Cloud-computing-based project cost management method and system
Patent Information
- Application Number
- CN202411859424.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-17
- Publication Date
- 2026-10-30
AI Technical Summary
[0004]针对现有技术的不足，本发明提供了基于云计算的工程造价管理方法及系统，解决了传统方式耗费时间长，效率低下的问题
[0046]本发明提供了基于云计算的工程造价管理方法及系统，本发明系统集成了用户管理、项目管理、成本管理、合同管理、供应链管理和风险管理多个模块，从项目初期到完成的全过程实现有效的监控和管理，特别是通过协同管理模块加强项目团队间的沟通与合作，保证了信息的及时共享和任务的有效分配，从多个维度提升了工程项目的管理效率和质量，在成本管理模块中利用机器学习技术线性回归模型进行成本估算，结合项目参数和历史数据提供更为准确的成本预测，采用K近邻算法或支持向量机自动归类成本开支，简化了成本记录与分类的过程，提高了工作效率，通过成本偏差分析和成本超支分析，系统能够及时发现成本异常，为项目成本控制提供科学依据，系统不仅实现了数据的收集、存储与归档，而且通过数据可视化模块将复杂的数据以直观的图表和报告形式展现给用户，帮助管理者快速理解项目成本、进度和风险状况，从而作出更加明智的决策，此外，成本分析与报告功能可以根据不同的用户需求生成定制化的报告，满足不同层面的管理需求，同时利用工作流引擎，成本审批流程被高度自动化，简化了审批手续，加快了审批速度，同时也确保了项目的透明度和规范性，每一步审批操作都会通过多种通知方式及时告知相关人员，提高了工作效率与沟通效率，通过协同管理模块支持任务分配、即时通讯、文件共享和会议管理，为项目团队提供了一个高效协作的平台，通过该模块，团队成员之间的交流更加便捷，项目文件的管理更加有序，有助于提高团队协作效率，加快项目进度，风险管理模块能够自动识别、评估项目中可能遇到的风险，并生成应对策略，同时系统还能够基于供应商的报价、质量和交付能力等信息对供应链进行高效管理，及时发现并解决潜在问题，这一功能对于预防和降低项目风险具有重要意义，本发明的基于云计算的工程造价管理系统通过集成交互性强、智能化水平高的多个功能模块，不仅大幅提升了工程项目的管理效率，降低了管理成本，还能够有效预防和控制项目风险。
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Abstract
Description
Technical Field
[0001] This invention relates to the field of engineering cost technology, specifically to a cloud computing-based engineering cost management method and system. Background Technology
[0002] Construction cost management refers to a series of activities that predict, control, monitor, and optimize the investment costs of a construction project throughout its entire lifecycle, from planning to implementation and final delivery. The main objective is to ensure the project is completed within a predetermined budget while maximizing the efficiency of capital utilization. Construction cost management involves multiple aspects, including cost estimation, cost control, contract management, supply chain management, and risk management.
[0003] Most project cost management still relies on manual operations and traditional tools. This includes manually entering project cost data such as material costs, labor costs, and equipment rental fees using spreadsheet software like Excel; project managers manually estimating and analyzing costs using formulas and calculations to generate preliminary cost budgets; some projects still use paper records and document management, leading to inefficient data processing and analysis; contract management involves manual review and management of contracts, extracting key clauses and recording them, which is inefficient and prone to errors; supply chain management is mainly conducted through telephone, email, and face-to-face communication, requiring significant time and manpower; risk management typically relies on the experience and judgment of the project management team, managing and responding to risks through regular meetings and reports; communication and collaboration among project team members depend on traditional tools, lacking real-time and efficiency; and project reports and charts are usually created manually, which is time-consuming and difficult to update in a timely manner. Summary of the Invention
[0004] To address the shortcomings of existing technologies, this invention provides a cloud computing-based engineering cost management method and system, which solves the problems of long time consumption and low efficiency in traditional methods.
