A method and system for calculating investment income of secondary vocational schools

Abstract

The present invention provides a method and system for calculating investment income of a secondary vocational school, wherein the method comprises: step 1: constructing a template for determining investment income calculation projects; step 2: determining the calculation projects for investment income calculation of a target secondary vocational school according to the template for determining investment income calculation projects; step 3: determining the target mathematical model according to project attributes; step 4: performing investment income calculation according to the calculation projects and the target mathematical model, and determining the system calculation process; step 5: performing process optimization based on the system calculation process, and performing calculation according to the obtained process optimization results. A method and system for calculating investment income of a secondary vocational school of the present invention determines the calculation projects of a target secondary vocational school according to the template for determining investment income calculation projects, then determines the target mathematical model according to the project attributes of the calculation projects, and finally performs process optimization based on the system calculation process, obtains the process optimization results for income calculation, and has higher calculation efficiency and is more suitable.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to a method and system for calculating investment income of secondary vocational schools. Background Art

[0002] At present, my country is vigorously developing vocational education and encouraging enterprise groups to open vocational schools. When opening a secondary vocational school, it is necessary to conduct a feasibility analysis and calculate the investment returns.

[0003] Investment return calculation can provide investors with a basis for decision-making. By calculating investment returns, investors can evaluate the potential benefits and rate of return of investing in secondary vocational schools. Investment return calculation also helps with risk assessment. By considering the investment amount, investment period and expected rate of return, investors can understand the risks and potential losses of investing in secondary vocational schools, which can help them make wise investment decisions and take appropriate risk management measures. In addition, for secondary vocational school managers, investment return calculation is very important for financial planning. It can help school managers understand the potential benefits of investment and incorporate them into the school's financial plan, which helps to formulate budgets, resource allocation and fund management strategies. Investment return calculation can also be used to evaluate the effectiveness of an investment. By comparing the expected investment returns with the actual returns, school managers can evaluate the success of the investment and determine whether adjustments or improvements are needed.

[0004] The invention patent with application number: CN202111356624.3 discloses a method, device, equipment and medium for calculating the investment income of distributed photovoltaic power generation, wherein the method includes: receiving a first basic parameter input by a user for calculating the installation of a distributed photovoltaic power generation device on a target building; when the parameter calculation control is triggered, the income data of installing the distributed photovoltaic power generation device on the target building is calculated based on the first basic parameter; when the control for generating a detailed income report is triggered, a detailed income report is generated based on the income data. The technical solution of the above invention solves the technical problems of low accuracy and low calculation efficiency in the existing methods for calculating the investment income of distributed photovoltaic power generation, and realizes faster and more accurate calculation of the beneficial data of installing distributed photovoltaic power generation devices, thereby achieving the technical effect of improving the accuracy and efficiency of calculating the income of installing distributed photovoltaic power generation devices.

[0005] However, the above-mentioned prior art does not disclose the process of system operation and data processing when calculating the revenue data of installing a distributed photovoltaic power generation device in a target building based on the first basic parameter. If a single system operation and data processing method is used when the computing power requirements are inconsistent, it is easy to cause the system operation speed to be slow, which is not suitable.

[0006] In view of this, there is an urgent need for a method and system for calculating investment returns of secondary vocational schools to at least solve the above-mentioned deficiencies. Summary of the invention

[0007] One of the purposes of the present invention is to provide a method for calculating the investment income of secondary vocational schools. The calculation project of the target secondary vocational school is determined according to a template for determining the investment income calculation project, and then the investment income mathematical modeling is performed according to the project attributes of the calculation project to determine the target mathematical model. Finally, process optimization is performed based on the system calculation process, and the process optimization result is obtained to calculate the income, which improves the calculation efficiency and is more suitable.

[0008] An embodiment of the present invention provides a method for calculating investment income of a secondary vocational school, comprising:

[0009] Step 1: Construct a template for determining investment income calculation projects;

[0010] Step 2: Determine the template based on the investment income calculation items and determine the investment income calculation items for the target secondary vocational school to be opened;

[0011] Step 3: Obtain the project attributes of the calculation project, and perform investment return mathematical modeling based on the project attributes to obtain the target mathematical model;

[0012] Step 4: Calculate the investment return based on the calculation project and the target mathematical model, and determine the system calculation process;

[0013] Step 5: Perform process optimization based on the system calculation process, obtain process optimization results, and perform corresponding calculations based on the process optimization results.

[0014] Preferably, step 3: obtaining the project attributes of the calculation project, and performing investment return mathematical modeling according to the project attributes to obtain a target mathematical model, including:

[0015] According to the project attributes, conduct a necessity analysis of mathematical modeling of investment returns;

[0016] When the necessity analysis result indicates that it is necessary to conduct mathematical modeling of investment returns, the corresponding target mathematical model is obtained. The target mathematical model is:

[0017] P=K(0.8XY-3372Y-60000)

[0018] Among them, P is the annual profit of the target secondary vocational school, the unit of P is: yuan, X is the tuition fee, Y is the number of students, K is the correction coefficient, K = 0.85;

[0019] Necessity analysis of mathematical modeling of investment returns, including:

[0020] According to the project attributes, obtain the student population, campus area, building area, number of teachers, number of books, per capita allocation of practical training equipment, and per capita allocation of computers;

[0021] If the student population, campus area, building area, number of teachers, number of books, per capita allocation of practical training equipment, and per capita number of computers all meet the preset target conditions, the analysis result is that it is necessary to conduct mathematical modeling of investment returns, otherwise it is not necessary.

