An intelligent construction management system and method based on data analysis

Abstract

The application discloses an intelligent construction management system and method based on data analysis, and belongs to the technical field of construction management, which comprises the following steps: acquiring original plan characteristic data and change estimation characteristic data of a target change task in a construction project, and generating a target change task basic change cost evaluation index; establishing a task relationship network among all tasks in the construction project; acquiring the number of affected tasks actually affected by the target change task in the completed tasks of the construction project, and then combining the target change task basic change cost evaluation index to generate a target change task change feasibility evaluation index; acquiring the change reason of the target change task in the construction project, and then combining the target change task change feasibility evaluation index to generate a target change task final change feasibility evaluation index, so that the target change task in the construction project is managed; and the application can optimize the resource allocation of construction and the precision of progress control.

Description

Technical Field

[0001] This invention belongs to the field of construction management technology, and in particular relates to an intelligent construction management system and method based on data analysis. Background Technology

[0002] During the implementation of complex construction projects, frequent occurrences of design changes, sudden changes in on-site geological conditions, or changes in external environmental factors necessitate dynamic adjustments to the construction tasks.

[0003] Current construction management techniques commonly rely on manual methods to estimate cost changes when handling task changes, such as rough estimations based on historical project data. They also use Gantt charts or the critical path method to analyze the impact of changes on subsequent tasks. However, these methods have the following limitations: manual estimation is limited by individual experience, making it difficult to comprehensively cover multiple cost dimensions such as project delays, material consumption fluctuations, and changes in labor costs. Furthermore, they cannot normalize and integrate cost factors of different dimensions, leading to biased assessment results. Gantt charts and the critical path method only provide a static view of progress and cannot effectively model the physical spatial dependencies and process sequence dependencies between tasks. When changes occur, it is difficult to dynamically track and quantify the actual chain effects on completed tasks, such as rework or additional resource consumption. In addition, existing techniques separate the assessment of the necessity of changes from feasibility analysis, failing to incorporate the mandatory nature of the reasons for changes (such as mandatory updates to safety regulations or adjustments to laws and policies) into a quantitative framework. This causes the decision-making process to ignore key external constraints, resulting in assessment results that are out of touch with actual project needs.

[0004] In summary, the specific shortcomings of existing construction management technologies are as follows: the evaluation dimensions are limited to the direct cost level, ignoring the indirect chain effects on completed tasks and potential rework costs; the analysis process lacks dynamic adaptability and cannot update the scope of impact in real time as the project progresses, resulting in the evaluation lagging behind the actual construction status; the decision-making basis is insufficient, and the mandatory characteristics of the reasons for changes are not integrated into the feasibility model, which can easily cause decisions to deviate from the core objectives of the project, ultimately leading to systemic risks such as resource waste and schedule delays. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent construction management system and method based on data analysis, which solves the aforementioned problems.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent construction management method based on data analysis, comprising:

[0007] Obtain the original planned feature data and the estimated feature data of the target change task in the construction project;

[0008] Based on the original planned characteristic data and the estimated characteristic data of the target change task in the construction project, a basic change cost assessment index for the target change task is generated.

[0009] Establish a task relationship network among all tasks in the construction project;

[0010] Based on the task relationship network, obtain the number of tasks affected by the actual impact of the target change task among the completed tasks of the construction project;

[0011] Based on the number of tasks affected by the actual impact of the target change task in the completed tasks of the construction project and the target change task basic change cost assessment index, establish a target change task change feasibility analysis model and generate a target change task change feasibility assessment index.

[0012] Obtain the reasons for the change of the target change task in the construction project, establish a necessity correction model based on the feasibility assessment index of the target change task and the reasons for the change of the target change task in the construction project, and generate the final feasibility assessment index of the target change task.

[0013] Based on the feasibility assessment index of the final change of objectives, the tasks for changing objectives in construction projects are managed.

[0014] Based on the above technical solutions, the present invention also provides the following optional technical solutions:

[0015] Further technical solutions: The specific method for generating the target change task basic change cost assessment index includes:

[0016] Based on the original planned characteristic data and the estimated change characteristic data of the target change task in the construction project, analyze all types of cost losses during the change of the target change task, and generate a basic change cost assessment index for the target change task; specifically:

[0017] Through the formula:

[0018] ;

[0019] Generate a target change task base change cost assessment index ;

[0020] In the formula, This represents the normalized value of the cost of the i-th type of change. This represents the weighting coefficient of the i-th type of change cost, and n represents the number of types of change costs.

[0021] Further technical solution: The method for generating the normalized value of the i-th change cost specifically includes:

[0022] By analyzing the original planned feature data and the estimated change feature data of the target change task in the construction project, the change cost of each feature of the target change task is analyzed when the change occurs, and a normalized value of the i-th change cost is generated; specifically:

[0023] Through the formula:

[0024] ;

[0025] Generate the normalized value of the i-th change cost. ;

[0026] In the formula, This represents the i-th originally planned feature data. This represents the i-th change prediction feature data corresponding to the i-th original planned feature data. This represents the feature loss threshold of the i-th feature of the target change task;

[0027] in ,like The normalized value of the i-th change cost The value of is 0.

[0028] Further technical solutions: The specific methods for generating the feasibility assessment index for the target change task include:

[0029] Based on the number of tasks affected by the target change task in the completed tasks of the construction project, a target change task impact index is generated.

[0030] Based on the target change task basic change cost assessment index and the target change task impact index, establish a target change task change feasibility analysis model and generate a target change task change feasibility assessment index.

[0031] Further technical solutions: The specific method for generating the target change task impact index includes:

[0032] By quantifying the degree of impact of the number of affected tasks in a construction project that are actually affected by the change in objectives, an impact index for the change in objectives is generated; specifically:

[0033] Through the formula:

[0034] ;

[0035] Generate target change task impact index ;

[0036] In the formula, This indicates the number of tasks affected. This indicates the number of tasks that have been completed in the construction project. This represents the set of affected tasks. This represents the j-th affected task. This represents the weight coefficient of the j-th affected task. This represents the percentage of the impact on the j-th affected task.