[0005] To achieve the above objectives, the present invention provides the following technical solution: a cloud-based engineering cost management system, comprising a user management module, wherein the user management module is connected to a project management module, the project management module is connected to a collaboration management module and a cost management module, the cost management module is connected to a contract management module, the contract management module is connected to a supply management module, the supply management module is connected to a risk management module, the collaboration management module is connected to a data visualization module, the data visualization module is connected to a training and support module, and the training and support module is connected to a feedback and optimization module;
[0006] The project management module and the collaboration management module are bidirectionally connected; the cost management module and the data visualization module are bidirectionally connected; the contract management module and the training and support module are bidirectionally connected; and the supply management module and the feedback and optimization module are bidirectionally connected.
[0007] Preferably, the cost management module is used for cost estimation, cost recording and classification, cost approval processes, and generating customized cost analysis reports, specifically:
[0008] Cost estimation:
[0009] Users input various project parameters, such as project scale, complexity, material requirements, and labor costs. The machine learning model uses linear regression to estimate costs based on historical data and input parameters. The basic formula is as follows:
[0010] Cost=β0+β1×Scale+β2×Complexity+β3×Material+β4×Labor
[0011] Where: Cost is the project cost, Complexity is the engineering complexity, Labor is the labor cost, and Material is the material cost;
[0012] Cost Records and Classification:
[0013] Predefined cost classification rules, such as design, construction, procurement, and labor, are used to record detailed information for each expense, including date, amount, category, and description, via API interface or manual input. Cost data is stored in a relational database, and a rule engine or machine learning classifier such as K-nearest neighbor algorithm or support vector machine is used to automatically classify expenses into the corresponding cost center. The specific steps are as follows:
[0014] Collect historical cost data, including detailed information and classification of each expense, normalize the data to ensure that each feature is on the same scale, select an appropriate K value, such as 5, train a K-nearest neighbor classifier using historical data, extract features from new records, and use the trained K-nearest neighbor classifier for classification prediction.
[0015] Cost approval process:
[0016] Predefined approval rules, such as approval levels for different amount ranges, are used to automate the approval process through workflow engines like Activiti or Flowable. Each step in the approval process is communicated to relevant personnel via email, SMS, or system notification.
[0017] Cost Analysis and Report:
[0018] Extract cost data from the database, process and analyze the data using data analysis tools such as Pandas or NumPy, and generate bar charts, pie charts, and trend charts using data visualization libraries such as Matplotlib or Plotly. Generate customized cost reports according to user needs.
[0019] Cost variance analysis:
[0020]
[0021] Where Cost Deviation is the percentage of cost deviation, Estimated Cost is the estimated cost, and Actual Cost is the actual cost;
[0022] Cost Overrun=Actual Cost-Budget
[0023] Cost Overrun is the amount of cost overrun, and Budget is the project budget.
[0024] Data processing
[0025] Remove irrelevant or missing data, handle outliers and isolated points, extract key features from the original data, such as project scale, complexity, material requirements and labor costs, and normalize the feature values to the same dimension using Z-score normalization or Min-Max normalization.
[0026] Machine learning model training
[0027] Historical cost data is divided into training and test sets. A linear regression model is selected, and the model is trained using the training set data. The parameters β0, β1, β2, β3, and β4 are optimized. Then, the performance of the model is evaluated using the test set data, such as mean squared error or coefficient of determination.
[0028] Preferably, the user management module is used for user registration, login, role definition, and permission management.
[0029] Preferably, the project management module is used for project creation, task allocation, progress tracking and file management, and provides a project template library; the contract management module is used for contract creation, clause extraction, execution monitoring and change management.
[0030] Preferably, the supply chain management module is used for supplier management, procurement management, inventory management and supplier evaluation, and the risk management module is used for risk identification, assessment, response strategy generation and real-time early warning.