[0022] Preferably, step 1: constructing a template for determining investment income calculation projects, including:

[0023] Based on big data, obtain investment cost projects and investment income projects, and take investment cost projects and investment income projects as the first construction projects;

[0024] Get the project source property of the first build project;

[0025] Get the target attributes of the target secondary vocational school;

[0026] According to the project source attributes and target attributes, a template for determining the investment return calculation project is constructed.

[0027] Preferably, according to the project source attribute and target attribute, a template for determining the investment return calculation project is constructed, including:

[0028] Determine similar and different attributes based on the source and target attributes of the project;

[0029] Obtaining a first construction item corresponding to a similar attribute and using it as a second construction item;

[0030] Determine a first construction link according to the similar attributes and the second construction item;

[0031] Obtain the attribute value of the difference attribute and, at the same time, obtain the difference item formulation model;

[0032] Formulate a model based on the attribute values ​​and difference items and determine the third construct item;

[0033] Determine a second construction link according to the difference attribute and the third construction item;

[0034] The first construction link and the second construction link are integrated to determine the investment return calculation project determination template.

[0035] Preferably, step 4: performing investment return calculation according to the calculation project and the target mathematical model, and determining the system calculation process, including:

[0036] Get initial operation parameters;

[0037] Determine the system calculation process based on the initial operation parameters.

[0038] Preferably, step 5: performing process optimization based on the system calculation process, obtaining process optimization results, and performing corresponding calculations according to the process optimization results, including:

[0039] Process splitting is performed on the system calculation process to obtain a plurality of first process splitting items;

[0040] Obtaining the adjustment type of the first process split item; the adjustment type includes: adjustable and non-adjustable;

[0041] If the adjustment type is adjustable, the corresponding first process split item will be used as the second process split item;

[0042] Obtaining adjustment limits for the second process split items;

[0043] Determine the adjustment position of the process optimization results according to the adjustment limit;

[0044] The system calculation process is updated according to the adjusted position to obtain the process optimization result.

[0045] Preferably, determining the adjustment position of the process optimization result according to the adjustment limit includes:

[0046] Determine an adjustment interval of the second process split item according to the adjustment limit, and obtain a current point position of the second process split item in the adjustment interval;

[0047] Randomly determine the adjustment points within the adjustment range;

[0048] Get the interval difference vector between the current point and the adjusted point; the modulus of the interval difference vector is the interval difference;

[0049] Get the adjustment interval attribute of the adjustment interval;

[0050] Determine the fluctuation reference library according to the adjustment interval attributes;

[0051] Determine the calculation time fluctuation value according to the interval difference vector and the fluctuation reference library;

[0052] According to the calculation time fluctuation value, determine the adjustment point set with the minimum system calculation time, and use the adjustment point set as the adjustment position;

[0053] Among them, obtaining the interval difference vector between the current point and the adjustment point includes:

[0054] If the interval difference between the current point and the adjustment point is positive, the interval difference vector is the preset first direction;

[0055] If the interval difference between the current point and the adjustment point is negative, the interval difference vector is the preset second direction;

[0056] Among them, according to the interval difference vector and the fluctuation reference library, the calculation time fluctuation value is determined, including:

[0057] Obtaining a matching vector in a fluctuation comparison library;

[0058] Match the interval difference vector and the matching vector, and determine the preset value corresponding to the matching vector that matches the matching;

[0059] Each preset value is cumulatively calculated to obtain a calculation time fluctuation value.

[0060] An embodiment of the present invention provides a method for calculating investment income of a secondary vocational school, further comprising:

[0061] Step 6: Obtain the future professional plan of the target secondary vocational school, and introduce big data teaching resources for professional layout according to the future professional plan;

[0062] Among them, step 6: obtain the future professional plan of the target secondary vocational school, and introduce big data teaching resources for professional layout according to the future professional plan, including:

[0063] Determine a list of target resources based on future professional plans;

[0064] According to the target resource list, determine the current resource list and the missing resource list;

[0065] Based on big data, determine the resource request node according to the missing resource list;

[0066] Establish communication links with resource request nodes and introduce big data teaching resources for professional layout.

[0067] Preferably, based on big data and according to the missing resource list, determining the resource request node includes:

[0068] Based on the big data, determining sharing information of a first pre-screened resource requesting node;

[0069] Get the storage ID on the preset blockchain;

[0070] Determine the first data to be uploaded to the chain based on the shared information and storage ID;

[0071] Voting on the first pre-screened resource requesting node corresponding to the first data to be uploaded to the chain to determine a voting list;

[0072] According to the voting list, determine the election node of the preset first election ranking range, and at the same time, determine the review node of the preset second election ranking range;

[0073] The review nodes review the election nodes to obtain the review results, and remove the untrustworthy nodes from the election nodes based on the review results;

[0074] Re-vote in the review nodes to elect candidate nodes equal to the number of the eliminated dishonest nodes and supplement the eliminated election nodes to obtain the second pre-screening resource request node;

[0075] Determine the first data to be uploaded to the chain of the second pre-screened resource requesting node and use it as the second data to be uploaded to the chain;

[0076] Obtain the number of operations per unit sharing time and the browsing time per unit sharing time of the second data to be uploaded to the chain;

[0077] Assigning a preset first weight to the number of operations and a preset second weight to the browsing time, and obtaining an assignment result;

[0078] The assigned results are summed and the calculation result of the summation is fused with the normalization coefficient to obtain the sharing parameter;

[0079] Obtaining click information of the second data to be uploaded to the chain, wherein the click information includes: download information, forwarding information, and evaluation information;

[0080] Determine the marking parameters according to the information features of the extracted click information and the preset marking favorability determination model;

[0081] Determine, based on a preset associated resource determination rule, missing list association parameters of the target resource in the second to-be-uploaded data and the missing resource in the missing list;

[0082] According to the sharing parameters, marking parameters and missing list associated parameters, the second data to be uploaded to the chain that meets the screening conditions is determined and used as the target uploaded data;

[0083] The target on-chain data is packaged and published on the blockchain, and the publishing node on the blockchain is used as the resource request node.