[0037] Further technical solution: The specific expression of the feasibility analysis model for target change and task change is as follows:

[0038] ;

[0039] In the expression, This represents the feasibility assessment index for changes in objectives and tasks. This represents the cost assessment index for the basic change of the target task. This represents the impact index of the task on the change of objectives. For adjustment coefficients, This is a constant term.

[0040] Further technical solutions: The specific method for generating the feasibility assessment index for the final change of the target change task includes:

[0041] Based on the reasons for the changes in the objectives and tasks in the construction project, generate a change necessity coefficient for the objectives and tasks.

[0042] A necessity correction model is established based on the necessity coefficient of the target change task and the feasibility assessment index of the target change task, and the final feasibility assessment index of the target change task is generated.

[0043] Further technical solution: The method for generating the necessity coefficient of the target change task specifically includes:

[0044] Through the formula:

[0045] ;

[0046] Generate the change necessity coefficient for the target change task. ;

[0047] In the formula, This represents the flag value for the kth necessary reason for the objective change task. This represents the weight coefficient of the kth necessary cause, and q represents the number of necessary causes.

[0048] Further technical solution: The expression of the necessity correction model is specifically as follows:

[0049] ;

[0050] In the expression, This represents the feasibility assessment index for the final change of the target task. This represents the necessity coefficient for changing the target task. This represents the feasibility assessment index for changes in objectives and tasks.

[0051] An intelligent construction management system based on data analysis, which executes the aforementioned intelligent construction management method based on data analysis, specifically includes:

[0052] The construction project data acquisition unit is used to acquire the original planned characteristic data and the estimated change characteristic data of the target change tasks in the construction project;

[0053] The preliminary analysis unit is used to generate a basic change cost assessment index for target change tasks based on the original planned characteristic data and change estimate characteristic data of the target change tasks in the construction project.

[0054] The task network establishment unit is used to establish a task relationship network among all tasks in a construction project.

[0055] The relationship network data acquisition unit is used to obtain the number of tasks affected by the actual impact of target change tasks among the completed tasks of the construction project based on the task relationship network.

[0056] The comprehensive analysis unit is used to establish a feasibility analysis model for target change tasks based on the number of tasks affected by the actual impact of target change tasks in the completed tasks of the construction project and the basic change cost assessment index of target change tasks, and to generate a feasibility assessment index for target change tasks.

[0057] The final analysis unit is used to obtain the reasons for the change of the target change task in the construction project, establish a necessity correction model based on the feasibility assessment index of the target change task and the reasons for the change of the target change task in the construction project, and generate the final feasibility assessment index of the target change task.

[0058] The management unit is used to manage target change tasks in construction projects based on the feasibility assessment index of the final change of target tasks.

[0059] This invention provides an intelligent construction management system and method based on data analysis, which has the following advantages compared with the prior art:

[0060] This invention effectively solves the technical problems of traditional construction change management, which relies on subjective experience and lacks systematic quantitative assessment and dynamic impact analysis, by quantitatively analyzing the cost loss of changed tasks, dynamically tracking the actual impact relationship between tasks, and making necessary corrections based on the reasons for changes. It has the advantages of providing an objective and quantitative change feasibility assessment mechanism, realizing dynamic impact analysis of construction task changes, and integrating change necessity and feasibility assessment to improve the scientific nature of decision-making, thereby optimizing the allocation of construction resources and the accuracy of schedule control. Attached Figure Description

[0061] Figure 1 This is a flowchart illustrating an intelligent construction management method based on data analysis provided by the present invention.

[0062] Figure 2 This is a flowchart illustrating step S50 of the present invention.

[0063] Figure 3 This is a flowchart illustrating step S60 of the present invention.

[0064] Figure 4 This is a schematic diagram of the structure of an intelligent construction management system based on data analysis provided by the present invention. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0066] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0067] Please see Figure 1 The present invention provides an intelligent construction management method based on data analysis, comprising the following steps:

[0068] Step S10: Obtain the original planned feature data and the estimated change feature data of the target change task in the construction project;

[0069] Step S20: Generate the basic change cost assessment index for the target change task based on the original planned characteristic data and the change estimated characteristic data of the target change task in the construction project;

[0070] Step S30: Establish a task relationship network among all tasks in the construction project; the task relationship network includes, but is not limited to, physical space dependencies and process sequence dependencies;

[0071] Step S40: Based on the task relationship network, obtain the number of tasks affected by the target change task among the completed tasks of the construction project;

[0072] Step S50: Based on the number of tasks affected by the actual impact of the target change task in the completed tasks of the construction project and the target change task basic change cost assessment index, establish a target change task change feasibility analysis model and generate a target change task change feasibility assessment index.

[0073] Step S60: Obtain the reasons for the change of the target change task in the construction project, establish a necessity correction model based on the feasibility assessment index of the target change task and the reasons for the change of the target change task in the construction project, and generate the final feasibility assessment index of the target change task.

[0074] Step S70: Based on the feasibility assessment index of the final change of the target change task, manage the target change task in the construction project; the management methods include whether to terminate the task change or change the content of the change.

[0075] Among them, the change estimate data refers to the total consumption characteristic value after the task is changed. The total consumption characteristic value is the sum of the characteristic value consumed before the target task change and the characteristic value planned to be consumed after the change. Specifically, the construction progress can be automatically tracked and the remaining construction period can be dynamically updated by project management software, or it can be estimated by manual input combined with on-site measurement data. For example, the material consumption can be determined based on the actual time recorded in the construction log and the engineer's experience. Its main purpose is to provide dynamically changing benchmark data to support subsequent cost quantification analysis.