[0031] Preferably, the data visualization module is used for visualizing costs, schedules, and risks, generating charts and reports; the collaborative management module is used for task allocation, instant messaging, file sharing, and meeting management; and the feedback and optimization module is used for collecting user feedback, tracking issues, and continuously improving the system.
[0032] The cloud-based engineering cost management method includes the following steps:
[0033] S1. Registration and Login
[0034] Users register and log in through the user management module, and the system assigns corresponding permissions based on user roles;
[0035] S2. Management Estimates
[0036] In the project management module, you can create and manage projects, including basic project information, phase division, task allocation, and document management. In the cost management module, you can perform cost estimation and generate preliminary cost estimates based on project parameters and historical data.
[0037] S3. Record Approval
[0038] Record and categorize every expense in the project, implement a cost approval process, conduct multi-level approvals and automatic workflows, and generate approval records;
[0039] S4. Report Generation
[0040] Generate customized cost analysis reports, including cost deviation analysis and trend forecasting; create, sign, store and manage contracts through the contract management module; extract key clauses from contracts and generate contract summaries.
[0041] S5. Risk Assessment
[0042] By managing supplier information, procurement tasks, and inventory status in the supply chain, the system automatically assesses supplier quotations, quality, and delivery capabilities, identifies potential project risks, evaluates the impact of these risks and corresponding response strategies, and provides real-time early warning notifications.
[0043] S6. Visualizing Data
[0044] The data visualization module generates visual charts and reports on costs, schedules, and risks, helping users intuitively understand the project status. The collaboration management module assigns tasks, facilitates communication and collaboration, sets up file sharing and meeting management, and collects user feedback and tracks the progress of issue resolution through the feedback and optimization module.
[0045] This invention provides a cloud computing-based method and system for engineering cost management. It offers the following advantages:
[0046] This invention provides a cloud-based engineering cost management method and system. The system integrates multiple modules including user management, project management, cost management, contract management, supply chain management, and risk management. It achieves effective monitoring and management throughout the entire project lifecycle, from initial planning to completion. In particular, the collaborative management module strengthens communication and cooperation among project teams, ensuring timely information sharing and effective task allocation. This improves project management efficiency and quality from multiple dimensions. The cost management module utilizes machine learning techniques, such as linear regression models, for cost estimation. Combined with project parameters and historical data, it provides more accurate cost predictions. The K-nearest neighbor algorithm or support vector machine is used to automatically classify cost expenditures, simplifying cost recording and classification and improving efficiency. Through cost deviation analysis and cost overrun analysis, the system can promptly detect cost anomalies, providing a scientific basis for project cost control. The system not only collects, stores, and archives data but also uses a data visualization module to present complex data to users in intuitive charts and reports, helping managers quickly understand project costs, schedules, and risks, thus enabling more informed decision-making. Furthermore, the cost analysis and reporting functions can be customized for different users. The system generates customized reports to meet management needs at different levels. Utilizing a workflow engine, the cost approval process is highly automated, simplifying procedures, accelerating approval speed, and ensuring project transparency and standardization. Each approval step is promptly communicated to relevant personnel through multiple notification methods, improving work and communication efficiency. The collaborative management module supports task allocation, instant messaging, file sharing, and meeting management, providing a highly efficient collaboration platform for project teams. This module facilitates communication among team members and organizes project documents more systematically, contributing to improved teamwork efficiency and faster project progress. The risk management module automatically identifies and assesses potential project risks and generates response strategies. Furthermore, the system efficiently manages the supply chain based on supplier quotations, quality, and delivery capabilities, promptly identifying and resolving potential problems. This functionality is crucial for preventing and mitigating project risks. This cloud-based engineering cost management system, by integrating multiple highly interactive and intelligent functional modules, not only significantly improves project management efficiency and reduces management costs but also effectively prevents and controls project risks. Attached Figure Description
[0047] Figure 1 This is a schematic diagram of the system flow of the present invention. Detailed Implementation
[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0049] like Figure 1 As shown, this embodiment of the invention provides a cloud-based engineering cost management system, including a user management module, a project management module connected to the user management module, a collaboration management module and a cost management module connected to the project management module, a contract management module connected to the contract management module, a supply management module connected to the supply management module, a risk management module connected to the collaboration management module, a data visualization module connected to the data visualization module, a training and support module connected to the training and support module, and a feedback and optimization module.