[0084] An embodiment of the present invention provides a system for calculating investment income of a secondary vocational school, comprising:

[0085] Template building subsystem, used to build investment return calculation project determination template;

[0086] The calculation project determination subsystem is used to determine the calculation projects for investment income calculation of the target secondary vocational school to be opened according to the investment income calculation project determination template;

[0087] The target mathematical model determination subsystem is used to obtain the project attributes of the calculation project, and to perform mathematical modeling of investment returns based on the project attributes to obtain the target mathematical model;

[0088] The system calculation process determination subsystem is used to calculate the investment return according to the calculation project and the target mathematical model and determine the system calculation process;

[0089] The process optimization subsystem is based on the system and is used to optimize the process based on the system calculation process, obtain the process optimization results, and perform corresponding calculations based on the process optimization results.

[0090] The beneficial effects of the present invention are:

[0091] The present invention determines the calculation project of the target secondary vocational school according to the constructed investment income calculation project determination template, then performs investment income mathematical modeling according to the project attributes of the calculation project to determine the target mathematical model, and finally performs process optimization based on the system calculation process, obtains the process optimization result for income calculation, improves the calculation efficiency, and is more suitable.

[0092] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0093] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0095] Figure 1 A schematic diagram of a method for calculating investment income of a secondary vocational school in an embodiment of the present invention;

[0096] Figure 2 It is a schematic diagram of a system for calculating investment income of a secondary vocational school in an embodiment of the present invention. DETAILED DESCRIPTION

[0097] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0098] The embodiment of the present invention provides a method for calculating investment income of a secondary vocational school. Figure 1 As shown, including:

[0099] Step 1: Construct an investment income calculation project determination template; wherein, the investment income calculation project determination template is a template for the system to determine the investment income calculation project, and the investment income calculation project is a project related to the investment income of the secondary vocational school, such as tuition, construction project costs, and educational resource costs;

[0100] Step 2: Determine the template based on the investment income calculation project, and determine the calculation project for the investment income calculation of the target secondary vocational school to be opened; wherein the calculation project is: the investment income calculation project related to the target secondary vocational school, and the system can determine the calculation project according to the specific conditions of the target secondary vocational school by comparing it with the template for determining the investment income calculation project;

[0101] Step 3: Obtain the project attributes of the calculation project, and perform investment return mathematical modeling based on the project attributes to obtain the target mathematical model; wherein the project attributes are: the project type of the calculation project; the target mathematical model is: the mathematical formula model used to calculate the investment return of the target secondary vocational school;

[0102] Step 4: Calculate the investment income according to the calculation items and the target mathematical model, and determine the system calculation process; wherein the system calculation process is: the operation and calculation process of the system calculating the investment income according to the calculation items and the target mathematical model;

[0103] Step 5: Perform process optimization based on the system calculation process, obtain process optimization results, and perform corresponding calculations based on the process optimization results. The process optimization results are: a more efficient calculation process obtained by optimizing the system calculation process.

[0104] The working principle and beneficial effects of the above technical solution are:

[0105] This application determines the calculation project of the target secondary vocational school based on the constructed investment income calculation project determination template, and then performs investment income mathematical modeling according to the project attributes of the calculation project to determine the target mathematical model. Finally, the process is optimized based on the system calculation process, and the process optimization results are obtained for income calculation, which improves the calculation efficiency and is more appropriate.

[0106] In one embodiment, step 3: obtaining the project attributes of the calculation project, and performing investment return mathematical modeling according to the project attributes to obtain a target mathematical model, includes:

[0107] According to the project attributes, conduct a necessity analysis of mathematical modeling of investment returns;

[0108] When the necessity analysis result indicates that it is necessary to conduct mathematical modeling of investment returns, the corresponding target mathematical model is obtained. The target mathematical model is:

[0109] P=K(0.8XY-3372Y-60000)

[0110] Among them, P is the annual profit of the target secondary vocational school, the unit of P is: yuan, X is the tuition fee, Y is the number of students, K is the correction coefficient, K = 0.85;

[0111] Necessity analysis of mathematical modeling of investment returns, including:

[0112] According to the project attributes, obtain the student population, campus area, building area, number of teachers, number of books, per capita allocation of practical training equipment, and per capita allocation of computers;

[0113] If the student population, campus area, building area, number of teachers, number of books, per capita allocation of practical training equipment, and per capita allocation of computers all meet the preset target conditions, the analysis result shows that it is necessary to conduct mathematical modeling of investment returns, otherwise it is unnecessary. Among them, the preset target conditions are: student population of 1,200, campus area of ​​33 square meters per student, building area of ​​20 square meters per student, teacher-student ratio of 1:20, per capita books of 30, per capita practical training equipment of 2,500 yuan, and 15 computers for every 100 people.

[0114] The working principle and beneficial effects of the above technical solution are:

[0115] This application conducts a necessity analysis of mathematical modeling of investment returns based on project attributes, introduces target conditions, and conducts mathematical modeling of investment returns when the student population, campus area, building area, number of teachers, number of books, per capita allocation of practical training equipment, and per capita allocation of computers all reach preset target conditions, thereby improving modeling efficiency.

