Intelligent management and control system and method for scientific research project budget execution

Abstract

The invention relates to the field of scientific research project management, in particular to an intelligent management and control system and method for scientific research project budget execution, and the system comprises a data collection module, a budget analysis module, an execution monitoring module, a feedback adjustment module and a decision support module. Through modular design, the system realizes whole-process monitoring and intelligent adjustment of scientific research project budget. The data acquisition module can acquire budget-related data in real time, so that the timeliness and accuracy of data input are ensured; the budget analysis module generates stage budget demand prediction based on the collected multi-dimensional data to ensure that budget distribution is more reasonable; the execution monitoring module provides real-time budget execution monitoring through a deviation monitoring algorithm, so that the risk of hyper-branch or insufficient budget is reduced; the feedback adjustment module dynamically adjusts budget allocation according to monitoring feedback, and the adaptability of fund allocation is ensured; the decision support module provides management suggestions, and improves the accuracy and decision efficiency of scientific research project budget management.

Description

Technical Field

[0001] The present invention relates to the field of scientific research project management, and in particular to a scientific research project budget execution intelligent management and control system and method thereof. Background Art

[0002] In scientific research project management, budget management is a key factor in the smooth progress of the project. Scientific research projects usually involve multiple stages, each stage has different funding requirements, and as the project progresses, budget requirements may change dynamically. In the traditional budget management process, the budget of a scientific research project is generally set at the beginning of the project and allocated to each stage in a one-time manner. However, due to the complexity and uncertainty of scientific research projects, the actual budget consumption often deviates from the budget set at the beginning. Traditional budget management methods are usually carried out manually, which makes it difficult to achieve dynamic prediction, real-time monitoring and timely adjustment of budget requirements, resulting in insufficient accuracy in fund allocation, low efficiency, and easy waste or shortage of funds.

[0003] With the development of information technology, some scientific research project management systems have begun to use data analysis and information integration technology to improve budget management. However, most of the current scientific research budget management technologies rely on fixed budget allocation methods, lack an effective dynamic prediction mechanism, and are difficult to adapt to the multi-stage and changing funding needs of scientific research projects. In addition, during the budget execution process, traditional management methods are difficult to monitor budget consumption in real time, resulting in abnormal fund consumption or deviation from the plan. It is difficult to detect in time, which in turn affects the smooth execution of scientific research projects. Therefore, the existing scientific research project budget management methods urgently need an intelligent solution that can obtain budget consumption information in real time and dynamically adjust budget allocation to improve the accuracy and flexibility of scientific research project budget management.

[0004] In traditional scientific research project budget management, budget allocation is usually based on the initial estimates of the project, and there is a lack of feedback and adjustment of real-time data during the project execution. The traditional budget allocation method relies on the initial budget planning of the project manager and lacks a dynamic prediction mechanism supported by data. Due to the uncertainty of scientific research projects, the actual budget requirements at each stage of the project may deviate greatly from the budget set at the initial stage, resulting in excess or insufficient funds at certain stages of the project, affecting the efficiency of the scientific research project. In addition, traditional budget allocation is often fixed and cannot dynamically adapt to changes in project requirements, which brings many inconveniences in the actual budget execution process. The lack of real-time data support and dynamic prediction directly affects the efficiency and accuracy of the use of scientific research project funds.

[0005] In the existing scientific research project management, the monitoring of budget execution is often lagging, and usually a retrospective review is conducted after the project is completed, which makes it difficult to timely discover and correct anomalies or deviations in budget consumption during the project execution process. When the project budget is overspent or funds are wasted, managers often find it difficult to learn and take measures in a timely manner. This lagging monitoring method brings great risks in the actual implementation of scientific research projects, especially in some project stages where budget consumption is more concentrated, which may lead to funding shortages and affect the smooth implementation of the project. In addition, traditional monitoring methods have more manual operations, are time-consuming and inefficient, and are difficult to meet the needs of scientific research projects for real-time monitoring and rapid response.

