware data, of which the hardware load capacity data meets the hardware load requirement value, from the hardware information base according to the hardware load requirement value and outputs the hardware data.
Further, the computer hardware adaptation intelligent analysis system is configured with a hardware load updating strategy, the hardware load updating strategy is configured with local load updating conditions, and when load associated data corresponding to any local terminal meets the local load updating conditions, the hardware load capacity data is updated according to the load associated data.
Further, in the hardware information base, a value burden value and a life bearing value are configured for each piece of hardware data, the value burden value reflects a price of hardware corresponding to the hardware data, the life bearing value reflects a life of the hardware, and in the hardware calculation step, the corresponding hardware data is determined according to a value threshold and a life threshold which are input by a user in advance.
The method comprises the steps of obtaining application information to be updated from an application information base, obtaining corresponding association information from the association information base according to the application information, determining corresponding hardware load capacity data according to the association information, calculating an update load difference value according to the obtained hardware load capacity data and local load association data, and outputting configuration abnormal information according to the update load difference value if the obtained update load difference value is larger than a preset first load threshold value.
Furthermore, a career association database is configured, the career association database stores a plurality of pieces of career information, each piece of career information comprises a plurality of application characteristics, each application characteristic corresponds to one piece of application information in the application information base, and in the load acquisition step, if a user inputs the career information, the application information is determined through the career association database according to the corresponding career information.
Further, the load obtaining step includes generating application information according to an application input by a user.
Further, the application update subsystem further includes an application installation policy, where the application installation policy includes a second application information obtaining step, the association determining step, and the difference analyzing step, and the second application information obtaining step includes obtaining application information to be installed from the application information base.
Further, the hardware selection subsystem further comprises a hardware monitoring strategy, the hardware monitoring strategy is configured with hardware exception conditions, and when any load-related data meets the hardware exception conditions, a hardware replacement request is generated according to corresponding hardware information and output.
Further, the hardware selection subsystem further comprises an application monitoring policy, the application monitoring policy is configured with application exception conditions, and in an application running process, when any one of the load-related data meets the application exception conditions, an application stopping request is generated according to corresponding application information and is output.
Further, each hardware data of the hardware load sub-strategy corresponds to a reference response time, the reference response time reflects a theoretical time required by the hardware to process data of a preset data volume, when an application runs, an actual measurement response time corresponding to the hardware is obtained, the actual measurement response time reflects an actual time required by the hardware to process the data of the preset data volume, the actual measurement load value of the hardware is a difference value between the actual measurement response time and the reference response, the anomaly monitoring sub-strategy is configured with an anomaly operation value corresponding to each different operation anomaly information, and a corresponding hardware anomaly load value is generated according to each hardware corresponding to the anomaly information.
The technical effects of the invention are mainly reflected in the following aspects: through the arrangement, the local management subsystem can acquire, associate and manage local application and hardware information, can acquire the use habits of a user and the requirement condition of the hardware in the actual operation process, the load analysis subsystem is used for detecting the load condition of each user terminal, and then reliable hardware is determined from the hardware information base through actually-measured load association data when the user changes the computer, so that the user can acquire information meeting the requirement according to personal requirements without influencing the use result.
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FIG. 1: the invention relates to a system architecture schematic diagram of a computer hardware adaptation intelligent analysis system.
Reference numerals: 1. a user terminal; 001. an application information base; 002. a hardware information base; 003. an associated information base; 100. a load analysis subsystem; 101. a load association database; 200. a local management subsystem; 201. a local application database; 202. a local hardware database; 210. an application update module; 220. a hardware update module; 300. a hardware selection subsystem; 400. an application update subsystem.
Detailed Description
The following detailed description of the embodiments of the present invention is provided in order to make the technical solution of the present invention easier to understand and understand.