[0116] In one embodiment, step 1: constructing an investment return calculation project determination template includes:

[0117] Based on big data, investment expenditure items and investment income items are obtained, and the investment expenditure items and investment income items are used as the first construction items; among which, the investment expenditure items are: site expenses and practical training equipment expenses, etc.; the investment income items are: student tuition, etc.;

[0118] Obtaining a project source attribute of the first construction project; wherein the project source attribute is: attribute information of the source of the first construction project, such as: the education stage and school size of the source school;

[0119] Obtain the target attributes of the target secondary vocational school; the target attributes include: the educational stage and school size of the target secondary vocational school;

[0120] According to the project source attributes and target attributes, a template for determining the investment return calculation project is constructed.

[0121] The working principle and beneficial effects of the above technical solution are:

[0122] Generally, when determining the school's investment return calculation projects, manual analysis is required to determine which projects will bring investment profits and which projects will bring capital consumption, etc. Manual determination of the investment return calculation projects relies on manual understanding of all aspects of the target secondary vocational school. Therefore, this application introduces a first construction project, and constructs an investment return calculation project determination template based on the project source attributes of the first construction project and the target attributes of the target secondary vocational school. The construction process of the investment return calculation project determination template is more reasonable and more convenient in subsequent applications.

[0123] In one embodiment, a template for determining investment return calculation projects is constructed based on project source attributes and target attributes, including:

[0124] Determine similar attributes and different attributes based on the project source attributes and target attributes; similar attributes are: similar attribute types of the project source attributes and target attributes, such as land area and student size; different attributes are: dissimilar attribute types of the project source attributes and target attributes;

[0125] Acquire a first construction item corresponding to the similar attribute and use it as the second construction item; wherein the first construction item corresponding to the similar attribute is: an investment income calculation item related to the similar attribute;

[0126] Determine a first construction link according to the similar attributes and the second construction project; wherein the first construction link is: a trigger mechanism for triggering construction of the second construction project corresponding to the similar attributes according to the similar attributes;

[0127] Acquire the attribute value of the difference attribute, and at the same time, acquire the difference project formulation model; wherein the attribute value is: the attribute characteristic value of the attribute type that is not similar to the source attribute and the target attribute of the project, such as: how many students there are, and how many teaching equipment there are; the difference project formulation model is: a pre-set intelligent model for replacing manual formulation of difference projects corresponding to the difference attributes, and the above intelligent model is obtained by using a neural network model based on the formulation record of manual formulation of difference projects according to the difference attributes;

[0128] A model is formulated according to the attribute value and the difference item to determine the third construction item; wherein the third construction item is: an investment income calculation item related to the difference attribute;

[0129] Determine a second construction link according to the difference attribute and the third construction project; wherein the second construction link is: a trigger mechanism for triggering construction of the third construction project corresponding to the difference attribute according to the difference attribute;

[0130] The first construction link and the second construction link are integrated to determine the investment return calculation project determination template.

[0131] The working principle and beneficial effects of the above technical solution are:

[0132] The present application determines the second construction project based on the determined similar attributes, and directly determines the first construction link based on the similar attributes and the second construction project. The third construction project is determined based on the attribute value of the determined difference attribute and the introduced difference project formulation model, and the third construction project is determined based on the attribute value and the difference project formulation model, and then the second construction link is determined based on the difference attribute and the third construction project, thereby improving the suitability of the second construction link.

[0133] In one embodiment, step 4: performing investment return calculation according to the calculation project and the target mathematical model, and determining the system calculation process, includes:

[0134] Obtaining initial operation parameters; wherein the initial operation parameters include: the operation algorithm and operation data processing method initially set by the system, and the setting rules are pre-entered by the staff;

[0135] Determine the system calculation process based on the initial operation parameters.

[0136] The working principle and beneficial effects of the above technical solution are:

[0137] This application determines the system calculation process based on the initial operation parameters, and the determination of the system calculation process is more accurate.

[0138] In one embodiment, step 5: performing process optimization based on the system calculation process, obtaining process optimization results, and performing corresponding calculations according to the process optimization results, including:

[0139] The system computing process is split into multiple first process split items; wherein the process split is split according to the process type of the system computing process, and the process types include: data preprocessing, algorithm optimization and parallel computing, etc.; the first process split item is: the process content of each process type, such as: what algorithm is used;

[0140] Obtaining an adjustment type of the first process split item; the adjustment type includes: adjustable and non-adjustable; wherein the first process split item of the adjustable adjustment type is: a first process split item that allows adjustment; the first process split item of the non-adjustable adjustment type is: a first process split item that does not allow adjustment; the adjustment type is determined by determining whether the adjustment decision is supported based on the software and hardware parameters of the system;

[0141] If the adjustment type is adjustable, the corresponding first process split item will be used as the second process split item;

[0142] Obtaining the adjustment limit of the second process split item; wherein the adjustment limit is: adjustment degree;

[0143] According to the adjustment limit, the adjustment position of the process optimization result is determined; wherein the adjustment position is: the second process split item when the system calculation time reaches the minimum corresponds to the limit position in the adjustment limit;

[0144] The system calculation process is updated according to the adjusted position to obtain the process optimization result.

[0145] The working principle and beneficial effects of the above technical solution are:

[0146] When optimizing the system calculation process, the present application splits the system calculation process to obtain the first process split item. The adjustment type of the first process split item is obtained. When the first process split item is adjustable, the adjustment position is determined according to the adjustment limit of the second process split item. The system calculation process is updated according to the adjustment position to obtain the process optimization result, thereby improving the rationality of the calculation process optimization.