[0050] The project management module is bidirectionally connected to the collaboration management module, the cost management module is bidirectionally connected to the data visualization module, the contract management module is bidirectionally connected to the training and support module, and the supply management module is bidirectionally connected to the feedback and optimization module.
[0051] The cost management module is used for cost estimation, cost recording and classification, cost approval processes, and generating customized cost analysis reports, specifically:
[0052] Cost estimation:
[0053] Users input various project parameters, such as project scale, complexity, material requirements, and labor costs. The machine learning model uses linear regression to estimate costs based on historical data and input parameters. The basic formula is as follows:
[0054] Cost=β0+β1×Scale+β2×Complexity+β3×Material+β4×Labor
[0055] Where: Cost is the project cost, Complexity is the engineering complexity, Labor is the labor cost, and Material is the material cost;
[0056] Cost Records and Classification:
[0057] Predefined cost classification rules, such as design, construction, procurement, and labor, are used to record detailed information for each expense, including date, amount, category, and description, via API interface or manual input. Cost data is stored in a relational database, and a rule engine or machine learning classifier such as K-nearest neighbor algorithm or support vector machine is used to automatically classify expenses into the corresponding cost center. The specific steps are as follows:
[0058] Collect historical cost data, including detailed information and classification of each expense, normalize the data to ensure that each feature is on the same scale, select an appropriate K value, such as 5, train a K-nearest neighbor classifier using historical data, extract features from new records, and use the trained K-nearest neighbor classifier for classification prediction.
[0059] Cost approval process:
[0060] Predefined approval rules, such as approval levels for different amount ranges, are used to automate the approval process through workflow engines like Activiti or Flowable. Each step in the approval process is communicated to relevant personnel via email, SMS, or system notification.
[0061] Cost Analysis and Report:
[0062] Extract cost data from the database, process and analyze the data using data analysis tools such as Pandas or NumPy, and generate bar charts, pie charts, and trend charts using data visualization libraries such as Matplotlib or Plotly. Generate customized cost reports according to user needs.
[0063] Cost variance analysis:
[0064]
[0065] Where Cost Deviation is the percentage of cost deviation, Estimated Cost is the estimated cost, and Actual Cost is the actual cost;
[0066] Cost Overrun=Actual Cost-Budget
[0067] Cost Overrun is the amount of cost overrun, and Budget is the project budget.
[0068] Data processing
[0069] Remove irrelevant or missing data, handle outliers and isolated points, extract key features from the original data, such as project scale, complexity, material requirements and labor costs, and normalize the feature values to the same dimension using Z-score normalization or Min-Max normalization.
[0070] Machine learning model training
[0071] Historical cost data is divided into training and test sets. A linear regression model is selected, and the model is trained using the training set data. The parameters β0, β1, β2, β3, and β4 are optimized. Then, the performance of the model is evaluated using the test set data, such as mean squared error or coefficient of determination.
[0072] The user management module handles user registration, login, role definition, and access control. The project management module handles project creation, task assignment, progress tracking, and document management, and provides a project template library. The contract management module handles contract creation, clause extraction, execution monitoring, and change management. The supply chain management module handles supplier management, procurement management, inventory management, and supplier evaluation. The risk management module handles risk identification, assessment, response strategy generation, and real-time alerts. The data visualization module provides visual representations of costs, schedules, and risks, generating charts and reports. The collaboration management module handles task assignment, instant messaging, file sharing, and meeting management. The feedback and optimization module collects user feedback, tracks issues, and continuously improves the system.