[0076] The task relationship network refers to the topological structure that describes the interdependencies between construction tasks. Physical spatial dependencies can be extracted using Building Information Modeling (BIM) to determine the spatial location associations between components, while process sequence dependencies are analyzed through construction process flowcharts to determine the logical sequence of tasks. For example, the Task Breakdown Structure (WBS) can be used to map the process connection between concrete pouring and rebar tying. Its main purpose is to build a dynamic network between tasks to achieve real-time updates of the scope of influence.

[0077] Actual impact refers to the substantial changes that the change of the target task causes to the completed task. Specifically, the impact status can be determined by checking the acceptance documents and quality reports of the completed task. For example, if the dimensions of the completed wall need to be reworked due to the design change, it is considered an actual impact. Tasks that have not been implemented are not included in the assessment scope. The main purpose is to ensure that the impact analysis focuses on the actual chain reaction.

[0078] The generation of the target change task basic change cost assessment index can be quantified by using multi-attribute decision-making methods. For example, the weights of cost dimensions such as schedule and materials can be determined by the Analytic Hierarchy Process (AHP) and then weighted and summed. Alternatively, normalized cost loss values ​​can be generated based on comparisons of similar cases in a historical project database. The main purpose is to achieve a comprehensive quantitative expression of multi-dimensional costs.

[0079] The feasibility assessment index for changes in objectives and tasks is designed to couple direct costs and indirect impacts to form a basis for feasibility judgment.

[0080] The acquisition of reasons for changes and the construction of a necessity adjustment model can be achieved using a classification coding system. For example, reasons such as safety requirements and regulatory changes can be mapped to preset levels and combined with expert scoring to determine necessity coefficients. Alternatively, key reason tags can be extracted from change request documents using text analysis technology. The main purpose is to quantify external mandatory requirements and integrate them into the decision-making process. As a preferred implementation method, management operations include triggering automated decision-making processes based on the final feasibility assessment index. For example, when the index falls below a threshold, the system automatically generates a task termination suggestion, or prompts project managers to adjust the change content through a visual interface. The main purpose is to transform quantitative assessments into concrete action plans.

[0081] Therefore, this application achieves refined management of construction task changes by systematically integrating change cost quantification, dynamic impact analysis, and necessity decision-making. It solves the problems of single evaluation dimensions, static analysis process, and insufficient decision-making basis in traditional methods. Specifically, the dynamic construction of the task relationship network ensures that the scope of impact is updated in real time as the project progresses, the limitation mechanism of actual impact improves the accuracy of the evaluation, and the introduction of the necessity correction model enables decision-making to balance technical feasibility and external mandatory requirements, thereby effectively reducing the risk of resource waste and schedule delays.

[0082] In the construction project management process, when a target task change occurs, step S10 is executed to obtain the original planned characteristic data and the estimated change characteristic data for the task. The original planned characteristic data includes parameters such as the original task duration and the original planned material consumption, while the estimated change data reflects the status after the task change; for example, the original task duration after the change is determined as the sum of the consumed time and the construction time required after the task change. Further, in step S20, a target change task basic change cost assessment index is generated. This index, based on the original planned characteristic data and the estimated change characteristic data, is used to quantify the multi-dimensional cost losses caused by the change. Therefore, step S30 is executed to establish a task relationship network among all tasks in the construction project. This network encompasses physical space dependencies and process sequence dependencies to describe the logical connections between tasks. Based on this task relationship network, in step S40, the number of tasks in the completed tasks of the construction project that are actually affected by the target change task is obtained. The actual impact only applies to completed tasks; unimplemented tasks are not included in the impact scope. Subsequently, in step S50, a feasibility analysis model for the target change task is established. This model generates a feasibility assessment index for the target change task based on the number of affected tasks and the basic change cost assessment index of the target change task. Simultaneously, in step S60, the reasons for the target change task are obtained and combined with the feasibility assessment index to establish a necessity correction model, generating a final feasibility assessment index for the target change task. Finally, in step S70, based on the final feasibility assessment index, the target change task is managed, including whether to terminate the task change or modify the changed content.

[0083] For example, in a high-rise office building construction project, when the core tube structure design is changed, step S10 is executed to obtain the original planned characteristic data (original task duration of 90 days, original planned material consumption of 1200 tons) and the change estimate characteristic data (40 days of consumed time, 60 days of construction time required after the task change, total duration of 100 days; estimated material consumption of 1350 tons). In step S30, a task relationship network is established, identifying a process sequence dependency between core tube construction and foundation engineering, and that the foundation engineering task has been completed. Based on the task relationship network, in step S40, the foundation engineering task is identified as the task actually affected. In step S20, a target change task basic change cost assessment index is generated, reflecting the cost losses due to extended construction period and increased materials. In step S50, a target change task change feasibility assessment index is calculated. In step S60, the reason for the change is identified as an update to the seismic code, and a necessity correction model is applied to generate the final change feasibility assessment index. In step S70, based on the index, the system suggests changes to the content of the changes in order to reduce the impact on the completed basic engineering.

[0084] This method, through the coordinated operation of the above steps, effectively solves the problem of lacking systematic quantitative assessment in construction task change management. Specifically, step S10 dynamically acquires change forecast data, avoiding assessment biases caused by relying solely on static planned values; step S30 establishes a task relationship network, enabling impact analysis to be updated in real time as the project progresses, overcoming the shortcomings of static analysis in adapting to changes in actual construction conditions; step S40 limits the actual impact to completed tasks, ensuring that the impact scope assessment focuses on real chain reactions, improving the accuracy and timeliness of the analysis; step S50 couples cost losses with the chain effects between tasks, reflecting both direct costs and indirect rework costs, compensating for the shortcomings of existing technologies that ignore the chain effects of completed tasks; step S60 quantifies the reasons for changes and incorporates them into the correction model, enabling the final assessment index to balance technical feasibility and external mandatory requirements, preventing decisions from deviating from actual project needs. Thus, the management of construction task changes is transformed into a data-driven, refined, and intelligent process, significantly reducing resource waste and the risk of schedule delays.

