Engineering project risk assessment method and system

Abstract

The invention discloses an engineering project risk assessment method and system, and particularly relates to the field of risk assessment. Historical project data are acquired, key project feature information is extracted, risk influence paths are divided, a historical project risk trigger factor set and a risk transfer factor set are generated, and a risk propagation intensity matrix is generated by analyzing the risk propagation intensity value of each node. And further identifying high-risk nodes by using the risk propagation intensity matrix, and establishing a multi-dimensional risk coupling model according to the relevance of the risk transmission factor set, thereby comprehensively evaluating the propagation law and relevance characteristics of the risk. According to the method, a multi-dimensional risk coupling model and key project feature information are combined, a historical comprehensive risk assessment factor set is constructed, risks caused by resource supply and demand imbalance between nodes are identified, a final risk assessment result is generated, the risk identification precision and assessment efficiency of an engineering project are effectively improved, and a scientific decision basis is provided for engineering management.

Description

Technical Field

[0001] The present invention relates to the technical field of risk assessment, and more specifically, to a method and system for risk assessment of an engineering project. Background Art

[0002] Engineering projects have the characteristics of complex tasks, uneven resource distribution, diverse dependencies, and significant external environmental influences, which makes the risks in the project often have the characteristics of multi-factor triggering, multi-path propagation, and high correlation. Most of the existing engineering project risk assessment methods only focus on a single risk point or local risk propagation, and lack systematic analysis methods for complex problems such as the coupling relationship between multiple risk factors and resource imbalance. At the same time, traditional methods often rely on subjective experience or simple statistical analysis, which makes it difficult to fully quantify the intensity of risk propagation and the dynamic evolution process, resulting in low accuracy of risk identification and evaluation efficiency. In addition, the uneven distribution of resources in engineering projects and the dynamic changes in the external environment have further aggravated the complexity of risk propagation and increased the difficulty of management.

[0003] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method and system for risk assessment of an engineering project to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for risk assessment of an engineering project comprises the following steps:

[0007] Obtain historical engineering project data, and extract key project feature information based on the historical engineering project data;

[0008] Based on key project feature information, risk impact paths are divided to form a set of historical project risk trigger factors and risk transfer factors;

[0009] Analyze the risk trigger factor set and risk transmission factor set of historical projects, determine the risk propagation intensity value of each path node, and generate a risk propagation intensity matrix;

[0010] In the risk transmission intensity matrix, high-risk nodes are identified, and a multidimensional risk coupling model is established based on the correlation of the risk transmission factor set;

[0011] Based on the multi-dimensional risk coupling model and combined with key project characteristic information, a historical comprehensive risk assessment factor set is constructed;

[0012] Based on the historical comprehensive risk assessment factor set, the resource imbalance risk between nodes is identified and the risk assessment results are generated.

[0013] In a preferred embodiment, historical engineering project data is obtained, and key project feature information is extracted based on the historical engineering project data, specifically:

[0014] Obtain task breakdown structure and resource allocation data from historical engineering project data;

[0015] According to the hierarchical relationship of the task decomposition structure, the dependency paths between tasks are extracted to form a task dependency feature set;

[0016] According to the resource utilization efficiency and distribution in the resource allocation data, a resource feature matrix is ​​formed;

[0017] Combined with the historical fluctuation trends of environmental variables, key project feature information is output.

[0018] In a preferred embodiment, the risk impact paths are divided according to the key project feature information to form a historical project risk trigger factor set and a risk transfer factor set, specifically:

[0019] According to the task dependency feature set in the key project feature information, determine the interrelationship between tasks, divide the potential risk trigger points, and form an initial risk trigger factor set;

[0020] Confirm the risk transfer relationship between adjacent tasks in the task dependency feature set, identify the risk propagation path, extract the transmission strength of the associated tasks, and form the initial transmission factor set of the risk path;

[0021] Combined with the resource characteristic matrix, evaluate the risk weighting factors caused by uneven resource allocation, adjust the initial risk trigger factor set and transfer factor set, and generate the revised historical project risk trigger factor set and risk transfer factor set;

[0022] According to the volatility characteristics of environmental variables, the scenario sensitivity of the risk trigger factor set and the risk transfer factor set are confirmed to generate the historical project risk trigger factor set and the risk transfer factor set.