A computer hardware adaptation intelligent analysis system comprises a load analysis subsystem 100, a local management subsystem 200 and a hardware selection subsystem 300, wherein the computer hardware adaptation intelligent analysis system is configured with an application information base 001, a hardware information base 002 and an associated information base 003; the application information base 001 stores application information, the application information base 001 stores the application information in advance, the format and the content of the application information at least comprise an application name and a version number, the content comprises the requirement condition of the application information on hardware modules such as a storage space, a video card, a sound card and a CPU, the requirement which can be directly obtained in general application is a quantifiable numerical value or a generalized requirement of a specific module, for example, more than 4G of a memory instead of directly corresponding to the corresponding specific hardware data, so that the hardware data which meets the condition can be obtained by correlating the correlation information in the correlation database, the content of the correlation information base 003 is detailed below, the hardware information base 002 stores hardware information, the hardware information comprises a plurality of hardware data under different hardware types, and each hardware data corresponds to hardware load capacity data, the hardware load capacity data reflects the load capacity corresponding to the hardware, the hardware information refers to the category to which the specific hardware belongs, such as a CPU, a sound card and a video card, and belongs to different hardware categories, so that the hardware belongs to different hardware information, and the type selection of the specific hardware is in one hardware data, but the hardware load capacities of different hardware data are different, so that the hardware and the application can be associated, and the judgment is carried out through the load capacity, the association information base 003 stores association information, and the association information reflects the requirement of the application corresponding to the application information on the hardware information; the related information is used for recording the requirement of the application information on the hardware information, that is, by searching the related information library 003, the corresponding hardware data under the requirement in the application information can be determined. And the associated information base 003 can perform editing operations such as rewriting, modification, deletion and the like under background management. The application information base 001 and the hardware information base 002 are preferably only capable of writing and storing information, and do not delete, modify, or rewrite information.
The local management subsystem 200 is configured with a local application database 201 and a local hardware database 202, where the local application database 201 stores a plurality of local application data, the local application data is generated corresponding to an application of the user terminal 1, the local application data stores an application installed by a local user or an updated application, and may specifically be two data storage manners, where first, the local application data is generated from information of the installed or updated application itself, that is, information is directly read from the application, and second, an application name and a version number are obtained from the application, corresponding application information is found from the application information base 001, the application data is obtained from the application information, but no matter which manner is adopted, the local application data reflects a situation of the application installed by the user, and the local hardware database 202 stores a plurality of local hardware data, the local hardware data is generated corresponding to the hardware of the user terminal 1, and the local hardware data storage is the selection type of the local hardware and reflects the hardware configuration of the original machine; the local management subsystem 200 is configured with an application update module 210 and a hardware update module 220, where the application update module 210 is configured to detect an application update action of the user terminal 1, generate corresponding local application data according to an application update result, and store the local application data in a local application database 201; the hardware updating module 220, where the hardware updating module 220 is configured to detect a hardware updating action of the user terminal 1, generate corresponding local hardware data according to a hardware updating result, and store the local hardware data in the local hardware database 202;
the load analysis subsystem 100 is configured with an information load analysis policy and an actual load monitoring policy, the load analysis subsystem 100 is configured with a load association database 101, the load association database 101 stores a plurality of load association data, the load association data uses local application data and local hardware data as indexes, the load association data is the key of the present invention, the data format of the load association data comprises a load item and a load value, if the hardware only has a single load item, the load value is the only content of the load association data, the load association data uses local data as indexes, for example, regarding hardware a and hardware number 152, if the hardware a application requires the efficiency of the hardware to process data to be a1, the requirement of the hardware specific instruction feedback time is a2, then for the hardware, at least two load items exist, each load item has a load value, and the higher the requirement of the application a on the hardware number 152 is, the higher the load value is, so the load related data reflects the requirement of the application on the hardware, and this requirement is the actual requirement when the user uses, for example, the user needs a plurality of applications to run and switch synchronously, or the setting requirement of the user on the application makes the hardware load higher, these are stored into the load related database 101 through the load related data, and the specific load related data is generated in the following manner; the load analysis strategy comprises the steps of acquiring a theoretical load associated value of each corresponding local hardware data according to local application data, generating the theoretical load associated value from corresponding associated information in the associated information base 003, generating initial load associated data according to the theoretical associated value, firstly, initializing and recording a load item and a load value, wherein two modes exist in the initialization, the first application is used for recording the load item and the load value, so the load item and the load value can be directly captured through an algorithm, and secondly, through the application information base 001 and the associated information base 003, because the format of associated information storage is also through the load item and the load value, the associated information is used for generating a theoretical load value (under each load item), and the theoretical load value is not in line with the actual requirements of a user because the actual use habit of the user cannot be used according to the theoretical load, therefore, when the user actually uses the system, the hardware cannot meet the requirements, and abnormal conditions such as blockage, halt, application closing and the like occur, so that the system is combined with the actual use requirements of the user; the actual load monitoring strategy is configured with a hardware load sub-strategy and an abnormal monitoring sub-strategy, the hardware load sub-strategy detects the hardware load state in the application running process in real time and generates a