[0085] Specifically, in some of the embodiments described above in this application, a target change task-based change cost assessment index is proposed to quantify change costs. However, in its implementation, there is a lack of comprehensive normalization assessment of multiple cost factors, which makes it impossible to uniformly handle the differences in units and magnitudes of different cost dimensions, resulting in inaccurate assessment results and affecting the accuracy of subsequent feasibility analysis.

[0086] In response, this invention further proposes a method for generating the basic change cost assessment index for the target change task, specifically including:

[0087] Based on the original planned characteristic data and the estimated change characteristic data of the target change task in the construction project, analyze all types of cost losses during the change of the target change task, and generate a basic change cost assessment index for the target change task; specifically:

[0088] Through the formula:

[0089] ;

[0090] Generate a target change task base change cost assessment index ;

[0091] In the formula, This represents the normalized value of the cost of the i-th type of change. This represents the weighting coefficient of the i-th type of change cost, and n represents the number of types of change costs.

[0092] Among them, the normalized value of the i-th change cost refers to the conversion of the original cost data into a dimensionless, uniform scale quantitative indicator. It can be achieved by using a standardized method based on historical data statistics or a dynamic threshold normalization technique. The purpose is to eliminate unit differences in different cost dimensions such as project extension and material waste, and to ensure the comparability of multi-dimensional costs.

[0093] The weighting coefficient of the i-th type of change cost can be understood as an adjustment parameter reflecting the relative importance of each cost factor. It can be determined by the analytic hierarchy process or an expert scoring system based on project management experience. The purpose is to dynamically adjust the contribution of each cost according to the priority of the construction project and avoid ignoring key factors.

[0094] The number of types of change costs refers to the total number of cost types included in the assessment system, including but not limited to construction period and material loss. These can be dynamically expanded or reduced according to the characteristics of the construction project in order to ensure the completeness of the assessment scope and prevent assessment deviations due to missing cost dimensions.

[0095] Specifically, the proposed solution first systematically quantifies all types of cost losses during changes based on the original planned characteristic data and estimated change characteristic data of the target change task in the construction project. Then, it converts various cost losses into normalized values ​​to eliminate dimensional differences and incorporates weighting coefficients to reflect the importance of each cost. Finally, it integrates all normalized values ​​through a weighted summation mechanism to generate a comprehensive change task-based change cost assessment index. This process ensures that cost assessment shifts from a single dimension to multi-dimensional collaborative quantification, allowing for unified handling of costs that cannot be directly compared, such as schedule and materials, thus providing an accurate input basis for subsequent feasibility analysis.

[0096] The above technical solution enables a comprehensive and normalized assessment of multiple cost factors, effectively unifying the differences in units and magnitudes across different cost dimensions, improving the accuracy of change cost assessment, and thus providing a reliable basis for subsequent feasibility analysis of change tasks.

[0097] In some of the embodiments described above in this application, a change cost assessment index based on change task is proposed to comprehensively quantify change costs. However, in its implementation, there is a lack of specific methods for generating the normalized value of the i-th change cost, which leads to inconsistent normalization processing of different cost factors (such as project duration and material consumption), making it impossible to accurately reflect the relative degree of cost change. This results in the assessment results being affected by subjective factors, making it difficult to achieve objective and comparable comprehensive cost analysis.

[0098] In response, this invention further proposes a method for generating the normalized value of the i-th type of change cost, specifically including:

[0099] By analyzing the original planned feature data and the estimated change feature data of the target change task in the construction project, the change cost of each feature of the target change task is analyzed when the change occurs, and a normalized value of the i-th change cost is generated; specifically:

[0100] Through the formula:

[0101] ;

[0102] Generate the normalized value of the i-th change cost. ;

[0103] In the formula, This represents the i-th originally planned feature data. This represents the i-th change prediction feature data corresponding to the i-th original planned feature data. This represents the feature loss threshold of the i-th feature of the target change task;

[0104] in ,like The normalized value of the i-th change cost The value of is 0;

[0105] Among them, the normalized value of the i-th type of change cost refers to the standardized measure of change cost change. It can be achieved by using the ratio of the difference in actual characteristic data to the characteristic loss threshold. The purpose is to unify cost factors of different dimensions such as project extension and material overconsumption into dimensionless relative change indicators to ensure the comparability of multi-dimensional costs in comprehensive evaluation.

[0106] The i-th original plan feature data can be understood as the feature benchmark value of the plan before the change. It can be realized by using historical data such as the construction period and material consumption recorded in the construction task plan document. The purpose is to provide a cost reference benchmark before the change.

[0107] The i-th change prediction feature data refers to the predicted feature value after the change, which aims to dynamically reflect the actual state after the change.

[0108] The feature loss threshold can be understood as the maximum reasonable loss range allowed for the i-th feature. It can be set using industry standards, historical project statistical extreme values, or expert experience. The purpose is to define the reasonable boundary of cost changes and avoid excessive interference from small fluctuations in the evaluation results.

[0109] Specifically, the proposed solution generates a normalized value by dividing the difference between the original planned characteristic data and the estimated change characteristic data by a characteristic loss threshold. This normalizes the changes in different cost factors to a relative scale. When the estimated change characteristic data is greater than or equal to the original planned characteristic data, the normalized value reflects the relative degree of cost increase; when the estimated change characteristic data is less than the original planned characteristic data, the normalized value is set to zero to avoid negative values ​​interfering with the calculation of the comprehensive evaluation index. This mechanism ensures that the quantitative assessment of cost changes is strictly based on actual project data, eliminating the assessment bias caused by subjective experience in traditional methods. Furthermore, by introducing a characteristic loss threshold, cost changes are constrained within a reasonable range, preventing minor fluctuations from being excessively amplified or ignored, thereby achieving an objective and stable comparison of multi-dimensional cost factors.

[0110] Through the above scheme, this application achieves an objective quantitative assessment of change costs, ensures the comparability of different cost factors in the comprehensive index, effectively avoids the influence of subjective factors on the assessment results, and provides a scientific basis for decision-making on construction task changes.