[0006] The budget management of scientific research projects requires timely adjustments to budget allocations based on changes in actual conditions, but existing technologies often lack a dynamic budget adjustment mechanism and cannot make real-time adjustments based on deviation information in budget execution. In traditional budget management, even if budget deviations are found, there is a lack of automatic adjustment algorithms based on deviation data, which requires managers to make manual adjustments, which is time-consuming and difficult to accurately respond to changes in funding needs. The fixed allocation method in traditional methods cannot be flexibly adjusted according to actual needs, especially when the budget execution deviation is large. The traditional static allocation method will further amplify the budget imbalance, resulting in inefficient budget management of scientific research projects, poor adaptability, and difficulty in meeting the dynamic needs of complex scientific research projects. Summary of the invention

[0007] The purpose of the present invention is to provide a scientific research project budget execution intelligent management and control system and method and method thereof to solve the technical problems raised in the above-mentioned background technology.

[0008] Based on the above ideas, the present invention provides the following technical solutions:

[0009] A scientific research project budget execution intelligent management and control system and method thereof, comprising:

[0010] Data collection module, budget analysis module, execution monitoring module, feedback adjustment module and decision support module;

[0011] The data acquisition module is used to obtain various budget data of scientific research projects in real time and transmit the budget data to the budget analysis module. The budget data includes historical budget data, real-time budget execution data, project phase data and cost composition data; the data acquisition module includes an interface circuit connected to each financial subsystem, a data buffer and a data transmission unit connected to the server;

[0012] The budget analysis module is used to predict the budget requirements of different stages based on the budget demand prediction algorithm according to the historical budget data, current budget execution data and project stage information input by the data acquisition module; the budget analysis module includes a data parsing unit and a computing core, the data parsing unit formats the received budget data, the computing core executes the budget demand prediction algorithm according to the formatted data, and the output prediction result is transmitted to the feedback adjustment module as the basis for budget allocation in subsequent stages;

[0013] The execution monitoring module is used to monitor the budget execution of scientific research projects in real time, detect the deviation of budget consumption through the budget deviation monitoring algorithm, and automatically trigger a warning signal when the budget deviation exceeds a preset threshold;

[0014] The execution monitoring module includes a difference analysis unit and an alarm trigger unit. The difference analysis unit calculates the difference between the actual budget consumption and the predicted budget demand based on the budget deviation monitoring algorithm. The alarm trigger unit generates an alarm signal when the deviation exceeds a preset threshold and outputs the deviation information to the feedback adjustment module.

[0015] The feedback adjustment module is used to dynamically adjust the budget allocation in the subsequent stage according to the budget deviation information of the execution monitoring module and the predicted data of the budget analysis module; the feedback adjustment module includes a dynamic adjustment unit and an output control unit, the dynamic adjustment unit executes the budget adjustment algorithm based on the budget deviation and the predicted budget value to calculate the new budget allocation value, and the output control unit sends the adjustment result to the decision support module and synchronously updates it to the budget analysis module;

[0016] The decision support module is used to generate a scientific research project budget management report based on the adjusted budget data provided by the feedback adjustment module, and provide suggestions for project management; the decision support module includes a report generation unit and a decision support unit, the report generation unit receives the budget adjustment data of the feedback adjustment module and generates a detailed budget execution report, and the decision support unit analyzes the fund utilization efficiency of the scientific research project based on the adjusted budget data to provide decision-making basis for managers.

[0017] Through modular design, the system realizes the whole process monitoring and intelligent adjustment of scientific research project budgets. The data acquisition module can obtain budget-related data in real time to ensure the timeliness and accuracy of data input; the budget analysis module generates periodic budget demand forecasts based on the collected multi-dimensional data to ensure more reasonable budget allocation; the execution monitoring module provides real-time budget execution monitoring through deviation monitoring algorithms to reduce the risk of overspending or under-budgeting; the feedback adjustment module dynamically adjusts budget allocation according to monitoring feedback to ensure the adaptability of fund allocation; the decision support module provides management suggestions to improve the accuracy and decision-making efficiency of scientific research project budget management.