[0023] In a preferred embodiment, the historical project risk trigger factor set and risk transfer factor set are analyzed to determine the risk propagation intensity value of each path node and generate a risk propagation intensity matrix, specifically:

[0024] Statistical analysis of the risk probability of a single node in the risk trigger factor set of historical projects;

[0025] Combined with the risk transfer factor set, the risk transfer coefficients of a single node and surrounding nodes are determined to form a node transfer strength matrix;

[0026] Normalize the node transmission intensity matrix to obtain the standardized transmission intensity matrix;

[0027] Based on the propagation paths between nodes in the standardized propagation intensity matrix, the risk propagation network structure is determined and the risk propagation intensity matrix is ​​generated.

[0028] In a preferred embodiment, in the risk transmission intensity matrix, high-risk nodes are identified, and a multi-dimensional risk coupling model is established according to the correlation of the risk transmission factor set, specifically:

[0029] Based on the risk propagation intensity matrix, nodes with risk propagation intensity values ​​greater than the preset threshold are extracted to identify high-risk node sets;

[0030] According to the high-risk node set, determine the risk transfer path and transmission strength between each node and the remaining nodes, and generate a risk transfer network;

[0031] Combined with the risk transfer factor set, the coupling relationship of the risk transfer network is judged, the coupling effect between high-risk nodes is identified, and the node coupling strength matrix is ​​generated;

[0032] The node coupling intensity matrix is ​​decomposed in multiple dimensions, the main coupling factors affecting risks are extracted, and a multidimensional risk coupling model is established.

[0033] In a preferred embodiment, based on the multi-dimensional risk coupling model and combined with key project feature information, a historical comprehensive risk assessment factor set is constructed, specifically:

[0034] Based on the multi-dimensional risk coupling model, the coupling strength of high-risk nodes and their positional relationship in the risk transmission network are extracted to form a node risk coupling feature set.

[0035] Map the node risk coupling feature set with the task dependency feature set in the key project feature information to determine the main impact range of the node risk coupling;

[0036] Combined with the resource characteristic matrix, the regulatory effect of resource configuration on node risk coupling is determined, and the resource regulation factor matrix is ​​generated;

[0037] According to the historical fluctuation trend of environmental variables, the impact of external conditions on node risk coupling is evaluated to generate a set of environmental impact factors;

[0038] The node risk coupling feature set, resource adjustment factor matrix and environmental impact factor set are integrated to construct a historical comprehensive risk assessment factor set.

[0039] In a preferred embodiment, based on the historical comprehensive risk assessment factor set, the resource imbalance risk between nodes is identified and the risk assessment result is generated, specifically:

[0040] Based on the historical comprehensive risk assessment factor set, the resource demand characteristics and resource supply characteristics of key nodes are extracted to generate a node resource characteristic matrix;

[0041] Based on the resource supply and demand matching degree of each node in the node resource feature matrix, a node resource matching degree dataset is generated;

[0042] According to the nodes in the node resource matching degree data set that are below the preset threshold, combined with the resource adjustment factor matrix, node pairs with imbalanced resource supply and demand are identified to generate a resource imbalance risk matrix;

[0043] According to the correlation between imbalance nodes in the resource imbalance risk matrix, a resource imbalance propagation network is established to evaluate the risk range of resource imbalance diffusion;

[0044] The resource imbalance risk matrix, resource imbalance propagation network and environmental impact factor set are integrated to generate risk assessment results.