[0147] In one embodiment, determining an adjustment position of a process optimization result according to an adjustment limit includes:

[0148] Determine the adjustment interval of the second process split item according to the adjustment limit, and obtain the current point position of the second process split item in the adjustment interval; wherein the current point position is: the point position in the adjustment interval determined according to the process content of the second process split item;

[0149] Randomly determine the adjustment point on the adjustment interval; wherein the adjustment point is: a point that can be taken on the adjustment interval;

[0150] Get the interval difference vector between the current point and the adjusted point; the modulus of the interval difference vector is the interval difference;

[0151] Get the adjustment interval attribute of the adjustment interval; wherein the adjustment interval attribute is: the process attribute of the process split item adjusted by the adjustment interval;

[0152] Determine a fluctuation reference library according to the adjustment interval attribute; wherein the fluctuation reference library stores a plurality of one-to-one corresponding matching vectors and preset values;

[0153] According to the interval difference vector and the fluctuation reference library, the calculation time fluctuation value is determined; wherein the calculation time fluctuation value is: the change value of the system calculation time after adjustment according to the interval difference vector, for example: -3 seconds;

[0154] According to the calculation time fluctuation value, determine the adjustment point set with the minimum system calculation time, and use the adjustment point set as the adjustment position;

[0155] Among them, obtaining the interval difference vector between the current point and the adjustment point includes:

[0156] If the interval difference between the current point and the adjustment point is positive, the interval difference vector is a preset first direction; wherein the preset first direction is: from right to left;

[0157] If the interval difference between the current point and the adjustment point is negative, the interval difference vector is the preset second direction; wherein the preset second direction is: from left to right;

[0158] Among them, according to the interval difference vector and the fluctuation reference library, the fluctuation value of the calculated investment income is determined, including:

[0159] Obtaining a matching vector in a fluctuation comparison library;

[0160] Match the interval difference vector and the matching vector, and determine the preset value corresponding to the matching vector that matches the matching;

[0161] Each preset value is cumulatively calculated to obtain a calculation time fluctuation value.

[0162] The working principle and beneficial effects of the above technical solution are:

[0163] The present application determines the adjustment interval of the second process split item according to the adjustment limit, determines the interval difference vector according to the current point of the second process split item in the adjustment interval and the adjustment point in the randomly determined adjustment interval, determines the calculation time fluctuation value according to the interval difference vector, and determines the adjustment point set with the minimum system calculation time as the adjustment position, thereby improving the comprehensiveness of adjustment position acquisition.

[0164] The embodiment of the present invention provides a method for calculating investment income of a secondary vocational school, further comprising:

[0165] Step 6: Obtain the future professional plan of the target secondary vocational school, and introduce big data teaching resources for professional layout according to the future professional plan; the future professional plan is: the professional introduction plan determined by the target secondary vocational school based on the popularity trend of the future major;

[0166] Among them, step 6: obtain the future professional plan of the target secondary vocational school, and introduce big data teaching resources for professional layout according to the future professional plan, including:

[0167] According to the future professional plan, determine the target resource list; the target resource list is: the list of resources required for the major in the future professional plan;

[0168] According to the target resource list, determine the current resource list and the missing resource list; the current resource list is: the resources currently allocated to the target secondary vocational school; the missing resource list is determined based on the target resource list and the current resource list;

[0169] Based on big data, the resource request node is determined according to the missing resource list; wherein the resource request node is: a node requesting the missing resource;

[0170] Establish communication links with resource request nodes and introduce big data teaching resources for professional layout.

[0171] The working principle and beneficial effects of the above technical solution are:

[0172] Generally, when developing the current professional courses, secondary vocational schools also need to seek the layout of some emerging majors to facilitate the development of students. Therefore, this application determines the target resource list based on the future professional plans of the secondary vocational schools, and then determines the missing resource list based on the target resource list and the current resource list, and determines the resource request node of the big data platform based on the missing resource list, establishes a communication link with the resource request node, introduces big data teaching resources for professional layout, and improves resource sharing.

[0173] In one embodiment, based on big data and according to the missing resource list, determining the resource requesting node includes:

[0174] Based on the big data, determine the sharing information of the first pre-screening resource request node; wherein the sharing information includes: the identity information of the resource party of the first pre-screening resource request and the content information of the shared content;

[0175] Obtain a storage ID on a preset blockchain; wherein the storage ID is: the identity information verified on the blockchain;

[0176] Determine the first data to be uploaded to the chain according to the sharing information and the storage ID; wherein the first data to be uploaded to the chain is: a shared resource whose identity information has been verified;

[0177] Voting is performed on the first pre-screened resource request nodes corresponding to the first data to be uploaded to the blockchain to determine a voting list; wherein voting refers to selecting or determining nodes by voting in the blockchain network, and when determining the voting list, the first pre-screened resource request nodes are sorted according to the support level of each first pre-screened resource request node;

[0178] According to the voting list, determine the election node of the preset first election ranking range, and at the same time, determine the review node of the preset second election ranking range; wherein the preset first election ranking range is the ranking range of the top 20 in the election node; the preset second election ranking range is the ranking range from the 21st to the 30th in the election node;

[0179] The review node reviews the election node to obtain the review result, and removes the untrustworthy nodes from the election node according to the review result; wherein the review result is: which node is the untrustworthy node;

[0180] Re-vote in the review nodes to elect candidate nodes equal to the number of the eliminated dishonest nodes and supplement the eliminated election nodes to obtain the second pre-screening resource request node;

[0181] Determine the first data to be uploaded to the chain of the second pre-screened resource requesting node and use it as the second data to be uploaded to the chain;

[0182] The number of operations per unit sharing time of the second data to be put on the chain and the browsing time per unit sharing time are obtained; wherein the number of operations per unit sharing time is the result obtained by dividing the total number of operations when the user uses the platform of the second data to be put on the chain by the total online time of the platform of the second data to be put on the chain; the browsing time per unit sharing time is the result obtained by dividing the time the user uses the platform of the second data to be put on the chain by the total online time of the platform of the second data to be put on the chain;