[0018] The budget analysis module includes a budget demand prediction algorithm, which is used to predict the budget demand of different project stages based on historical budget data, current consumption data and project stage data, and solve the problem of rational budget allocation of scientific research projects. The budget demand prediction algorithm includes the following steps:

[0019] S1. Input historical budget data, current consumption data and project phase data;

[0020] S2, calculate the forecast budget demand value;

[0021] S3. Output the predicted budget demand value to the feedback adjustment module as the initial basis for the next stage of budget allocation.

[0022] The budget demand forecasting algorithm conducts comprehensive analysis based on historical data and current data, making the budget demand forecasting more accurate, thereby ensuring the rationality of budget allocation at each stage of scientific research projects and reducing the waste or shortage of funds. The phased budget forecasting function of the algorithm provides the system with accurate budget planning, improving the scientificity and applicability of budget allocation.

[0023] Preferably, the calculation formula of the budget demand prediction algorithm is:

[0024] P T =α×H T-1 +β×C T-1 +γ×E

[0025] Among them, P T is the budget demand value for the predicted Tth stage;

[0026] H T-1 Indicates the historical budget data of the previous period;

[0027] C T-1 The actual budget consumption in the previous stage;

[0028] E is the experience adjustment factor for the overall project budget;

[0029] α, β, and γ are set weight parameters, which are used to adjust the impact of historical budget, current consumption, and experience factors on the budget forecast value respectively.

[0030] By comprehensively considering three data sources, namely historical budget, current consumption and experience factors, an accurate budget forecast value is generated, which effectively improves the accuracy of budget demand forecast. The setting of parameters α, β and γ enables the system to adjust budget demand according to different project stages, improves the flexibility of budget allocation for scientific research projects, and makes the forecast results more in line with changes in project demand.

[0031] Preferably, the execution monitoring module includes a budget deviation monitoring algorithm for calculating the budget execution deviation and triggering a deviation warning, and the budget deviation monitoring algorithm includes the following steps:

[0032] S1. Real-time collection of current actual budget consumption data;

[0033] S2. Calculate the current budget execution deviation rate according to the deviation formula;

[0034] S3. If the deviation rate exceeds the set threshold, a deviation warning is generated and the deviation rate is output to the feedback adjustment module for budget adjustment.

[0035] It realizes real-time monitoring of scientific research project budgets, can quickly identify the deviation between budget execution and forecast budget, and triggers an alarm when the deviation exceeds the threshold, providing data support for timely correction and adjustment, and reducing the risk of budget out of control. At the same time, real-time feedback of deviation information can enhance managers' insight into the execution of project budgets and help them respond flexibly in the decision-making process.

[0036] Preferably, the deviation calculation formula of the budget deviation monitoring algorithm includes:

[0037]

[0038] Among them, D T is the budget deviation rate in stage T;

[0039] C T The current actual budget consumption;

[0040] P T Forecast value for budget demand in the current period.

[0041] The deviation rate D T It is used to identify deviations from budget execution and output them to the feedback adjustment module when the deviation exceeds the preset threshold.

[0042] By calculating the deviation rate to quantify the budget execution deviation, it is convenient to monitor in real time whether the budget execution exceeds the forecast range. The deviation rate calculation formula is simple and easy to implement. It provides quantitative deviation data to ensure the efficiency and accuracy of budget monitoring. The deviation rate information is used as the basis for the budget adjustment of the feedback adjustment module, which effectively improves the system's response speed when dealing with budget deviations.

[0043] Preferably, the feedback adjustment module includes a dynamic budget adjustment algorithm for adjusting the budget allocation value of the next stage according to the current deviation rate and the budget prediction value, and the dynamic budget adjustment algorithm includes the following steps:

[0044] S1. Obtain the current stage deviation data provided by the execution monitoring module;

[0045] S2. Calculate the adjusted budget allocation value for the next stage according to the adjustment formula;

[0046] S3. Output the adjusted budget allocation value to the decision support module.

[0047] The dynamic budget adjustment algorithm is based on the dynamic feedback information of the deviation rate, and can flexibly adjust the budget allocation for the next stage, so that the budget execution is more in line with the actual needs of the project and avoid excessive waste or shortage of funds. By introducing dynamic budget adjustment, the system has adaptive capabilities, and even if there is a budget deviation in the project, it can quickly and reasonably reallocate the budget.