[0045] On the other hand, the present invention provides a project risk assessment system, including an information extraction module, a risk path division module, a risk propagation analysis module, a risk node identification module, an assessment factor construction module, and an assessment result generation module;

[0046] The information extraction module obtains historical engineering project data and extracts key project feature information based on the historical engineering project data;

[0047] The risk path division module divides the risk impact path according to key project feature information to form a historical project risk trigger factor set and a risk transmission factor set;

[0048] The risk propagation analysis module analyzes the risk trigger factor set and risk transfer factor set of historical projects, determines the risk propagation intensity value of each path node, and generates a risk propagation intensity matrix;

[0049] The risk node identification module identifies high-risk nodes in the risk transmission intensity matrix and establishes a multi-dimensional risk coupling model based on the correlation of the risk transmission factor set;

[0050] The assessment factor construction module constructs a historical comprehensive risk assessment factor set based on a multi-dimensional risk coupling model and combined with key project feature information;

[0051] The assessment result generation module identifies the resource imbalance risk between nodes based on the historical comprehensive risk assessment factor set and generates risk assessment results.

[0052] The technical effects and advantages of the engineering project risk assessment method and system of the present invention are as follows:

[0053] By acquiring historical engineering project data and extracting key project feature information, we can comprehensively analyze the impact of task dependencies, resource allocation characteristics, and environmental variables, providing an accurate data basis for risk assessment. By dividing the risk impact path and constructing a risk trigger factor set and a risk transmission factor set, we can fully capture multi-source risk factors, quantify the risk propagation intensity, and generate a risk propagation intensity matrix, thereby intuitively reflecting the dynamic propagation law of risks between project tasks. Using a multidimensional risk coupling model to identify high-risk nodes and their correlation can reveal the coupling effects and linkage mechanisms between multiple risks, effectively improving the comprehensiveness and accuracy of risk identification. Finally, by identifying resource imbalance risks and generating risk assessment results, we can provide project managers with scientific risk response strategies and optimization suggestions, significantly improving the efficiency of risk management and the reliability of decision-making, and are suitable for a variety of complex engineering projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A schematic diagram of a method for risk assessment of an engineering project according to the present invention;

[0055] Figure 2 The present invention is a schematic diagram of the structure of an engineering project risk assessment system. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] Example 1

[0058] Figure 1 The present invention provides a method for risk assessment of an engineering project, which comprises the following steps:

[0059] Obtain historical engineering project data, and extract key project feature information based on the historical engineering project data;

[0060] Based on key project feature information, risk impact paths are divided to form a set of historical project risk trigger factors and risk transfer factors;

[0061] Analyze the risk trigger factor set and risk transmission factor set of historical projects, determine the risk propagation intensity value of each path node, and generate a risk propagation intensity matrix;

[0062] In the risk transmission intensity matrix, high-risk nodes are identified, and a multidimensional risk coupling model is established based on the correlation of the risk transmission factor set;

[0063] Based on the multi-dimensional risk coupling model and combined with key project characteristic information, a historical comprehensive risk assessment factor set is constructed;

[0064] Based on the historical comprehensive risk assessment factor set, the resource imbalance risk between nodes is identified and the risk assessment results are generated.

[0065] Specifically, historical project data is obtained, and key project feature information is extracted based on the historical project data, including:

[0066] Obtain the task breakdown structure and resource allocation data from historical engineering project data; specifically, the task breakdown structure refers to a hierarchical structure that breaks down a complete engineering project into multiple subtasks or work packages; for example, if you want to build a building, you may break the project down into sub-projects such as foundation engineering, main construction, decoration and decoration, water and electricity installation, fire inspection and acceptance, and each sub-project can be further divided; resource allocation data means that in a project, resources may include manpower (personnel of different types of work or different levels of ability), equipment (such as cranes, generators, etc.), materials (such as steel, cement, etc.) and funds; resource allocation data records how these resources were allocated, used and scheduled in similar projects in the past; for example: how much labor input is required at different stages; how the equipment is scheduled (whether it is shared or dedicated, and when to use it); the consumption rate of materials and inventory changes, etc.