[0183] Assign a preset first weight to the number of operations and a preset second weight to the browsing time to obtain an assignment result; wherein the sum of the first weight and the second weight is 1 and both the first weight and the second weight are positive numbers;

[0184] The assigned results are summed and the calculation results of the summed calculation are integrated with the normalization coefficient to obtain the sharing parameters; wherein the normalization coefficient is determined by the degree of screening of the subsequent target on-chain data by the calculation results, and the higher the screening degree, the higher the corresponding normalization coefficient;

[0185] Obtaining click information of the second data to be uploaded to the chain, wherein the click information includes: download information, forwarding information and evaluation information; wherein the download information includes: relevant information on how long it took to download and how many times it was downloaded; the forwarding information includes: relevant information on how long it took to forward and how many times it was forwarded; and the evaluation information includes: relevant information on the degree of favorable comments and the degree of unfavorable comments;

[0186] Determine the marking parameters according to the information features of the extracted click information and the preset marking favorability determination model; wherein the information features are: how many times it has been downloaded, how many times it has been forwarded, and the degree of good reviews and bad reviews; the marking favorability determination model is: an intelligent model for replacing manual work to determine the marking favorability of the second data to be uploaded to the chain according to the click information; the marking parameters are: marking favorability value;

[0187] Based on the preset associated resource determination rule, determine the missing list association parameters of the target resource in the second to-be-uploaded data and the missing resource in the missing list; wherein the preset associated resource determination rule is: calculate the resource similarity value of the target resource and the missing resource, if the resource similarity value is greater than or equal to the preset resource similarity value threshold, then the corresponding target resource is the associated resource; the missing list association parameter is: the sum of the resource similarity values ​​of the associated resources;

[0188] According to the sharing parameters, marking parameters and missing list associated parameters, the second data to be uploaded that meets the screening conditions is determined and used as the target data to be uploaded; wherein the screening condition is: the second data to be uploaded can be screened if the sum of the sharing parameters, marking parameters and missing list associated parameters corresponding to the second data to be uploaded meets the preset screening value threshold;

[0189] The target on-chain data is packaged and published on the blockchain, and the publishing node on the blockchain is used as the resource request node.

[0190] The working principle and beneficial effects of the above technical solution are:

[0191] This application introduces the storage ID and sharing information of the blockchain, determines the first data to be uploaded to the chain that has passed the identity authentication, votes on the first pre-screened resource request node corresponding to the first data to be uploaded to the chain, determines the election node and the review node, and conducts a secondary verification of the election node through the review node, eliminates the untrustworthy nodes and replaces them, and obtains the second pre-screened resource request node, which is more appropriate. The sharing parameters, marking parameters, and missing list associated parameters are introduced to determine the target data to be uploaded to the chain, and the process of determining the target data to be uploaded to the chain is more accurate. Finally, the target data to be uploaded to the chain is packaged and published on the blockchain, and the publishing node is determined as the resource request node, which improves the reliability of subsequent resource requests.

[0192] The embodiment of the present invention provides a system for calculating investment income of secondary vocational schools. Figure 2 As shown, including:

[0193] Template building subsystem 1, used to build a template for determining investment income calculation projects;

[0194] The calculation project determination subsystem 2 is used to determine the calculation projects for the investment income calculation of the target secondary vocational school to be opened according to the investment income calculation project determination template;

[0195] The target mathematical model determination subsystem 3 is used to obtain the project attributes of the calculation project, and to perform investment return mathematical modeling according to the project attributes to obtain the target mathematical model;

[0196] The system calculation process determination subsystem 4 is used to calculate the investment income according to the calculation project and the target mathematical model and determine the system calculation process;

[0197] The process optimization subsystem 5 is used to perform process optimization based on the system calculation process, obtain process optimization results, and perform corresponding calculations based on the process optimization results.