[0073] The cloud-based engineering cost management method includes the following steps:
[0074] S1. Registration and Login
[0075] Users register and log in through the user management module, and the system assigns corresponding permissions based on user roles;
[0076] S2. Management Estimates
[0077] In the project management module, you can create and manage projects, including basic project information, phase division, task allocation, and document management. In the cost management module, you can perform cost estimation and generate preliminary cost estimates based on project parameters and historical data.
[0078] S3. Record Approval
[0079] Record and categorize every expense in the project, implement a cost approval process, conduct multi-level approvals and automatic workflows, and generate approval records;
[0080] S4. Report Generation
[0081] Generate customized cost analysis reports, including cost deviation analysis and trend forecasting; create, sign, store and manage contracts through the contract management module; extract key clauses from contracts and generate contract summaries.
[0082] S5. Risk Assessment
[0083] By managing supplier information, procurement tasks, and inventory status in the supply chain, the system automatically assesses supplier quotations, quality, and delivery capabilities, identifies potential project risks, evaluates the impact of these risks and corresponding response strategies, and provides real-time early warning notifications.
[0084] S6. Visualizing Data
[0085] The data visualization module generates visual charts and reports on costs, schedules, and risks, helping users intuitively understand the project status. The collaboration management module assigns tasks, facilitates communication and collaboration, sets up file sharing and meeting management, and collects user feedback and tracks the progress of issue resolution through the feedback and optimization module.
[0086] Specifically, the user management module allows users to register and log in through various methods such as email, mobile phone, and social media. It defines different roles, such as cost estimators, project managers, suppliers, and clients, and assigns corresponding permissions to each role. Users can manage their personal information, such as avatars and contact details, and set up an OAuth 2.0-based authentication mechanism to ensure the security of user information.
[0087] In the project management module, users can create and manage multiple projects, including basic project information, phase division, and task assignment. A project template library provides various types of templates, allowing users to choose the appropriate template based on project characteristics and quickly build the project framework. The module records and displays the progress of each stage and task of the project in real time, and allows for the uploading, downloading, and version management of project-related files.
[0088] The cost management module uses integrated intelligent algorithms to generate preliminary cost estimates based on project parameters and historical data. It automatically records every project expense and categorizes them according to different cost centers, such as design, construction, and procurement. It automates cost approval processes and enables multi-level approvals and automatic workflows. It provides cost analysis tools such as bar charts, pie charts, and trend charts, allowing users to generate customized cost reports.
[0089] The contract management module enables the creation, signing, storage, and management of contracts. Through natural language processing technology, it automatically extracts key clauses and information from contracts to generate contract summaries. It monitors contract execution in real time, recording milestones and payment progress. It automatically records and manages contract changes, generating change reports to ensure transparency in the change process.
[0090] The supply chain management module is used to establish a supplier database, recording suppliers' basic information, quotation history, and delivery records. It supports the creation, approval, and execution of procurement tasks, generating purchase orders and procurement reports. It records and manages project inventory in real time, supporting inventory alerts and automatic replenishment suggestions. The system automatically evaluates suppliers' quotations, quality, and delivery capabilities, providing evaluation reports.
[0091] The risk management module automatically identifies potential risks in a project, such as market fluctuations and supply chain disruptions. It generates risk assessment reports, evaluating the likelihood and impact of each risk. It also provides recommendations for risk response strategies, such as alternative suppliers and risk transfer. When project costs or schedules exceed warning thresholds, the system automatically sends alerts to remind relevant personnel to take appropriate action.
[0092] The data visualization module uses charts and dashboards to visually display the project's cost status and trends. It supports various visualization tools such as Gantt charts and milestone charts to show project progress. Heatmaps and Gantt charts are used to display the distribution of risks and their mitigation measures. Users can generate customized reports according to their needs; the system provides a variety of report templates to choose from.
[0093] The collaborative management module assigns, tracks, and manages project tasks, ensuring each task is assigned and completed on time. An integrated chat tool enables real-time communication among team members. Project file sharing and collaboration are enabled, allowing all members to access the latest project materials. Integrated video and audio conferencing tools facilitate remote meetings and collaboration.