[0067] According to the hierarchical relationship of the task decomposition structure, the dependency paths between tasks are extracted to form a task dependency feature set. Specifically, the hierarchical relationship of the task decomposition structure refers to the step-by-step decomposition structure from the overall task to the subtask and then to the sub-subtask. The dependency path between tasks can be understood as follows: Task B can only be started after Task A is completed, so there is a dependency relationship from A to B. Some tasks can be performed in parallel, and some tasks must be performed serially.

[0068] According to the resource utilization efficiency and distribution in the resource allocation data, a resource feature matrix is ​​formed; specifically, the rows of the resource feature matrix may correspond to various subtasks or stages; the columns of the resource feature matrix may correspond to various types of resources (manpower, equipment, funds, etc.) or resource utilization indicators (utilization rate, idle time, etc.);

[0069] Combined with the historical fluctuation trend of environmental variables, key project characteristic information is output; specifically, environmental variables refer to the external environmental factors of the project, such as: market fluctuations (rising and falling prices of raw materials, changes in labor costs); changes in weather and geological conditions (the impact of heavy rain, typhoons, earthquakes, etc. on the construction period).

[0070] Specifically, based on key project feature information, the risk impact paths are divided to form a set of historical project risk trigger factors and risk transfer factors, including:

[0071] According to the task dependency feature set in the key project feature information, determine the interrelationship between tasks, divide the potential risk trigger points, and form the initial risk trigger factor set; specifically, dividing the potential risk trigger points usually means finding those task nodes that are most likely to generate risks and cause chain reactions; for example, a difficult construction task in the critical path, its delay will often drag down all subsequent related tasks; or a cross-departmental collaborative task, poor collaboration will affect the progress;

[0072] Confirm the risk transfer relationship between adjacent tasks in the task dependency feature set, identify the risk propagation path, extract the transmission strength of related tasks, and form an initial transmission factor set of the risk path; specifically, the risk transfer relationship between adjacent tasks can mean that if task A is delayed, then the adjacent task B will also incur corresponding delays or additional costs; if task A wastes or conflicts in the use of resources, will it affect the subsequent task B's inability to obtain resources in a timely manner? Identifying the risk propagation path is to connect these adjacent relationships in series according to the possible propagation order to form one or more risk propagation chains.

[0073] Combined with the resource characteristic matrix, evaluate the risk weighting factors caused by uneven resource allocation, adjust the initial risk trigger factor set and transfer factor set, and generate the revised historical project risk trigger factor set and risk transfer factor set;

[0074] According to the volatility characteristics of environmental variables, the scenario sensitivity of the risk trigger factor set and the risk transfer factor set is confirmed to generate the historical project risk trigger factor set and the risk transfer factor set. Specifically, scenario sensitivity analysis can be understood as the impact on risk triggering or risk transfer if the external environment changes to different degrees.

[0075] Specifically, the risk trigger factor set and risk transmission factor set of historical projects are analyzed, the risk propagation intensity value of each path node is calculated, and the risk propagation intensity matrix is ​​generated, including:

[0076] Statistically calculate the single-node risk probability in the risk trigger factor set of historical projects; for example, if design changes occurred 3 times in the past 10 projects, the single-node risk probability of design changes is 30%;

[0077] Combined with the risk transfer factor set, the risk transfer coefficient between a single node and the surrounding nodes is determined to form a node transfer strength matrix; for example, if the risk probability of node A is 0.3, and the transfer factor shows that the influence coefficient of A on B is 0.5, then the risk transfer coefficient between B and A is 0.3*0.5=0.15; the node transfer strength matrix, in which each row and column corresponds to a node, and the matrix elements represent the transfer strength from the row node to the column node.

[0078] Normalize the node transmission intensity matrix to obtain the standardized transmission intensity matrix;

[0079] Based on the propagation paths between nodes in the standardized propagation intensity matrix, the risk propagation network structure is determined and the risk propagation intensity matrix is ​​generated.