[0198] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for calculating investment income of secondary vocational schools, characterized in that: include: Step 1: Construct a template for determining investment income calculation projects; The step 1: constructing a template for determining investment income calculation projects, including: Based on big data, obtain investment cost projects and investment income projects, and take investment cost projects and investment income projects as the first construction projects; Acquire a project source attribute of a first construction project; the project source attribute is: attribute information of a source of the first construction project; Get the target attributes of the target secondary vocational school; According to the project source attributes and target attributes, a template for determining investment return calculation projects is constructed; According to the project source attributes and target attributes, a template for determining investment return calculation projects is constructed, including: Determine similar and different attributes based on the source and target attributes of the project; Obtaining a first construction item corresponding to a similar attribute and using it as a second construction item; Determine a first construction link according to the similar attributes and the second construction project; the first construction link is: a trigger mechanism for triggering construction of the second construction project corresponding to the similar attributes according to the similar attributes; Acquire the attribute value of the difference attribute, and at the same time, acquire the difference item formulation model; the difference item formulation model is: a pre-set intelligent model for replacing manual formulation of difference items corresponding to the difference attribute, and the above intelligent model is obtained by training a neural network model based on the formulation record of manual formulation of difference items according to the difference attribute; Formulate a model based on the attribute values ​​and difference items and determine the third construct item; Determine a second construction link according to the difference attribute and the third construction project; the second construction link is: a trigger mechanism for triggering construction of the third construction project corresponding to the difference attribute according to the difference attribute; Integrate the first construction link and the second construction link to determine the investment return calculation project determination template; Step 2: Determine the template based on the investment income calculation items and determine the investment income calculation items for the target secondary vocational school to be opened; Step 3: Obtain the project attributes of the calculation project, and perform investment return mathematical modeling based on the project attributes to obtain the target mathematical model; the project attributes are: the project type of the calculation project; Step 4: Calculate the investment income according to the calculation items and the target mathematical model, and determine the system calculation process; the system calculation process is: the operation and calculation process of the system to calculate the investment income according to the calculation items and the target mathematical model; Step 5: Optimize the process based on the system calculation process, obtain the process optimization results, and perform corresponding calculations based on the process optimization results; Step 4: Calculate the investment return based on the calculation project and target mathematical model, and determine the system calculation process, including: Acquire initial operation parameters; the initial operation parameters include: the operation algorithm and operation data processing method of the initial setting of the system; Determine the system calculation process according to the initial operation parameters; Step 5: Perform process optimization based on the system calculation process, obtain process optimization results, and perform corresponding calculations based on the process optimization results, including: Process splitting is performed on the system calculation process to obtain a plurality of first process splitting items; Obtaining the adjustment type of the first process split item; the adjustment type includes: adjustable and non-adjustable; the adjustment type is determined based on the system's software and hardware parameters to determine whether the adjustment decision is supported; If the adjustment type is adjustable, the corresponding first process split item will be used as the second process split item; Obtaining adjustment limits for the second process split items; According to the adjustment limit, the adjustment position of the process optimization result is determined; the adjustment position is: the second process split item when the system calculation time reaches the minimum corresponds to the limit position in the adjustment limit; The system calculation process is updated according to the adjustment position to obtain the process optimization result; the adjustment position of the process optimization result is determined according to the adjustment limit, including: Determine an adjustment interval of the second process split item according to the adjustment limit, and obtain a current point position of the second process split item in the adjustment interval; Randomly determine the adjustment points within the adjustment range; Get the interval difference vector between the current point and the adjusted point; the modulus of the interval difference vector is the interval difference; Get the adjustment interval attribute of the adjustment interval; According to the adjustment interval attribute, a fluctuation reference library is determined; the fluctuation reference library stores a plurality of one-to-one corresponding matching vectors and preset values; Determine the calculation time fluctuation value according to the interval difference vector and the fluctuation reference library; According to the calculation time fluctuation value, determine the adjustment point set with the minimum system calculation time, and use the adjustment point set as the adjustment position; Among them, obtaining the interval difference vector between the current point and the adjustment point includes: If the interval difference between the current point and the adjustment point is positive, the interval difference vector is the preset first direction; If the interval difference between the current point and the adjustment point is negative, the interval difference vector is the preset second direction; Among them, according to the interval difference vector and the fluctuation reference library, the calculation time fluctuation value is determined, including: Obtaining a matching vector in a fluctuation comparison library; Match the interval difference vector and the matching vector, and determine the preset value corresponding to the matching vector that matches the matching; Each preset value is cumulatively calculated to obtain a calculation time fluctuation value.

2. A method for calculating investment income of a secondary vocational school as claimed in claim 1, characterized in that: Step 3: Obtain the project attributes of the calculation project, and perform investment return mathematical modeling based on the project attributes to obtain the target mathematical model, including: According to the project attributes, conduct a necessity analysis of mathematical modeling of investment returns; When the necessity analysis result indicates that it is necessary to conduct mathematical modeling of investment returns, a corresponding target mathematical model is obtained; Necessity analysis of mathematical modeling of investment returns, including: According to the project attributes, obtain the student population, campus area, building area, number of teachers, number of books, per capita allocation of practical training equipment, and per capita allocation of computers; If the student population, campus area, building area, number of teachers, number of books, per capita allocation of practical training equipment, and per capita number of computers all meet the preset target conditions, the analysis result is that it is necessary to conduct mathematical modeling of investment returns, otherwise it is not necessary.

3. A method for calculating investment income of a secondary vocational school as claimed in claim 1, characterized in that: Also includes: Step 6: Obtain the future professional plan of the target secondary vocational school, and introduce big data teaching resources for professional layout according to the future professional plan; The future professional plan is: the professional introduction plan determined by the target secondary vocational school based on the popularity trend of the future major; Among them, step 6: obtain the future professional plan of the target secondary vocational school, and introduce big data teaching resources for professional layout according to the future professional plan, including: Determine a list of target resources based on future professional plans; According to the target resource list, determine the current resource list and the missing resource list; Based on big data, determine the resource request node according to the missing resource list; Establish communication links with resource request nodes and introduce big data teaching resources for professional layout; The method of determining a resource request node based on the big data and the missing resource list includes: Based on the big data, determine the sharing information of the first pre-screening resource request node; the sharing information includes: the identity information of the resource party of the first pre-screening resource request and the content information of the shared content; Get the storage ID on the preset blockchain; the storage ID is: the identity information verified on the blockchain; Determine the first data to be uploaded to the chain according to the sharing information and the storage ID; the first data to be uploaded to the chain is: the shared resources whose identity information has been verified; Voting on the first pre-screened resource requesting node corresponding to the first data to be uploaded to the chain to determine a voting list; According to the voting list, determine the election node of the preset first election ranking range, and at the same time, determine the review node of the preset second election ranking range; The review nodes review the election nodes to obtain the review results, and remove the untrustworthy nodes from the election nodes based on the review results; Re-vote in the review nodes to elect candidate nodes equal to the number of the eliminated dishonest nodes and supplement the eliminated election nodes to obtain the second pre-screening resource request node; Determine the first data to be uploaded to the chain of the second pre-screened resource requesting node and use it as the second data to be uploaded to the chain; Obtain the number of operations per unit sharing time and the browsing time per unit sharing time of the second data to be uploaded to the chain; Assigning a preset first weight to the number of operations and a preset second weight to the browsing time, and obtaining an assignment result; The assigned results are summed and the calculation result of the summation is fused with the normalization coefficient to obtain the sharing parameter; Obtaining click information of the second data to be uploaded to the chain, wherein the click information includes: download information, forwarding information, and evaluation information; Determine the marking parameters according to the information features of the extracted click information and the preset marking favorability determination model; the marking favorability determination model is: an intelligent model for replacing manual work to determine the marking favorability of the second data to be uploaded to the chain according to the click information; Based on a preset associated resource determination rule, determine the missing list association parameter of the target resource in the second to-be-uploaded data and the missing resource in the missing list; the missing list association parameter is: the sum of the resource similarity values ​​of the associated resources; According to the sharing parameters, marking parameters and missing list associated parameters, the second data to be uploaded to the chain that meets the screening conditions is determined and used as the target uploaded data; The target on-chain data is packaged and published on the blockchain, and the publishing node on the blockchain is used as the resource request node.