[0094] The training and support module offers multiple online training courses and video tutorials to help users quickly master the system's usage and best practices. It shares successful project management and cost control case studies for user reference and learning. Detailed user manuals and operation guides are provided to resolve problems encountered during use. A user community is established to allow users to exchange ideas and share experiences.
[0095] The feedback and optimization module establishes a user feedback mechanism to regularly collect user suggestions and opinions, improving system functionality and user experience. Based on user feedback and market changes, it continuously optimizes system functions to ensure competitiveness. It records user feedback issues, tracks issue resolution progress, and ensures issues are resolved promptly.
[0096] This invention ensures comprehensive and consistent cost management by integrating the entire process from cost estimation to cost recording and classification, and cost approval. Automating cost estimation and approval processes using machine learning models improves the accuracy of cost forecasting and the efficiency of approval, reducing human error and approval time. Automated cost recording and classification guarantee real-time data accuracy, helping to promptly identify and correct cost overruns. Contract management automatically extracts key contract clauses and generates contract summaries using natural language processing technology, reducing the time spent on manual contract reading and review, and improving the efficiency and accuracy of contract management. Automated management of contract changes and execution monitoring ensures timely updates of change information and real-time tracking of contract performance, reducing contract risks. Supply chain management quickly selects suitable suppliers and optimizes procurement decisions by automating the evaluation of supplier quotations, quality, and delivery capabilities. It supports the creation, approval, and execution of procurement tasks, ensuring the standardization and transparency of the procurement process. Real-time inventory management helps to adjust inventory strategies in a timely manner, avoiding shortages or excesses, and improving the responsiveness and efficiency of the supply chain. Risk management utilizes automated tools to identify potential risks in projects, enabling proactive measures to mitigate them; it generates risk assessment reports and response strategy recommendations, providing the project team with a scientific basis for decision-making; and it offers real-time early warning notifications to ensure the project team is promptly informed of risk status and can take appropriate action. The data visualization module uses charts and dashboards to visually display project cost status and trends, helping project managers quickly understand and analyze data; it also provides various visualization tools to display project progress and risk distribution, facilitating a comprehensive understanding of project status and timely adjustments to project plans. The collaborative management module ensures team members understand their responsibilities and task progress through the allocation, tracking, and management of project tasks; it integrates chat and video conferencing tools to enable real-time communication and collaboration among team members, improving team efficiency; and real-time communication and collaboration facilitate rapid information sharing, reducing information asymmetry and communication barriers.
[0097] 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 cloud-based engineering cost management system, including a user management module, characterized in that: The user management module is connected to the project management module, the project management module is connected to the collaboration management module and the cost management module, the cost management module is connected to the contract management module, the contract management module is connected to the supply management module, the supply management module is connected to the risk management module, the collaboration management module is connected to the data visualization module, the data visualization module is connected to the training and support module, and the training and support module is connected to the feedback and optimization module. The project management module and the collaboration management module are bidirectionally connected; the cost management module and the data visualization module are bidirectionally connected; the contract management module and the training and support module are bidirectionally connected; and the supply management module and the feedback and optimization module are bidirectionally connected.