corresponding hardware measured load value, and updates corresponding load associated data according to the hardware measured load value, each hardware data of the hardware load sub-strategy corresponds to a reference response time, the reference response time reflects the theoretical time required by the hardware to process the data of the preset data amount, when the application runs, the actual measurement response time corresponding to the hardware is obtained, the actual measurement response time reflects the actual time required by the hardware to process the data of the preset data amount, the hardware measured load value is the difference between the actual measurement response time and the reference response, and by the arrangement, the actual load condition of the hardware can be obtained, namely the specific corresponding load value under the load item is obtained, the actual measured load value of the hardware is more in number in the using process, so that the influence of the actual measured load value of the hardware on load associated data can be reduced, specifically, 0.02 of the deviation value can be used as the basis of the load associated data, the abnormality monitoring sub-strategy receives the operation abnormality information generated by the computer, generates a corresponding abnormal hardware load value according to the operation abnormality information, and updates the corresponding load associated data according to the abnormal hardware load value; and the abnormal monitoring sub-strategy is configured with an abnormal operation value corresponding to each different operation abnormal information, and generates a corresponding hardware abnormal load value according to each hardware corresponding to the abnormal information. While the abnormal monitoring refers to the computer being abnormal, such as stuck, dead halt, application screen jump, over-high hardware temperature, etc., when such a situation occurs, the load value adjustment cardinality under each load item can be established, the abnormal load values of the hardware obtained under different conditions of the system are different, so that when the specific application is used, the corresponding application associated data change, for the convenience of understanding, the invention uses the hardware No. 152 as the necessary load hardware of the application A, the hardware No. 152 has two load items for the load associated data of the application A, the load value corresponding to the processing efficiency item is 2, the load value corresponding to the abnormal occurrence item is 3 (theoretical load associated value generation), and the actually measured response time is 1.02 seconds at this time, the reference response time is 1 second, then the difference is that the actually measured load value of the hardware is 0.01, and if the average value of 100 times of tests is the actually measured load value of the hardware, under the adjustment of the hardware load sub-strategy, the load value of the processing efficiency item is 2.02 corresponding to the load item (the adjustment cardinality adopts a proportion of 0.02), and if 5 times of hitches and 1 time of crashes occur, the abnormal load value corresponding to each hitching is 0.01, the abnormal load value corresponding to each crashed is 0.1 (preset according to the operation abnormal information), the load value corresponding to the abnormal occurrence item is 3.15. Thus, a specific load situation is obtained, and the load situation can reflect the actual use habits of the user, because the theoretical load situation is generated when only one application is operated, and a plurality of applications are required to be operated or switched simultaneously in an actual scene, so that a larger load is generated.
The hardware selection subsystem 300 is configured with a hardware selection policy, where the hardware selection policy includes a load obtaining step, a load calculating step, and a hardware selection step, the load obtaining step includes obtaining load associated data corresponding to each type of hardware according to application information corresponding to the user to generate a load difference, and the generation of the application information may be performed in the following manner except that the local application database 201 is called: 1. and a professional association database is also configured, wherein the professional association database stores a plurality of professional information, each professional information comprises a plurality of application features, each application feature corresponds to one application information in the application information base 001, and in the load acquisition step, if a user inputs the professional information, the application information is determined through the professional association database according to the corresponding professional information. Namely, the user can input own occupation, and the more common application of the occupation can be obtained by establishing the occupation association database, so that the corresponding hardware requirement can be obtained. 2. The load acquiring step includes generating application information according to an application input by a user. Or increase the demand according to the application information input by the user, which is not described herein, the specific load obtaining step generates the corresponding load difference according to the current load associated data, where the load difference is the load difference that actually reflects whether the original hardware is matched, first obtains the corresponding application information from the application information base 001 according to the local application data, and then obtains the corresponding required load value according to the associated information, that is, the requirement of the user on the hardware is determined according to the application information of the user, and this information is also recorded in the form of load items and load values, and this corresponds exactly to the corresponding load associated data, so that the load difference under the actual use habit of the user can be obtained, taking the above case as an example, the difference between two load items is 0.02 and 0.15, the load calculating step includes retrieving the hardware load capacity data corresponding to the hardware from the hardware information base 002, and generating a hardware load demand value according to the hardware load capacity data and the load difference value, wherein the hardware load capacity data is also adjusted and corrected, the more user samples are, the more accurate the hardware load capacity data is, the hardware load updating strategy is configured in the computer hardware adaptation intelligent analysis system, the local load updating condition is configured in the hardware load updating strategy, and when the load related data corresponding to any local terminal meets the local load updating condition, the hardware load capacity data is updated according to the load related data. The local load update condition may be that when the load value under the corresponding load item reaches a preset value, the hardware load capacity data is corrected in proportion, so that the actual required value of the user for the hardware load can be obtained at this time, the hardware selection step selects the hardware data whose hardware load capacity data meets the required value of the hardware load from the hardware information base 002 according to the required value of the hardware load, and outputs the hardware data, specifically, the load value under the corresponding load item is greater than the required value of the hardware load, so that the hardware data meeting the condition can be obtained, but in order to further facilitate the user to determine the corresponding hardware, in the hardware information base 002, a valuable burden value and a lifetime undertaking value are configured corresponding to each hardware data, the value burden value reflects the price of the hardware corresponding to the hardware data, and the lifetime undertaking value reflects the lifetime of the hardware, and in