4. A system for calculating investment income of secondary vocational schools, characterized in that: include: Template building subsystem, used to build investment return calculation project determination template; The template construction subsystem constructs an investment return calculation project determination template, including: Based on big data, obtain investment cost projects and investment income projects, and take investment cost projects and investment income projects as the first construction projects; Acquire a project source attribute of a first construction project; the project source attribute is: attribute information of a source of the first construction project; Get the target attributes of the target secondary vocational school; According to the project source attributes and target attributes, a template for determining investment return calculation projects is constructed; According to the project source attributes and target attributes, a template for determining investment return calculation projects is constructed, including: Determine similar and different attributes based on the source and target attributes of the project; Obtaining a first construction item corresponding to a similar attribute and using it as a second construction item; Determine a first construction link according to the similar attributes and the second construction project; the first construction link is: a trigger mechanism for triggering construction of the second construction project corresponding to the similar attributes according to the similar attributes; Acquire the attribute value of the difference attribute, and at the same time, acquire the difference item formulation model; the difference item formulation model is: a pre-set intelligent model for replacing manual formulation of difference items corresponding to the difference attribute, and the above intelligent model is obtained by training a neural network model based on the formulation record of manual formulation of difference items according to the difference attribute; Formulate a model based on the attribute values ​​and difference items and determine the third construct item; Determine a second construction link according to the difference attribute and the third construction project; the second construction link is: a trigger mechanism for triggering construction of the third construction project corresponding to the difference attribute according to the difference attribute; Integrate the first construction link and the second construction link to determine the investment return calculation project determination template; The calculation project determination subsystem is used to determine the calculation projects for the investment income calculation of the target secondary vocational school to be opened according to the investment income calculation project determination template; The target mathematical model determination subsystem is used to obtain the project attributes of the calculation project, and to perform mathematical modeling of investment returns based on the project attributes to obtain the target mathematical model; the project attributes are: the project type of the calculation project; The system calculation process determination subsystem is used to perform investment income calculation according to the calculation items and the target mathematical model and determine the system calculation process; the system calculation process is: the operation and calculation process of the system performing investment income calculation according to the calculation items and the target mathematical model; The process optimization subsystem is based on the system and is used to optimize the process based on the system calculation process, obtain the process optimization results, and perform corresponding calculations based on the process optimization results; The system calculation process determines that the subsystem performs the following operations: Acquire initial operation parameters; the initial operation parameters include: the operation algorithm and operation data processing method of the initial setting of the system; Determine the system calculation process according to the initial operation parameters; The process optimization subsystem performs the following operations: Process splitting is performed on the system calculation process to obtain a plurality of first process splitting items; Obtaining the adjustment type of the first process split item; the adjustment type includes: adjustable and non-adjustable; the adjustment type is determined based on the system's software and hardware parameters to determine whether the adjustment decision is supported; If the adjustment type is adjustable, the corresponding first process split item will be used as the second process split item; Obtaining adjustment limits for the second process split items; According to the adjustment limit, the adjustment position of the process optimization result is determined; the adjustment position is: the second process split item when the system calculation time reaches the minimum corresponds to the limit position in the adjustment limit; The system calculation process is updated according to the adjustment position to obtain the process optimization result; the adjustment position of the process optimization result is determined according to the adjustment limit, including: Determine an adjustment interval of the second process split item according to the adjustment limit, and obtain a current point position of the second process split item in the adjustment interval; Randomly determine the adjustment points within the adjustment range; Get the interval difference vector between the current point and the adjusted point; the modulus of the interval difference vector is the interval difference; Get the adjustment interval attribute of the adjustment interval; According to the adjustment interval attribute, a fluctuation reference library is determined; the fluctuation reference library stores a plurality of one-to-one corresponding matching vectors and preset values; Determine the calculation time fluctuation value according to the interval difference vector and the fluctuation reference library; According to the calculation time fluctuation value, determine the adjustment point set with the minimum system calculation time, and use the adjustment point set as the adjustment position; Among them, obtaining the interval difference vector between the current point and the adjustment point includes: If the interval difference between the current point and the adjustment point is positive, the interval difference vector is the preset first direction; If the interval difference between the current point and the adjustment point is negative, the interval difference vector is the preset second direction; Among them, according to the interval difference vector and the fluctuation reference library, the calculation time fluctuation value is determined, including: Obtaining a matching vector in a fluctuation comparison library; Match the interval difference vector and the matching vector, and determine the preset value corresponding to the matching vector that matches the matching; Each preset value is cumulatively calculated to obtain a calculation time fluctuation value.

Images