[0080] Specifically, in the risk transmission intensity matrix, high-risk nodes are identified, and a multi-dimensional risk coupling model is established based on the correlation of the risk transmission factor set, including:

[0081] Based on the risk propagation intensity matrix, nodes with risk propagation intensity values ​​greater than the preset threshold are extracted to identify high-risk node sets;

[0082] According to the high-risk node set, determine the risk transfer path and transmission strength between each node and the remaining nodes, and generate a risk transfer network;

[0083] Combined with the risk transfer factor set, the coupling relationship of the risk transfer network is judged, the coupling effect between high-risk nodes is identified, and the node coupling strength matrix is ​​generated; specifically, the risk coupling effect refers to the phenomenon that the risks of two or more nodes will overlap or amplify each other, thereby increasing the overall risk level; the node coupling strength matrix can be understood as follows: the rows and columns of the node coupling strength matrix correspond to high-risk nodes; each element value in the matrix represents the degree of coupling between the two nodes;

[0084] The node coupling intensity matrix is ​​decomposed in multiple dimensions to extract the main coupling factors of risk impact and establish a multidimensional risk coupling model. Specifically, the multidimensional decomposition includes: resource dimension (insufficient resources or unfair distribution lead to mutual constraints between A and B); task timing dimension (delay of task A directly affects task B); and environmental dimension (a certain external risk has the same or synergistic impact on A and B at the same time).

[0085] Specifically, based on the multi-dimensional risk coupling model and combined with key project characteristic information, a historical comprehensive risk assessment factor set is constructed, including:

[0086] Based on the multi-dimensional risk coupling model, the coupling strength of high-risk nodes and their positional relationship in the risk transmission network are extracted to form a node risk coupling feature set; specifically, the positional relationship refers to whether the high-risk node is located at the core or edge of the entire risk network; whether it is on the critical path; and whether it is the intersection of multiple risk transmission pathways.

[0087] Map the node risk coupling feature set with the task dependency feature set in the key project feature information to determine the main impact range of the node risk coupling;

[0088] Combined with the resource characteristic matrix, the regulatory effect of resource configuration on node risk coupling is determined, and the resource regulation factor matrix is ​​generated;

[0089] According to the historical fluctuation trend of environmental variables, the impact of external conditions on node risk coupling is evaluated to generate a set of environmental impact factors;

[0090] The node risk coupling feature set, resource adjustment factor matrix and environmental impact factor set are integrated to construct a historical comprehensive risk assessment factor set.

[0091] Specifically, based on the historical comprehensive risk assessment factor set, the resource imbalance risk between nodes is identified and the risk assessment results are generated, including:

[0092] Based on the historical comprehensive risk assessment factor set, the resource demand characteristics and resource supply characteristics of key nodes are extracted to generate a node resource characteristic matrix; specifically, resource demand and resource supply refer to how many resources each key node needs, whether these resources can be provided in time in history or forecast, and whether there is a resource conflict (multiple nodes compete for the same resource);

[0093] Based on the resource supply and demand matching degree of each node in the node resource feature matrix, a node resource matching degree data set is generated; for example, if the demand = 10 and the supply = 12, the matching degree can be considered to be 1.2; if the supply = 5, the matching degree = 0.5;

[0094] According to the nodes in the node resource matching degree data set that are below the preset threshold, combined with the resource adjustment factor matrix, node pairs with imbalanced resource supply and demand are identified to generate a resource imbalance risk matrix;

[0095] According to the correlation between imbalance nodes in the resource imbalance risk matrix, a resource imbalance propagation network is established to evaluate the risk range of resource imbalance diffusion;

[0096] The resource imbalance risk matrix, resource imbalance propagation network and environmental impact factor set are integrated to generate risk assessment results.

[0097] Example 2

[0098] The difference between Example 2 of the present invention and Example 1 is that this example introduces a project risk assessment system.