[0048] Preferably, the adjustment formula of the dynamic budget adjustment algorithm is:

[0049] P T+1 =P T +λ×D T ×P T

[0050] Among them, P T+1 Assign a value to the budget for the next period after the adjustment;

[0051] λ is the adjustment coefficient, which is used to control the impact of deviation in budget adjustment;

[0052] D T is the deviation rate of the current stage;

[0053] The adjusted budget allocation value P T+1 Used to guide budget execution in subsequent stages to ensure the rationality and effectiveness of budget allocation for scientific research projects.

[0054] Through the dynamic budget adjustment formula, the system can reasonably introduce the impact of deviations in the next stage of budget allocation to control the continuity and rationality of the budget. The adjustment coefficient provides control over the deviation correction, allowing the system to set the impact of deviations on budget adjustment according to actual needs, further enhancing the flexibility and effectiveness of budget management. The final adjusted budget value is used for budget guidance in the next stage, greatly improving the efficiency of the use of scientific research project funds.

[0055] A method for an intelligent management and control system for budget execution of scientific research projects, using the intelligent management and control system for budget execution of scientific research projects.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] Through the budget demand forecasting algorithm in the budget analysis module, the system can generate accurate budget demand forecast values ​​at each stage of the project based on historical budget data, current budget consumption and project experience factors. The forecasting formula comprehensively considers multi-dimensional data sources and uses the set weight parameters to adjust the impact of different data sources to ensure that the generated budget forecast results can closely match the project needs and reduce resource waste or shortages caused by excessive or insufficient budgets. This forecast value serves as the initial basis for the feedback adjustment module, providing a scientific guiding basis for subsequent budget allocation and significantly improving the rationality of budget allocation for scientific research projects.

[0058] The budget deviation monitoring algorithm in the execution monitoring module can quantify the difference between the current budget execution and the predicted budget in real time through the calculation formula of the deviation rate, providing intuitive data feedback. When the deviation in budget execution exceeds the preset threshold, it will automatically trigger a warning signal, prompting managers to take timely action to prevent the budget from getting out of control. At the same time, the deviation information will be fed back to the feedback adjustment module to ensure that the budget deviation can be quickly adjusted during the project implementation, thereby ensuring the timeliness of the budget management of scientific research projects and the continuity of execution. This monitoring mechanism effectively improves the response speed of the system, helps managers make quick decisions when the budget execution deviates from the established plan, and maintains the accuracy of the use of project funds.

[0059] The dynamic budget adjustment algorithm in the feedback adjustment module generates the budget adjustment allocation value for the next stage by comprehensively analyzing the current deviation rate and budget forecast value, thus realizing the dynamic adaptation of budget allocation. The adjustment coefficient in the dynamic adjustment formula is used to control the impact of deviation in budget adjustment, so that the system has adaptive capabilities when adjusting the budget. It can not only amplify the impact of deviation to quickly correct budget allocation, but also maintain budget continuity under stable demand to avoid excessive fluctuations. This function enables the system to respond quickly to changes in project funding needs, ensure that budget execution can be adjusted according to real-time conditions, improve the efficiency and adaptability of scientific research project funds, and meet the actual needs of projects at different stages. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 The present invention is a schematic diagram of the module relationship of an intelligent management and control system and method for budget execution of scientific research projects. DETAILED DESCRIPTION

[0061] A scientific research project budget execution intelligent management and control system and method thereof, comprising:

[0062] Data collection module, budget analysis module, execution monitoring module, feedback adjustment module and decision support module;

[0063] The data acquisition module is used to obtain various budget data of scientific research projects in real time and transmit the budget data to the budget analysis module. The budget data includes historical budget data, real-time budget execution data, project phase data and cost composition data; the data acquisition module includes an interface circuit connected to each financial subsystem, a data buffer and a data transmission unit connected to the server;

[0064] The budget analysis module is used to predict the budget requirements of different stages based on the budget demand prediction algorithm according to the historical budget data, current budget execution data and project stage information input by the data acquisition module; the budget analysis module includes a data parsing unit and a computing core, the data parsing unit formats the received budget data, the computing core executes the budget demand prediction algorithm according to the formatted data, and the output prediction result is transmitted to the feedback adjustment module as the basis for budget allocation in subsequent stages;