[0111] In some of the embodiments described above in this application, a feasibility analysis model for changing tasks is proposed to assess the feasibility of the change. However, in its implementation, the model lacks a specific quantification method for the number of affected tasks, fails to consider the weight differences and impact depth of the tasks, and relies solely on simple counting, resulting in an overly coarse feasibility assessment that cannot accurately reflect the actual degree of interference of the change on completed tasks. It may cause decision-making bias due to ignoring the high impact weight of key tasks.

[0112] For this, please refer to Figure 2 The present invention further proposes a method for generating the feasibility assessment index for the target change task, specifically including:

[0113] Step S51: Generate the target change task impact index based on the number of tasks actually affected by the target change task among the completed tasks of the construction project;

[0114] Step S52: Establish a feasibility analysis model for the target change task based on the target change task basic change cost assessment index and the target change task impact index, and generate the target change task feasibility assessment index;

[0115] Among them, the change task impact index refers to the technical feature of transforming the discrete number of affected tasks into a continuous quantitative indicator. It can be achieved by summing the product of the task weight coefficient and the degree of impact. For example, it can be calculated by weighting the priority and interference degree of each affected task. Its purpose is to capture the heterogeneity between tasks and avoid the evaluation distortion caused by simple counting.

[0116] The feasibility analysis model for task change can be understood as an evaluation framework that integrates direct costs and cascading effects. Its purpose is to dynamically couple the direct economic losses and indirect ripple effects of the change, thereby providing a multi-dimensional feasibility assessment.

[0117] Specifically, the solution of this application first systematically transforms the number of tasks actually affected by the completed tasks of the construction project into a change task impact index through step S51. This transformation process takes into account the weight differences and impact depth of the tasks, so that the index can reflect the amplification effect when high-priority tasks are disturbed. Subsequently, in step S52, the impact index is dynamically coupled with the change task basic change cost assessment index to form a change task change feasibility analysis model. The basic change cost assessment index quantifies the resource consumption of the change itself, while the impact index supplements the chain interference on the completed task network. The combination of the two ensures that the feasibility assessment index can simultaneously weigh direct costs and indirect reactions, thereby outputting accurate assessment results.

[0118] Through the above technical solutions, the feasibility assessment of task changes can more accurately quantify the actual degree of interference of changes on completed tasks, effectively avoid the assessment distortion caused by ignoring the differences in task weights, and thus improve the scientificity and reliability of construction management decisions.

[0119] In some of the embodiments described above in this application, a change task impact index is proposed to quantify the chain effect of construction task changes on completed tasks. However, in its implementation, the generation of the impact index lacks a specific quantitative method, making it difficult to accurately assess the actual impact on the affected tasks. This results in the output of the change feasibility analysis model being inaccurate and may lead to decision-making errors.

[0120] In response, this invention further proposes a method for generating the target change task impact index, specifically including:

[0121] By quantifying the degree of impact of the number of affected tasks in a construction project that are actually affected by the change in objectives, an impact index for the change in objectives is generated; specifically:

[0122] Through the formula:

[0123] ;

[0124] Generate target change task impact index ;

[0125] In the formula, This indicates the number of tasks affected. This indicates the number of tasks that have been completed in the construction project. This represents the set of affected tasks. This represents the j-th affected task. This represents the weight coefficient of the j-th affected task. This represents the percentage of the impact on the j-th affected task;

[0126] Among them, the number of affected tasks refers to the total number of tasks in the construction project that have been completed but are actually affected by the target change. It can be determined by the depth-first traversal algorithm of the task relationship network, with the aim of dynamically reflecting the actual scope of the change's impact.

[0127] The number of completed tasks refers to the total number of tasks that have been completed in a construction project. It can be obtained through the status markers of the project schedule management system, with the aim of providing a benchmark for impact assessment. The set of affected tasks refers to the set of all completed tasks that are actually affected by the change in objectives. It can use a graph structure to store the node relationships, with the aim of systematically organizing the information on affected tasks.

[0128] The jth affected task refers to any unit in the set of affected tasks, which can correspond to a specific construction procedure, and is intended to serve as the basic calculation object for impact quantification.

[0129] Weighting coefficient This refers to a value that characterizes the criticality of the j-th affected task. It can be set according to the task's location on the critical path or the level of security risk, with the aim of distinguishing the decisive impact of different tasks on the overall progress.

[0130] The degree of impact refers to the extent to which the j-th affected task is substantially affected by the change. It can be calculated based on the proportion of rework or the proportion of resource reallocation. The purpose is to quantify the depth of the impact on the task rather than just to determine whether it is affected.

[0131] The proposed solution normalizes the weighted impact depth of affected tasks by using the ratio of the number of affected tasks to the number of completed tasks as a proportional factor, thereby eliminating the impact assessment bias caused by differences in project scale. At the same time, it differentiates the weighting of each affected task by multiplying the weight coefficient with the proportion of the degree of impact, so that the impact index can comprehensively reflect the relative proportion of the scope of impact and the impact intensity of individual tasks, ultimately forming a quantitative indicator that takes into account both breadth and depth, providing accurate input for change feasibility analysis.

[0132] Through the above technical solutions, the change task impact index can dynamically adapt to changes in project scale, avoiding excessive amplification or dilution of the impact due to differences in project size. At the same time, by finely weighting the criticality of the task and the degree of impact, it can accurately capture the substantial changes in the chain of impacts, thereby improving the accuracy of change feasibility assessment and reducing the risk of decision-making errors caused by assessment bias.

[0133] In some of the embodiments described above in this application, a feasibility analysis model for changing tasks is proposed to generate a feasibility assessment index for changing tasks. However, in its implementation, the model lacks a specific mathematical expression definition, which makes it impossible to accurately quantify the comprehensive influence relationship between the basic change cost assessment index and the change task impact index. Furthermore, an abnormal situation where the denominator is zero may occur during the calculation, making the feasibility assessment results unstable and difficult to support scientific decision-making for changes in construction tasks.