[0099] Figure 2 A structural schematic diagram of a project risk assessment system of the present invention is given, which includes an information extraction module, a risk path division module, a risk propagation analysis module, a risk node identification module, an assessment factor construction module and an assessment result generation module;

[0100] The information extraction module obtains historical engineering project data and extracts key project feature information based on the historical engineering project data;

[0101] The risk path division module divides the risk impact path according to key project feature information to form a historical project risk trigger factor set and a risk transmission factor set;

[0102] The risk propagation analysis module analyzes the risk trigger factor set and risk transfer factor set of historical projects, determines the risk propagation intensity value of each path node, and generates a risk propagation intensity matrix;

[0103] The risk node identification module identifies high-risk nodes in the risk transmission intensity matrix and establishes a multi-dimensional risk coupling model based on the correlation of the risk transmission factor set;

[0104] The assessment factor construction module constructs a historical comprehensive risk assessment factor set based on a multi-dimensional risk coupling model and combined with key project feature information;

[0105] The assessment result generation module identifies the resource imbalance risk between nodes based on the historical comprehensive risk assessment factor set and generates risk assessment results.

[0106] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0107] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0108] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0109] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0110] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0111] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0112] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0113] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0114] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0115] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for risk assessment of an engineering project, characterized in that: The steps include: Obtain historical engineering project data, and extract key project feature information based on the historical engineering project data; Based on key project feature information, risk impact paths are divided to form a set of historical project risk trigger factors and risk transfer factors; Analyze the risk trigger factor set and risk transmission factor set of historical projects, determine the risk propagation intensity value of each path node, and generate a risk propagation intensity matrix; In the risk transmission intensity matrix, high-risk nodes are identified, and a multidimensional risk coupling model is established based on the correlation of the risk transmission factor set; Based on the multi-dimensional risk coupling model and combined with key project characteristic information, a historical comprehensive risk assessment factor set is constructed; Based on the historical comprehensive risk assessment factor set, the resource imbalance risk between nodes is identified and the risk assessment results are generated.

2. A method for risk assessment of an engineering project according to claim 1, characterized in that: Obtain historical project data and extract key project feature information based on the historical project data, specifically: Obtain task breakdown structure and resource allocation data from historical engineering project data; According to the hierarchical relationship of the task decomposition structure, the dependency paths between tasks are extracted to form a task dependency feature set; According to the resource utilization efficiency and distribution in the resource allocation data, a resource feature matrix is ​​formed; Combined with the historical fluctuation trends of environmental variables, key project feature information is output.

3. A method for risk assessment of an engineering project according to claim 1, characterized in that: According to the key project characteristic information, the risk impact path is divided to form the historical project risk trigger factor set and risk transmission factor set, which are as follows: According to the task dependency feature set in the key project feature information, determine the interrelationship between tasks, divide the potential risk trigger points, and form an initial risk trigger factor set; Confirm the risk transfer relationship between adjacent tasks in the task dependency feature set, identify the risk propagation path, extract the transmission strength of the associated tasks, and form the initial transmission factor set of the risk path; Combined with the resource characteristic matrix, evaluate the risk weighting factors caused by uneven resource allocation, adjust the initial risk trigger factor set and transfer factor set, and generate the revised historical project risk trigger factor set and risk transfer factor set; According to the volatility characteristics of environmental variables, the scenario sensitivity of the risk trigger factor set and the risk transfer factor set are confirmed to generate the historical project risk trigger factor set and the risk transfer factor set.

4. A method for risk assessment of an engineering project according to claim 1, characterized in that: The risk trigger factor set and risk transmission factor set of historical projects are analyzed, the risk propagation intensity value of each path node is calculated, and the risk propagation intensity matrix is ​​generated, which is as follows: Statistical analysis of the risk probability of a single node in the risk trigger factor set of historical projects; Combined with the risk transfer factor set, the risk transfer coefficients of a single node and surrounding nodes are determined to form a node transfer strength matrix; Normalize the node transmission intensity matrix to obtain the standardized transmission intensity matrix; Based on the propagation paths between nodes in the standardized propagation intensity matrix, the risk propagation network structure is determined and the risk propagation intensity matrix is ​​generated.