[0065] The execution monitoring module is used to monitor the budget execution of scientific research projects in real time, detect the deviation of budget consumption through the budget deviation monitoring algorithm, and automatically trigger a warning signal when the budget deviation exceeds a preset threshold;

[0066] The execution monitoring module includes a difference analysis unit and an alarm trigger unit. The difference analysis unit calculates the difference between the actual budget consumption and the predicted budget demand based on the budget deviation monitoring algorithm. The alarm trigger unit generates an alarm signal when the deviation exceeds a preset threshold and outputs the deviation information to the feedback adjustment module.

[0067] The feedback adjustment module is used to dynamically adjust the budget allocation in the subsequent stage according to the budget deviation information of the execution monitoring module and the predicted data of the budget analysis module; the feedback adjustment module includes a dynamic adjustment unit and an output control unit, the dynamic adjustment unit executes the budget adjustment algorithm based on the budget deviation and the predicted budget value to calculate the new budget allocation value, and the output control unit sends the adjustment result to the decision support module and synchronously updates it to the budget analysis module;

[0068] The decision support module is used to generate a scientific research project budget management report based on the adjusted budget data provided by the feedback adjustment module, and provide suggestions for project management; the decision support module includes a report generation unit and a decision support unit, the report generation unit receives the budget adjustment data of the feedback adjustment module and generates a detailed budget execution report, and the decision support unit analyzes the fund utilization efficiency of the scientific research project based on the adjusted budget data to provide decision-making basis for managers.

[0069] Through modular design, the system realizes the whole process monitoring and intelligent adjustment of scientific research project budgets. The data acquisition module can obtain budget-related data in real time to ensure the timeliness and accuracy of data input; the budget analysis module generates periodic budget demand forecasts based on the collected multi-dimensional data to ensure more reasonable budget allocation; the execution monitoring module provides real-time budget execution monitoring through deviation monitoring algorithms to reduce the risk of overspending or under-budgeting; the feedback adjustment module dynamically adjusts budget allocation according to monitoring feedback to ensure the adaptability of fund allocation; the decision support module provides management suggestions to improve the accuracy and decision-making efficiency of scientific research project budget management.

[0070] The budget analysis module includes a budget demand prediction algorithm, which is used to predict the budget demand of different project stages based on historical budget data, current consumption data and project stage data, and solve the problem of rational budget allocation of scientific research projects. The budget demand prediction algorithm includes the following steps:

[0071] S1. Input historical budget data, current consumption data and project phase data;

[0072] S2, calculate the forecast budget demand value;

[0073] S3. Output the predicted budget demand value to the feedback adjustment module as the initial basis for the next stage of budget allocation.

[0074] The budget demand forecasting algorithm conducts comprehensive analysis based on historical data and current data, making the budget demand forecasting more accurate, thereby ensuring the rationality of budget allocation at each stage of scientific research projects and reducing the waste or shortage of funds. The phased budget forecasting function of the algorithm provides the system with accurate budget planning, improving the scientificity and applicability of budget allocation.

[0075] The interface circuit and data buffer of the data acquisition module ensure the timeliness and accuracy of various budget data;

[0076] The data parsing unit standardizes multi-source data and eliminates differences in data formats;

[0077] The computing core executes the budget demand forecasting algorithm formula through the configured weight parameters, and adjusts the impact of each data on the budget in real time.

[0078] Preferably, the calculation formula of the budget demand prediction algorithm is:

[0079] P T =α×H T-1 +β×C T-1 +γ×E

[0080] Among them, P T is the budget demand value for the predicted Tth stage;

[0081] H T-1 Indicates the historical budget data of the previous period;

[0082] C T-1 The actual budget consumption in the previous stage;

[0083] E is the experience adjustment factor for the overall project budget;

[0084] α, β, and γ are set weight parameters, which are used to adjust the impact of historical budget, current consumption, and experience factors on the budget forecast value respectively.