[0134] In response, this invention further proposes the following expression for the feasibility analysis model of the target change and task change:

[0135] ;

[0136] In the expression, This represents the feasibility assessment index for changes in objectives and tasks. This represents the cost assessment index for the basic change of the target task. This represents the impact index of the task on the change of objectives. For adjustment coefficients, For constant terms;

[0137] Among them, the change of task feasibility assessment index is a comprehensive indicator used to quantify the overall feasibility of task changes. It can be realized by numerical calculation and aims to provide a quantifiable scientific basis for construction management decisions.

[0138] The adjustment coefficient is a parameter used to dynamically adjust the sensitivity of the basic change cost assessment index to the impact index. It can be determined by empirical setting based on historical project data or by optimization algorithm, with the aim of making the model adapt to the dynamic characteristics of different construction projects.

[0139] The constant term refers to a tiny positive value, which can be achieved by setting a fixed threshold. The purpose is to ensure that the denominator is not zero and to guarantee the numerical stability of the calculation process.

[0140] The proposed solution combines the basic change cost assessment index and the change impact index of the task in a non-linear manner to form a comprehensive assessment item. This combined term effectively integrates the coupling effect of cost factors and cascading impact factors. Subsequently, the comprehensive evaluation term is converted into a change task feasibility assessment index through reciprocal calculation, ensuring that the index value monotonically decreases with increasing cost and impact, thus intuitively reflecting the feasibility level. The introduction of a constant term ensures that the denominator is always greater than zero, avoiding the risk of calculation anomalies. This design enables dynamic quantitative assessment of change feasibility, allowing the model to adjust the assessment results according to the progress of the construction project, providing a stable and reliable basis for decision-making.

[0141] The above technical solution enables the accurate quantification and stable calculation of the feasibility assessment index for changing tasks, effectively avoiding numerical anomalies caused by a zero denominator, ensuring the reliability of the assessment results in the dynamic environment of the construction project, and thus providing solid technical support for scientific decision-making on changes to construction tasks.

[0142] Specifically, in some of the embodiments described above in this application, a method for generating the feasibility assessment index of the final change of the change task is proposed. However, in its implementation process, the quantitative processing of the reasons for the change is insufficient, and the mandatory degree of different reasons is not systematically incorporated into the model, which may cause the assessment results to ignore key factors and affect the scientific nature of management decisions.

[0143] For this, please refer to Figure 3 The present invention further proposes a method for generating the feasibility assessment index of the final change of the target change task, specifically including:

[0144] Step S61: Generate the change necessity coefficient of the target change task based on the reasons for the change of the target change task in the construction project;

[0145] Step S62: Establish a necessity correction model based on the change necessity coefficient and change feasibility assessment index of the target change task, and generate the final change feasibility assessment index of the target change task;

[0146] The change necessity coefficient refers to converting diverse reasons for change into quantifiable numerical indicators. It can be achieved using an expert scoring system or a statistical model based on historical data. Its purpose is to objectively assess the degree of mandatory nature of different reasons and avoid the subjectivity of traditional experience-based judgment.

[0147] The necessity correction model can be understood as a mathematical relationship between the change necessity coefficient and the change task feasibility assessment index. It can be implemented by multiplication or weighted average function. The purpose is to dynamically adjust the final assessment index through the necessity coefficient to ensure that the high necessity reasons get reasonable weight in the decision-making, thereby solving the problem of the disconnect between the change reasons and the feasibility assessment.

[0148] Specifically, the solution of this application first quantifies the reasons for the change of the target change task in the construction project in step S61 to generate a change necessity coefficient. This coefficient reflects the degree of mandatory nature of different reasons such as safety requirements and regulatory changes. Then, in step S62, a necessity correction model is established using this coefficient and the change task change feasibility assessment index to generate the final change task change feasibility assessment index. This organically combines the necessity and feasibility of the change, so that mandatory changes can dynamically affect the final assessment result according to their importance, avoiding the one-sided assessment problem caused by the isolated analysis of change reasons in the prior art.

[0149] Through the above scheme, this application systematically incorporates the degree of mandatory nature of the reasons for change into the evaluation model, avoids the neglect of key factors, and improves the scientificity and adaptability of construction task change management decisions.

[0150] In some of the embodiments described above in this application, a change necessity coefficient is proposed to integrate the reasons for change with the feasibility assessment. However, in its implementation, the generation of the change necessity coefficient relies on subjective experience judgment and lacks a quantitative assessment mechanism for various necessary reasons (such as safety requirements, regulatory changes, etc.). It is impossible to accurately distinguish the differences in the degree of mandatory nature of different reasons, which leads to the distortion of the input of the necessity correction model and ultimately affects the scientific nature of change decision-making and the optimal allocation of resources.

[0151] In response, this invention further proposes a method for generating the necessity coefficient of the target change task, specifically including:

[0152] Through the formula:

[0153] ;

[0154] Generate the change necessity coefficient for the target change task. ;

[0155] In the formula, This represents the flag value for the kth necessary reason for the objective change task. This represents the weight coefficient of the kth necessary reason, and q represents the number of necessary reasons.

[0156] Among them, the change necessity coefficient is a quantitative indicator used to comprehensively characterize the necessity of the target change task. It can be generated by a weighted summation algorithm. Its purpose is to transform qualitative change reasons into calculable values, thereby supporting the objective input of the necessity correction model.

[0157] The kth type of necessity reason flag value refers to a quantitative identifier that indicates the existence status of a specific necessity reason. It can use binary flag values ​​or hierarchical scoring values ​​to quantify the reasons for changes in the target task in the construction project. The purpose is to transform qualitative reasons such as safety requirements and regulatory changes into calculable inputs and avoid the ambiguity of human experience.