the hardware calculation step, corresponding hardware data is determined according to a value threshold value and a service life threshold value which are input by a user in advance. Through the setting, hardware data can be screened, and hardware with short service life or high price is deleted, so that the satisfied hardware data of a user can be presented conveniently. The hardware selection subsystem 300 further includes a hardware monitoring policy, where the hardware monitoring policy is configured with hardware exception conditions, and when any of the load-related data meets the hardware exception conditions, a hardware replacement request is generated according to corresponding hardware information and output. Therefore, when the hardware is abnormal, the user is advised to replace the hardware, and corresponding hardware information is output to the corresponding user. The hardware selection subsystem 300 further includes an application monitoring policy, where the application monitoring policy is configured with application exception conditions, and in an application running process, when any one of the load-related data meets the application exception conditions, an application stop request is generated according to corresponding application information and output. When the application has a large hardware load, a request for stopping the application can be output, and the damage to the hardware is avoided.
In an embodiment, the system further includes an application update subsystem 400, it should be noted that the application update subsystem 400 and the application update module 210 have different policies, which are two concepts, where the application update subsystem 400 includes an application update policy, the application update policy includes a first application information obtaining step, an association determining step, and a difference analysis step, the first application information obtaining step includes obtaining application information to be updated from the application information base 001, the association determining step includes obtaining corresponding association information from the association information base 003 according to the application information, and determining corresponding hardware load capacity data according to the association information, the difference analysis step includes calculating an update load difference according to the obtained hardware load capacity data and local load association data, and if the obtained update load difference is greater than a preset first load threshold, and outputting configuration abnormal information according to the updated load difference value. The application update subsystem 400 further includes an application installation policy, where the application installation policy includes a second application information obtaining step, the association determining step, and the difference analyzing step, and the second application information obtaining step includes obtaining application information to be installed from the application information base 001. The application updating subsystem 400 obtains the application information to be updated and installed, then obtains the load capacity data according to the associated information, calculates the difference value, if the difference value exceeds the preset range, indicates that the updated and installed application is not suitable for being used in the local computer, outputs corresponding configuration abnormal information, and then can recommend the user not to install and update the application, thereby facilitating the use of the user.
The above are only typical examples of the present invention, and besides, the present invention may have other embodiments, and all the technical solutions formed by equivalent substitutions or equivalent changes are within the scope of the present invention as claimed.
Claims (10)
1. A computer hardware adaptation intelligent analysis system is characterized in that: the computer hardware adaptation intelligent analysis system is provided with an application information base, a hardware information base and an associated information base; the application information base stores application information, the hardware information base stores hardware information, the hardware information comprises a plurality of hardware data under different hardware types, each hardware data corresponds to hardware load capacity data, the hardware load capacity data reflects the load capacity corresponding to the hardware, the association information base stores association information, and the association information reflects the requirement of the application corresponding to the application information on the hardware information;
the local management subsystem is configured with a local application database and a local hardware database, the local application database stores a plurality of local application data, the local application data corresponds to the application generation of the user terminal, the local hardware database stores a plurality of local hardware data, and the local hardware data corresponds to the hardware generation of the user terminal; the local management subsystem is configured with an application updating module and a hardware updating module, wherein the application updating module is used for detecting an application updating action of the user terminal, generating corresponding local application data according to an application updating result and storing the local application data in a local application database; the hardware updating module is used for detecting the hardware updating action of the user terminal, generating corresponding local hardware data according to the hardware updating result and storing the local hardware data into a local hardware database;
the load analysis subsystem is configured with an information load analysis strategy and an actual load monitoring strategy, the load analysis subsystem is configured with a load association database, the load association database stores a plurality of load association data, and the load association data takes local application data and local hardware data as indexes; the load analysis strategy comprises the steps of obtaining a theoretical load associated value of each corresponding local hardware data according to local application data, generating the theoretical load associated value from corresponding associated information in the associated information base, and generating initial load associated data according to the theoretical associated value; the actual load monitoring strategy is configured with a hardware load sub-strategy and an abnormal monitoring sub-strategy, the hardware load sub-strategy detects the hardware load state in the application running process in real time and generates a corresponding hardware actual measurement load value, and updates corresponding load associated data according to the hardware actual measurement load value, the abnormal monitoring sub-strategy receives running abnormal information generated by a computer, generates a corresponding hardware abnormal load value according to the running abnormal information, and updates the corresponding load associated data according to the hardware abnormal load value;
the hardware selection subsystem is configured with a hardware selection strategy, the hardware selection strategy comprises a load obtaining step, a load calculating step and a hardware selection step, the load obtaining step comprises obtaining load relevant data corresponding to each type of hardware according to application information corresponding to the user to generate a load difference value, the load calculating step comprises calling hardware load capacity data corresponding to the hardware from the hardware information base and generating a hardware load requirement value according to the hardware load capacity data and the load difference value, and the hardware selection step selects hardware data, of which the hardware load capacity data meets the hardware load requirement value, from the hardware information base according to the hardware load requirement value and outputs the hardware data.