[0085] By comprehensively considering three data sources, namely historical budget, current consumption and experience factors, an accurate budget forecast value is generated, which effectively improves the accuracy of budget demand forecast. The setting of parameters α, β and γ enables the system to adjust budget demand according to different project stages, improves the flexibility of budget allocation for scientific research projects, and makes the forecast results more in line with changes in project demand.

[0086] This formula is based on historical data, current consumption data and experience factors to comprehensively predict budget needs. The core idea is to generate forecast budget needs through multi-dimensional weight combination to adapt to the funding needs of different scientific research project stages. The weight parameters in the formula are set according to the actual budget consumption rules of the project to adjust the influence of each data item.

[0087] Through comprehensive weight analysis, the budget demand forecast value output by the formula is used to guide the budget allocation in the subsequent stage to ensure that the budget of the scientific research project is more in line with actual needs. The forecast results are passed to the feedback adjustment module through the budget analysis module to dynamically adjust the budget allocation.

[0088] Preferably, the execution monitoring module includes a budget deviation monitoring algorithm for calculating the budget execution deviation and triggering a deviation warning, and the budget deviation monitoring algorithm includes the following steps:

[0089] S1. Real-time collection of current actual budget consumption data;

[0090] S2. Calculate the current budget execution deviation rate according to the deviation formula;

[0091] S3. If the deviation rate exceeds the set threshold, a deviation warning is generated and the deviation rate is output to the feedback adjustment module for budget adjustment.

[0092] It realizes real-time monitoring of scientific research project budgets, can quickly identify the deviation between budget execution and forecast budget, and triggers an alarm when the deviation exceeds the threshold, providing data support for timely correction and adjustment, and reducing the risk of budget out of control. At the same time, real-time feedback of deviation information can enhance managers' insight into the execution of project budgets and help them respond flexibly in the decision-making process.

[0093] The data collection module provides real-time data input of actual budget consumption;

[0094] The variance analysis unit calls the budget deviation monitoring algorithm and performs the deviation calculation;

[0095] The warning trigger unit monitors the deviation rate in real time. Once it exceeds the preset threshold, it immediately generates a warning signal to achieve real-time feedback on the budget deviation.

[0096] Preferably, the deviation calculation formula of the budget deviation monitoring algorithm includes:

[0097]

[0098] Among them, D T is the budget deviation rate in stage T;

[0099] C T The current actual budget consumption;

[0100] P T Forecast value for budget demand in the current period.

[0101] The deviation rate D T It is used to identify deviations from budget execution and output them to the feedback adjustment module when the deviation exceeds the preset threshold.

[0102] By calculating the deviation rate to quantify the budget execution deviation, it is convenient to monitor in real time whether the budget execution exceeds the forecast range. The deviation rate calculation formula is simple and easy to implement. It provides quantitative deviation data to ensure the efficiency and accuracy of budget monitoring. The deviation rate information is used as the basis for the budget adjustment of the feedback adjustment module, which effectively improves the system's response speed when dealing with budget deviations.

[0103] This formula is a deviation monitoring algorithm based on budget execution, which calculates the deviation rate between the current actual budget consumption and the forecasted budget. It quantifies whether the current budget consumption meets the forecast requirements through the "deviation percentage" of budget execution. Large deviations may indicate that the budget consumption is unreasonable and needs to be adjusted in time.

[0104] The deviation rate system can identify whether the current budget exceeds the forecast range. When the preset deviation threshold (e.g. 10%) is exceeded, the system will automatically trigger a warning signal and pass the deviation information to the feedback adjustment module to dynamically adjust the budget allocation and ensure that the project operates within the deviation control range.

[0105] Preferably, the feedback adjustment module includes a dynamic budget adjustment algorithm for adjusting the budget allocation value of the next stage according to the current deviation rate and the budget prediction value, and the dynamic budget adjustment algorithm includes the following steps:

[0106] S1. Obtain the current stage deviation data provided by the execution monitoring module;

[0107] S2. Calculate the adjusted budget allocation value for the next stage according to the adjustment formula;

[0108] S3. Output the adjusted budget allocation value to the decision support module.