[0158] The weight coefficient of the kth necessity reason refers to the preset parameter that reflects the importance level of different necessity reasons. It can be implemented by using a constant preset based on expert experience or a dynamically adjusted coefficient. The purpose is to highlight the decision influence of key reasons through weight differences and ensure that reasons with a high degree of mandatory force dominate the calculation.

[0159] The number of necessary causes, q, refers to the total number of necessary causes included in the assessment. It can be configured as a fixed value or an expandable value, with the aim of adapting the model to different project needs and flexibly handling the addition or deletion of cause types.

[0160] Specifically, the solution in this application identifies various necessary reasons for the target change task through a system, assigns a flag value to each reason, then calculates a weighted average of the flag values ​​according to preset weight coefficients, and finally generates a change necessity coefficient by summing all weighted values. This coefficient serves as the core input of the necessity correction model and works in conjunction with the change task feasibility assessment index to achieve a dynamic integrated analysis of change reasons and feasibility. Because the generation process of the change necessity coefficient is strictly based on quantified flag values ​​and preset weights, it ensures that reasons with a high degree of mandatory force dominate the decision-making process, avoiding decision-making bias caused by isolated evaluation of the change itself.

[0161] Through the above technical solution, the generation of change necessity coefficient realizes an objective quantitative assessment of various necessity reasons, effectively distinguishes the differences in the degree of mandatoryness of different reasons, avoids the input distortion problem caused by subjective experience judgment, and thus improves the scientific nature of change decision-making and the efficiency of resource optimization and allocation.

[0162] In some of the embodiments described above in this application, a necessity correction model is proposed to generate a final change feasibility assessment index for a change task. However, in its implementation, due to the lack of specific mathematical expressions, the correction model may rely too much on empirical judgment and cannot objectively and quantitatively reflect the impact of change necessity on feasibility, resulting in inaccurate assessment results and easily causing resource waste or decision-making errors.

[0163] In response, this invention further proposes the following expression for the necessity correction model:

[0164] ;

[0165] In the expression, This represents the feasibility assessment index for the final change of the target task. This represents the necessity coefficient for changing the target task. This represents the feasibility assessment index for changes in objectives and tasks;

[0166] Among them, the final change feasibility assessment index is a quantitative indicator used to comprehensively assess the final feasibility of changes to construction tasks. It can be achieved by multiplying the change necessity coefficient and the change feasibility assessment index. The purpose is to provide a unified basis for decision-making and facilitate subsequent management steps.

[0167] The change necessity coefficient of the target change task refers to the coefficient that quantifies the degree of mandatory nature of the change cause. It can be calculated based on the weight of the change cause. For example, by multiplying different cause indicator values ​​with their corresponding weight coefficients and then summing them, the purpose is to reflect the driving strength of different causes on the change.

[0168] The Feasibility Assessment Index for Task Change refers to a basic feasibility indicator that integrates the basic change costs and task impacts. It can be calculated based on the Basic Change Cost Assessment Index and the Change Task Impact Index, with the aim of providing an objective assessment of the feasibility of the change.

[0169] Specifically, the proposed solution achieves a precise quantitative assessment of the final feasibility of a change task by multiplying a change necessity coefficient by a change feasibility assessment index. The change necessity coefficient is dynamically adjusted based on the weight of the change reason; when the change reason is highly mandatory (such as safety requirements or regulatory changes), the coefficient value is larger. The change feasibility assessment index integrates the basic change cost and the task impact index, reflecting the objective feasibility of the change. The product of these two factors ensures that the assessment of final feasibility considers both the objective constraints of the change and the weight of necessity, thus avoiding decision-making errors caused by solely relying on feasibility indicators. For example, when the change necessity is high, even if the feasibility assessment index is low, the final assessment index may still reach an acceptable level, prompting the system to reasonably adopt the change and preventing compliance risks or resource waste caused by ignoring necessity.

[0170] Through the above-mentioned approach, this application achieves an objective and quantitative assessment of changes in construction tasks, effectively avoiding the problem of relying on experience-based judgments in the modification model, ensuring that change decisions are based on data rather than subjective experience, thereby reducing the risk of resource waste and decision-making errors, and improving the scientific nature and efficiency of construction management.

[0171] Please see Figure 4 In another embodiment, the present invention also proposes an intelligent construction management system based on data analysis, which is used to execute the above-described intelligent construction management method based on data analysis, specifically including:

[0172] The construction project data acquisition unit 10 is used to acquire the original planned feature data and the estimated change feature data of the target change task in the construction project;

[0173] The preliminary analysis unit 20 is used to generate a basic change cost assessment index for the target change task based on the original planned characteristic data and the change estimated characteristic data of the target change task in the construction project.

[0174] The task relationship establishment unit 30 is used to establish a task relationship network among all tasks in the construction project; the task relationship network includes, but is not limited to, physical space dependencies, process sequence dependencies, etc.

[0175] The relationship network data acquisition unit 40 is used to obtain the number of tasks affected by the actual impact of the target change task among the completed tasks of the construction project based on the task relationship network.

[0176] The comprehensive analysis unit 50 is used to establish a feasibility analysis model for target change tasks based on the number of affected tasks in the completed tasks of the construction project that are actually affected by the target change tasks and the basic change cost assessment index of the target change tasks, and to generate a feasibility assessment index for target change tasks.

[0177] The final analysis unit 60 is used to obtain the reasons for the change of the target change task in the construction project, establish a necessity correction model based on the feasibility assessment index of the target change task and the reasons for the change of the target change task in the construction project, and generate the final feasibility assessment index of the target change task.

[0178] Management unit 70 is used to manage target change tasks in construction projects based on the feasibility assessment index of the final change of target change tasks.

[0179] The present invention further proposes that the comprehensive analysis unit 50 specifically includes:

[0180] The impact index generation module is used to generate the impact index of the target change task based on the number of tasks that are actually affected by the target change task among the completed tasks of the construction project.

[0181] The feasibility assessment index generation module is used to establish a feasibility analysis model for target change tasks based on the target change task basic change cost assessment index and the target change task impact index, and generate a target change task feasibility assessment index.