2. The computer hardware adapted intelligent analysis system of claim 1, wherein: the computer hardware adaptation intelligent analysis system is configured with a hardware load updating strategy, the hardware load updating strategy is configured with local load updating conditions, and when load associated data corresponding to any local terminal meets the local load updating conditions, the hardware load capacity data is updated according to the load associated data.
3. The computer hardware adapted intelligent analysis system of claim 1, wherein: in the hardware information base, configuring a valuable burden value and a service life undertaking value of hardware data corresponding to each piece of hardware data, wherein the valuable burden value reflects the price of the hardware corresponding to the hardware data, the service life undertaking value reflects the service life of the hardware, and in the hardware calculation step, the corresponding hardware data is determined according to a value threshold value and a service life threshold value which are input by a user in advance.
4. The computer hardware adapted intelligent analysis system of claim 1, wherein: the method comprises an application updating subsystem and a differential analysis step, wherein the application updating subsystem comprises an application updating strategy, the application updating strategy comprises a first application information acquisition step, an association judgment step and a difference analysis step, the first application information acquisition step comprises the step of acquiring application information to be updated from an application information base, the association judgment step comprises the step of acquiring corresponding association information from an association information base according to the application information and determining corresponding hardware load capacity data according to the association information, the differential analysis step comprises the step of calculating an updating load difference according to the acquired hardware load capacity data and local load association data, and configuration abnormal information is output according to the updating load difference if the acquired updating load difference is larger than a preset first load threshold.
5. The computer hardware adapted intelligent analysis system of claim 1, wherein: and a professional association database is also configured, wherein the professional association database stores a plurality of professional information, each professional information comprises a plurality of application characteristics, each application characteristic corresponds to one application information in the application information base, and in the load acquisition step, if a user inputs the professional information, the application information is determined through the professional association database according to the corresponding professional information.
6. The computer hardware adapted intelligent analysis system of claim 1, wherein: the load acquiring step includes generating application information according to an application input by a user.
7. The computer hardware adapted intelligent analysis system of claim 4, wherein: the application updating subsystem further comprises an application installation strategy, the application installation strategy comprises a second application information acquisition step, the association judgment step and the difference analysis step, and the second application information acquisition step comprises the step of acquiring the application information to be installed from the application information base.
8. The computer hardware adapted intelligent analysis system of claim 1, wherein: the hardware selection subsystem further comprises a hardware monitoring strategy, the hardware monitoring strategy is configured with hardware abnormal conditions, and when any load associated data meets the hardware abnormal conditions, a hardware replacement request is generated according to corresponding hardware information and output.
9. The computer hardware adapted intelligent analysis system of claim 8, wherein: the hardware selection subsystem further comprises an application monitoring strategy, the application monitoring strategy is configured with application exception conditions, and in the application running process, when any load associated data meets the application exception conditions, an application stopping request is generated according to corresponding application information and is output.
10. The computer hardware adapted intelligent analysis system of claim 1, wherein: each hardware data of the hardware load sub-strategy corresponds to a reference response time, the reference response time reflects theoretical time required by the hardware for processing data of a preset data volume, when an application runs, actual measurement response time corresponding to the hardware is obtained, the actual measurement response time reflects actual time required by the hardware for processing the data of the preset data volume, the actual measurement load value of the hardware is a difference value between the actual measurement response time and the reference response, the abnormality monitoring sub-strategy is configured with an abnormal operation value corresponding to each different operation abnormality information, and a corresponding hardware abnormal load value is generated according to each hardware corresponding to the abnormality information.
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