[0109] The dynamic budget adjustment algorithm is based on the dynamic feedback information of the deviation rate, and can flexibly adjust the budget allocation for the next stage, so that the budget execution is more in line with the actual needs of the project and avoid excessive waste or shortage of funds. By introducing dynamic budget adjustment, the system has adaptive capabilities, and even if there is a budget deviation in the project, it can quickly and reasonably reallocate the budget.

[0110] The dynamic adjustment unit of the feedback adjustment module executes a dynamic budget adjustment algorithm to incrementally adjust the budget through a parameterized adjustment formula;

[0111] After the budget is adjusted, the output control unit synchronizes the data to the decision support module for generating budget management reports.

[0112] The adjusted budget allocation value provides a dynamic adjustment basis for the next stage of budget management, effectively reducing the risk of accumulated budget deviations. The budget value is directly used for report generation in the decision support module, helping managers maintain scientificity and adaptability in budget allocation, and improving project fund utilization and management efficiency.

[0113] Preferably, the adjustment formula of the dynamic budget adjustment algorithm is:

[0114] P T+1 =P T +λ×D T ×P T

[0115] Among them, P T+1 Assign a value to the budget for the next period after the adjustment;

[0116] λ is the adjustment coefficient, which is used to control the impact of deviation in budget adjustment;

[0117] D T is the deviation rate of the current stage;

[0118] The adjusted budget allocation value P T+1 Used to guide budget execution in subsequent stages to ensure the rationality and effectiveness of budget allocation for scientific research projects.

[0119] Through the dynamic budget adjustment formula, the system can reasonably introduce the impact of deviations in the next stage of budget allocation to control the continuity and rationality of the budget. The adjustment coefficient provides control over the deviation correction, allowing the system to set the impact of deviations on budget adjustment according to actual needs, further enhancing the flexibility and effectiveness of budget management. The final adjusted budget value is used for budget guidance in the next stage, greatly improving the efficiency of the use of scientific research project funds.

[0120] The dynamic budget adjustment formula is used to adjust the budget requirements for the next stage based on the deviation rate of the current stage. The formula uses the deviation rate to make incremental or decremental adjustments to make the budget closer to actual needs. The adjustment coefficient controls the correction intensity of the deviation by setting a reasonable value to balance the impact of the predicted budget and actual deviation.

[0121] This formula enables the system to automatically adjust the budget allocation for the next stage, maintaining the flexibility and rationality of budget execution. The output budget value is passed to the decision support module to generate corresponding management reports and support subsequent decision analysis to ensure the efficient use of scientific research project funds.

[0122] A method for an intelligent management and control system for budget execution of scientific research projects, using the intelligent management and control system for budget execution of scientific research projects.

Claims

1. A scientific research project budget execution intelligent management and control system and method, characterized in that: include: Data collection module, budget analysis module, execution monitoring module, feedback adjustment module and decision support module; The data acquisition module is used to obtain various budget data of scientific research projects in real time and transmit the budget data to the budget analysis module. The budget data includes historical budget data, real-time budget execution data, project phase data and cost composition data; the data acquisition module includes an interface circuit connected to each financial subsystem, a data buffer and a data transmission unit connected to the server; The budget analysis module is used to predict the budget requirements of different stages based on the budget demand prediction algorithm according to the historical budget data, current budget execution data and project stage information input by the data acquisition module; the budget analysis module includes a data parsing unit and a computing core, the data parsing unit formats the received budget data, the computing core executes the budget demand prediction algorithm according to the formatted data, and the output prediction result is transmitted to the feedback adjustment module as the basis for budget allocation in subsequent stages; The execution monitoring module is used to monitor the budget execution of scientific research projects in real time, detect the deviation of budget consumption through the budget deviation monitoring algorithm, and automatically trigger a warning signal when the budget deviation exceeds a preset threshold; The execution monitoring module includes a difference analysis unit and an alarm trigger unit. The difference analysis unit calculates the difference between the actual budget consumption and the predicted budget demand based on the budget deviation monitoring algorithm. The alarm trigger unit generates an alarm signal when the deviation exceeds a preset threshold and outputs the deviation information to the feedback adjustment module. The feedback adjustment module is used to dynamically adjust the budget allocation in the subsequent stage according to the budget deviation information of the execution monitoring module and the predicted data of the budget analysis module; the feedback adjustment module includes a dynamic adjustment unit and an output control unit, the dynamic adjustment unit executes the budget adjustment algorithm based on the budget deviation and the predicted budget value to calculate the new budget allocation value, and the output control unit sends the adjustment result to the decision support module and synchronously updates it to the budget analysis module; The decision support module is used to generate a scientific research project budget management report based on the adjusted budget data provided by the feedback adjustment module, and provide suggestions for project management; the decision support module includes a report generation unit and a decision support unit, the report generation unit receives the budget adjustment data of the feedback adjustment module and generates a detailed budget execution report, and the decision support unit analyzes the fund utilization efficiency of the scientific research project based on the adjusted budget data to provide decision-making basis for managers.