[0182] The present invention further proposes that the comprehensive analysis unit 50 specifically includes:

[0183] The necessity analysis module is used to generate a necessity coefficient for changing the target task based on the reasons for the change in the target task in the construction project.

[0184] The correction module is used to establish a necessity correction model based on the change necessity coefficient and the change feasibility assessment index of the target change task, and generate the final change feasibility assessment index of the target change task.

[0185] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A data analysis-based intelligent construction management method, characterized in that, The method specifically comprises the following steps: Obtain the original plan feature data and the change estimation feature data of the target change task in the construction project; Generate a target change task basic change cost evaluation index according to the original plan feature data and the change estimation feature data of the target change task in the construction project; Establish a task relationship network among all tasks in the construction project; Obtain the number of affected tasks actually affected by the target change task in the completed tasks in the construction project based on the task relationship network; Establish a target change task change feasibility analysis model according to the number of affected tasks actually affected by the target change task in the completed tasks in the construction project and the target change task basic change cost evaluation index, and generate a target change task change feasibility evaluation index; Obtain the change reason of the target change task in the construction project, establish a necessity correction model according to the target change task change feasibility evaluation index and the change reason of the target change task in the construction project, and generate a target change task final change feasibility evaluation index; Manage the target change task in the construction project according to the target change task final change feasibility evaluation index; The generation mode of the target change task change feasibility evaluation index specifically comprises: Generate a target change task influence index according to the number of affected tasks actually affected by the target change task in the completed tasks in the construction project; Establish a target change task change feasibility analysis model according to the target change task basic change cost evaluation index and the target change task influence index, and generate a target change task change feasibility evaluation index; The generation mode of the target change task influence index specifically comprises: Quantify the influence degree of the number of affected tasks by the number of affected tasks actually affected by the target change task in the construction project, and generate a target change task influence index; specifically: Through the formula: ； Generating target change task impact indices ; In the formula, represents the number of affected tasks, represents the number of completed tasks of the construction project, represents the affected task set, represents the jth affected task, represents the weight coefficient of the jth affected task, the weight coefficient of the jth affected task is set according to the safety risk level of the task on the critical path, and the purpose is to distinguish the decisive influence of different tasks on the overall progress; represents the affected degree proportion of the jth affected task, the affected degree proportion of the jth affected task refers to the substantial degree of the jth affected task affected by the change, which is calculated based on the rework workload proportion, and the purpose is to quantify the depth of the affected task; The generation mode of the target change task basic change cost evaluation index specifically comprises: ； In the expression, represents a target change task change feasibility evaluation index, represents a target change task basis change cost evaluation index, represents a target change task influence index, is a regulation coefficient, is a constant term. 2.The data analysis based intelligent construction management method according to claim 1, characterized in that, Analyze all types of cost losses of the target change task when the target change task is changed according to the original plan feature data and the change estimation feature data of the target change task in the construction project, and generate a target change task basic change cost evaluation index; specifically: Through the formula: The generation mode of the normalized value of the i-th change cost specifically comprises: ； Generating target change task base change cost evaluation index ; In the formula, represents the normalized value of the i-th change cost, represents the weight coefficient of the i-th change cost, and n represents the number of change cost types. 3.The data analysis based intelligent construction management method of claim 2, wherein, Analyze the change cost of each feature of the target change task when the target change task is changed by the original plan feature data and the change estimation feature data of the target change task in the construction project, and generate a normalized value of the i-th change cost; specifically: Through the formula: The generation mode of the target change task final change feasibility evaluation index specifically comprises: ； generating a normalized value of the ith change cost ; In the formula, represents the i-th original planned feature data, represents the i-th change estimation feature data corresponding to the i-th original planned feature data, represents the feature loss threshold of the i-th feature of the target change task; wherein , if , the normalized value of the i-th change cost is 0. 4.The data analysis based intelligent construction management method of claim 1, wherein, Generate a change necessity coefficient of the target change task according to the change reason of the target change task in the construction project; Establish a necessity correction model according to the change necessity coefficient of the target change task and the target change task change feasibility evaluation index, and generate a target change task final change feasibility evaluation index. The generation mode of the change necessity coefficient of the target change task specifically comprises: 5.The data analysis based intelligent construction management method of claim 4, wherein, Through the formula: ​ ； Change necessity coefficient for generating a target change task ; In the formula, represents the kth necessary reason flag value of the target change task, represents the weight coefficient of the kth necessary reason, and q represents the number of types of necessary reasons. 6.The data analysis based intelligent construction management method according to claim 4, characterized in that, The expression of the necessity correction model is specifically: ； In the expression, represents the final change feasibility evaluation index of the target change task, represents the change necessity coefficient of the target change task, represents the change feasibility evaluation index of the target change task.

7. An intelligent construction management system based on data analysis, characterized by, The system is used for executing the intelligent construction management method based on data analysis in any one of claims 1-6, and specifically comprises: A construction project data acquisition unit is configured to acquire original plan feature data and change estimation feature data of a target change task in a construction project; A preliminary analysis unit is configured to generate a target change task basic change cost evaluation index according to the original plan feature data and the change estimation feature data of the target change task in the construction project; A relationship network establishment unit is configured to establish a task relationship network among all tasks in the construction project; A relationship network data acquisition unit is configured to acquire the number of affected tasks actually affected by the target change task among completed tasks in the construction project based on the task relationship network; A comprehensive analysis unit is configured to establish a target change task change feasibility analysis model according to the number of affected tasks actually affected by the target change task among the completed tasks in the construction project and the target change task basic change cost evaluation index, and generate a target change task change feasibility evaluation index; A final analysis unit is configured to acquire a change reason of the target change task in the construction project, establish a necessity correction model according to the target change task change feasibility evaluation index and the change reason of the target change task in the construction project, and generate a final target change task change feasibility evaluation index; A management unit is configured to manage the target change task in the construction project according to the final target change task change feasibility evaluation index.

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