5. A method for risk assessment of an engineering project according to claim 1, characterized in that: In the risk transmission intensity matrix, high-risk nodes are identified, and a multidimensional risk coupling model is established based on the correlation of the risk transmission factor set, specifically: Based on the risk propagation intensity matrix, nodes with risk propagation intensity values ​​greater than the preset threshold are extracted to identify high-risk node sets; According to the high-risk node set, determine the risk transfer path and transmission strength between each node and the remaining nodes, and generate a risk transfer network; Combined with the risk transfer factor set, the coupling relationship of the risk transfer network is judged, the coupling effect between high-risk nodes is identified, and the node coupling strength matrix is ​​generated; The node coupling intensity matrix is ​​decomposed in multiple dimensions, the main coupling factors affecting risks are extracted, and a multidimensional risk coupling model is established.

6. A method for risk assessment of an engineering project according to claim 1, characterized in that: Based on the multi-dimensional risk coupling model and combined with key project characteristic information, a historical comprehensive risk assessment factor set is constructed, specifically: Based on the multi-dimensional risk coupling model, the coupling strength of high-risk nodes and their positional relationship in the risk transmission network are extracted to form a node risk coupling feature set. Map the node risk coupling feature set with the task dependency feature set in the key project feature information to determine the main impact range of the node risk coupling; Combined with the resource characteristic matrix, the regulatory effect of resource configuration on node risk coupling is determined, and the resource regulation factor matrix is ​​generated; According to the historical fluctuation trend of environmental variables, the impact of external conditions on node risk coupling is evaluated to generate a set of environmental impact factors; The node risk coupling feature set, resource adjustment factor matrix and environmental impact factor set are integrated to construct a historical comprehensive risk assessment factor set.

7. A method for risk assessment of an engineering project according to claim 1, characterized in that: Based on the historical comprehensive risk assessment factor set, the resource imbalance risk between nodes is identified and the risk assessment results are generated, specifically: Based on the historical comprehensive risk assessment factor set, the resource demand characteristics and resource supply characteristics of key nodes are extracted to generate a node resource characteristic matrix; Based on the resource supply and demand matching degree of each node in the node resource feature matrix, a node resource matching degree dataset is generated; According to the nodes in the node resource matching degree data set that are below the preset threshold, combined with the resource adjustment factor matrix, node pairs with imbalanced resource supply and demand are identified to generate a resource imbalance risk matrix; According to the correlation between imbalance nodes in the resource imbalance risk matrix, a resource imbalance propagation network is established to evaluate the risk range of resource imbalance diffusion; The resource imbalance risk matrix, resource imbalance propagation network and environmental impact factor set are integrated to generate risk assessment results.

8. A project risk assessment system, used to implement a project risk assessment method according to any one of claims 1 to 8, characterized in that: It includes information extraction module, risk path division module, risk propagation analysis module, risk node identification module, assessment factor construction module and assessment result generation module; The information extraction module obtains historical engineering project data and extracts key project feature information based on the historical engineering project data; The risk path division module divides the risk impact path according to key project feature information to form a historical project risk trigger factor set and a risk transmission factor set; The risk propagation analysis module analyzes the risk trigger factor set and risk transfer factor set of historical projects, determines the risk propagation intensity value of each path node, and generates a risk propagation intensity matrix; The risk node identification module identifies high-risk nodes in the risk transmission intensity matrix and establishes a multi-dimensional risk coupling model based on the correlation of the risk transmission factor set; The assessment factor construction module constructs a historical comprehensive risk assessment factor set based on a multi-dimensional risk coupling model and combined with key project feature information; The assessment result generation module identifies the resource imbalance risk between nodes based on the historical comprehensive risk assessment factor set and generates risk assessment results.

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