2. According to claim 1, a scientific research project budget execution intelligent management and control system and method thereof is characterized in that: The budget analysis module includes a budget demand prediction algorithm, which is used to predict the budget demand of different project stages based on historical budget data, current consumption data and project stage data, and solve the problem of rational budget allocation of scientific research projects. The budget demand prediction algorithm includes the following steps: S1. Input historical budget data, current consumption data and project phase data; S2, calculate the forecast budget demand value; S3. Output the predicted budget demand value to the feedback adjustment module as the initial basis for the next stage of budget allocation.

3. According to claim 2, a scientific research project budget execution intelligent management and control system and method thereof is characterized in that: The calculation formula of the budget demand forecasting algorithm is: P T =α×H T-1 +β×C T-1 +γ×E Among them, P T is the budget demand value for the predicted Tth stage; H T-1 Indicates the historical budget data of the previous period; C T-1 The actual budget consumption in the previous stage; E is the experience adjustment factor for the overall project budget; α, β, and γ are set weight parameters, which are used to adjust the impact of historical budget, current consumption, and experience factors on the budget forecast value respectively.

4. According to claim 3, a scientific research project budget execution intelligent management and control system and method thereof is characterized in that: The execution monitoring module includes a budget deviation monitoring algorithm for calculating the budget execution deviation and triggering a deviation warning. The budget deviation monitoring algorithm includes the following steps: S1. Real-time collection of current actual budget consumption data; S2. Calculate the current budget execution deviation rate according to the deviation formula; S3. If the deviation rate exceeds the set threshold, a deviation warning is generated and the deviation rate is output to the feedback adjustment module for budget adjustment.

5. According to claim 4, a scientific research project budget execution intelligent management and control system and method thereof is characterized in that: The deviation calculation formula of the budget deviation monitoring algorithm includes: Among them, D T is the budget deviation rate in stage T; C T The current actual budget consumption; P T Forecast value for budget demand in the current period. The deviation rate D T It is used to identify deviations from budget execution and output them to the feedback adjustment module when the deviation exceeds the preset threshold.

6. According to claim 5, a scientific research project budget execution intelligent management and control system and method thereof is characterized in that: The feedback adjustment module includes a dynamic budget adjustment algorithm for adjusting the budget allocation value of the next stage according to the current deviation rate and the budget prediction value. The dynamic budget adjustment algorithm includes the following steps: S1. Obtain the current stage deviation data provided by the execution monitoring module; S2. Calculate the adjusted budget allocation value for the next stage according to the adjustment formula; S3. Output the adjusted budget allocation value to the decision support module.

7. According to claim 6, a scientific research project budget execution intelligent management and control system and method thereof is characterized in that: The adjustment formula of the dynamic budget adjustment algorithm is: P T+1 =P T +λ×D T ×P T Among them, P T+1 Assign a value to the budget for the next period after the adjustment; λ is the adjustment coefficient, which is used to control the impact of deviation in budget adjustment; D T is the deviation rate of the current stage; The adjusted budget allocation value P T+1 Used to guide budget execution in subsequent stages to ensure the rationality and effectiveness of budget allocation for scientific research projects.

8. A method for intelligent management and control of scientific research project budget execution system, characterized in that: Use the scientific research project budget execution intelligent management and control system as described in any one of claims 1-7.

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