2. The cloud-based engineering cost management system according to claim 1, characterized in that: The cost management module is used for cost estimation, cost recording and classification, cost approval processes, and generating customized cost analysis reports, specifically: Cost estimation: Users input various project parameters, such as project scale, complexity, material requirements, and labor costs. The machine learning model uses linear regression to estimate costs based on historical data and input parameters. The basic formula is as follows: Cost=β0+β1×Scale+β2×Complexity+β3×Material+β4×Labor Where: Cost is the project cost, Complexity is the engineering complexity, Labor is the labor cost, and Material is the material cost; Cost Records and Classification: Predefined cost classification rules, such as design, construction, procurement, and labor, are used to record detailed information for each expense, including date, amount, category, and description, via API interface or manual input. Cost data is stored in a relational database, and a rule engine or machine learning classifier such as K-nearest neighbor algorithm or support vector machine is used to automatically classify expenses into the corresponding cost center. The specific steps are as follows: Collect historical cost data, including detailed information and classification of each expense, normalize the data to ensure that each feature is on the same scale, select an appropriate K value, such as 5, train a K-nearest neighbor classifier using historical data, extract features from new records, and use the trained K-nearest neighbor classifier for classification prediction. Cost approval process: Predefined approval rules, such as approval levels for different amount ranges, are used to automate the approval process through workflow engines like Activiti or Flowable. Each step in the approval process is communicated to relevant personnel via email, SMS, or system notification. Cost Analysis and Report: Extract cost data from the database, process and analyze the data using data analysis tools such as Pandas or NumPy, and generate bar charts, pie charts, and trend charts using data visualization libraries such as Matplotlib or Plotly. Generate customized cost reports according to user needs. Cost variance analysis: Where Cost Deviation is the percentage of cost deviation, Estimated Cost is the estimated cost, and Actual Cost is the actual cost; Cost Overrun=Actual Cost-Budget Cost Overrun is the amount of cost overrun, and Budget is the project budget. Data processing Remove irrelevant or missing data, handle outliers and isolated points, extract key features from the original data, such as project scale, complexity, material requirements and labor costs, and normalize the feature values to the same dimension using Z-score normalization or Min-Max normalization. Machine learning model training Historical cost data is divided into training and test sets. A linear regression model is selected, and the model is trained using the training set data. The parameters β0, β1, β2, β3, and β4 are optimized. Then, the performance of the model is evaluated using the test set data, such as mean squared error or coefficient of determination.
3. The cloud-based engineering cost management system according to claim 1, characterized in that: The user management module is used for user registration, login, role definition, and permission management.
4. The cloud-based engineering cost management system according to claim 1, characterized in that: The project management module is used for project creation, task assignment, progress tracking and file management, and provides a project template library. The contract management module is used for contract creation, clause extraction, execution monitoring and change management.
5. The cloud-based engineering cost management system according to claim 1, characterized in that: The supply chain management module is used for supplier management, procurement management, inventory management and supplier evaluation, while the risk management module is used for risk identification, assessment, response strategy generation and real-time early warning.
6. The cloud-based engineering cost management system according to claim 1, characterized in that: The data visualization module is used to visualize costs, schedules, and risks, and generate charts and reports. The collaborative management module is used for task allocation, instant messaging, file sharing, and meeting management. The feedback and optimization module is used for collecting user feedback, tracking issues, and continuously improving the system.
7. The cloud computing-based engineering cost management method according to any one of claims 1-6, characterized in that, Specifically, the following steps are included: S1. Registration and Login Users register and log in through the user management module, and the system assigns corresponding permissions based on user roles; S2. Management Estimates In the project management module, you can create and manage projects, including basic project information, phase division, task allocation, and document management. In the cost management module, you can perform cost estimation and generate preliminary cost estimates based on project parameters and historical data. S3. Record Approval Record and categorize every expense in the project, implement a cost approval process, conduct multi-level approvals and automatic workflows, and generate approval records; S4. Report Generation Generate customized cost analysis reports, including cost deviation analysis and trend forecasting; create, sign, store and manage contracts through the contract management module; extract key clauses from contracts and generate contract summaries. S5. Risk Assessment By managing supplier information, procurement tasks, and inventory status in the supply chain, the system automatically assesses supplier quotations, quality, and delivery capabilities, identifies potential project risks, evaluates the impact of these risks and corresponding response strategies, and provides real-time early warning notifications. S6. Visualizing Data The data visualization module generates visual charts and reports on costs, schedules, and risks, helping users intuitively understand the project status. The collaboration management module assigns tasks, facilitates communication and collaboration, sets up file sharing and meeting management, and collects user feedback and tracks the progress of issue resolution through the feedback and optimization module.