CN-121616111-B - Road construction material cost control system

CN121616111BCN 121616111 BCN121616111 BCN 121616111BCN-121616111-B

Abstract

The invention relates to the technical field of cost management, in particular to a road construction material cost control system which comprises a material consumption data acquisition module, a material dynamic consumption reference generation module, a material consumption cost abnormality discrimination module and a material space risk linkage identification module. According to the invention, material consumption data are collected in real time through field equipment, multidimensional factors such as progress and equipment operation are combined, a weighted moving average and multiple linear regression model is adopted to dynamically correct consumption references, accurate correction of material plan consumption is realized, abnormality is found in time through actual consumption cost and dynamic reference interval judgment, regional material consumption risks are identified by means of space aggregation analysis, from single-point monitoring to multidimensional dynamic judgment and space linkage identification are realized, scientificity and timeliness of cost control are improved, potential abnormality is actively early-warned, human errors and data lag are reduced, reasonable distribution of power-assisted resources and refined management of cost are realized, and fund utilization efficiency and risk prevention and control capability are improved.

Inventors

LIU JICHANG
Yu Focai
LIU JIANJUN
WANG KUN
LI YAJUN
LUO HONGLIANG
YANG YANG
CAO LIQIANG

Assignees

成都嘉新科技集团有限公司

Dates

Publication Date: 20260512
Application Date: 20260130

Claims (7)

1. A road construction material cost control system, the system comprising: The material consumption data acquisition module is used for acquiring actual consumption, planned consumption, progress percentage and equipment operation time of the material through the field equipment, correcting the planned consumption of the material by adopting a weighted moving average model, generating weighted corrected consumption of the material and transmitting the weighted corrected consumption of the material to the material dynamic consumption reference generation module; the material consumption data acquisition module includes: The method comprises the steps that a field data acquisition submodule acquires actual consumption of materials, planned consumption, progress percentage and equipment operation time of field equipment, calculates consumption difference degree according to the actual consumption of the materials and the planned consumption, integrates the progress percentage and the equipment operation time, correlates and classifies data of different time periods, and establishes field material consumption basic data quantity; The consumption weight determination submodule invokes the field material consumption basic data quantity, extracts the equipment operation time length of a plurality of periods according to the time proximity principle in the weighted moving average model, takes the time length as a core factor of weight distribution, distributes differentiated weight values for the material consumption data of the plurality of periods, performs normalization calculation on all the weight values, and generates a moving average weight coefficient; the weighted moving correction submodule calls the planned consumption of the material in the field material consumption basic data volume, applies a weighted moving average model according to the moving average weight coefficient, multiplies the planned consumption of a plurality of periods by the corresponding weight coefficient, and sums the calculated products of all the periods to obtain the weighted corrected material consumption; the material dynamic consumption reference generation module is used for acquiring the weighted corrected material consumption, meteorological parameters and material unit price, correcting the material consumption by adopting a multiple linear regression model, generating a material dynamic consumption cost reference interval and transmitting the material dynamic consumption cost reference interval to the material consumption cost abnormality judgment module; The material consumption cost abnormality judging module is used for calculating the material actual consumption cost according to the material actual consumption and the material unit price, calling the material dynamic consumption cost reference interval to judge the interval, generating a material consumption cost abnormality judging result, and transmitting the material consumption cost abnormality judging result to the material space risk linkage identifying module; The material space risk linkage identification module is used for carrying out space aggregation analysis by acquiring an abnormal discrimination result of the material consumption cost and the material consumption cost of the same construction site, and outputting material space linkage risk information, wherein the material space linkage risk information comprises space aggregation degree, risk distribution type and influence range; The space aggregation degree in the material space linkage risk information is quantified by calculating an average contour coefficient of each cluster, and the average contour coefficient is used as a measurement value of the space aggregation degree, wherein the average contour coefficient is represented by the formula: Calculating; Wherein, the Representing clusters of clusters Is used for the average profile coefficient of (c), Representing clusters of clusters The total number of work points within the interior, Representing clusters of clusters A single work site within the interior of the building, Representative working point Average Euclidean distance between the cluster and all other work points in the same cluster, Representative working point The minimum of the average euclidean distance from the worker points in all other clusters, Representative of And Is a larger value of (a); The risk distribution type is determined as a gallery type risk by calculating the minimum boundary rectangle of all working point space coordinates in each screened cluster and solving the aspect ratio of the rectangle, if the aspect ratio is larger than a preset shape proportion threshold value, otherwise, the risk distribution type is determined as a patch type risk; The influence range is defined by constructing a minimum convex hull polygon of all working point space coordinates in the screened cluster, the geographic coordinate vertex set of the minimum convex hull polygon is used as boundary data of the influence range, and meanwhile, the area of the polygon is calculated to be used as a quantization index of the influence range.
2. The road construction material cost control system according to claim 1, wherein the weighted corrected material consumption is a corrected consumption and a corrected basis parameter, the material dynamic consumption cost reference section includes a lower cost limit, an upper cost limit and a section fluctuation range, and the material consumption cost abnormality discrimination result is an abnormal state, an abnormal type and an associated risk.
3. The road construction material cost control system according to claim 1, wherein the material dynamic consumption reference generation module includes: the regression variable screening submodule acquires the weighted corrected material consumption, the meteorological parameters and the material unit price, takes the weighted corrected material consumption as a dependent variable and the meteorological parameters and the material unit price as independent variables based on a multiple linear regression model, and screens the independent variables with the degree of association with the dependent variables exceeding a preset association threshold value by calculating association coefficients between the independent variables and the dependent variables to obtain a multiple regression model core influence factor; The consumption dynamic correction submodule calls the core influence factors of the multiple regression model, constructs a regression equation according to the multiple linear regression model, multiplies the current values of the core influence factors by the corresponding regression coefficients in the regression equation, sums the multiplied values, adds the multiplied values with constant terms, corrects the weighted corrected material consumption, and generates the material consumption after the environmental factor correction; And the cost reference area measurement operator module multiplies the material consumption and the material unit price according to the environmental factors after correction to obtain a cost center value, calculates a confidence interval of the cost center value under a specified confidence level according to a prediction standard error of the multiple linear regression model, takes the upper limit and the lower limit of the interval as fluctuation boundaries, and establishes a material dynamic consumption cost reference interval.
4. The road construction material cost control system according to claim 3, wherein the material consumption cost abnormality determination module includes: The actual cost accounting submodule acquires the actual consumption of the material and the unit price of the material, multiplies the consumption value by the unit price value, adds up all the multiplication results, calculates the total cost value in the period, and establishes the occurrence cost of the material in the current period; The cost interval judging submodule calls the current material occurrence cost and the material dynamic consumption cost reference interval, compares the value of the current material occurrence cost with the upper limit and the lower limit of the material dynamic consumption cost reference interval, marks the current material occurrence cost as an abnormal state if the value of the current material occurrence cost exceeds the upper limit and the lower limit of the interval, marks the current material occurrence cost as a normal state if the value of the current material occurrence cost is within the range, and generates a material consumption cost abnormal judging result.
5. The roadway construction material cost control system of claim 4, wherein the material space risk linkage identification module comprises: The cost data integration submodule acquires an abnormal judging result of the material consumption cost and the material consumption cost of the same construction site, integrates two types of data by taking the construction site as a basic unit, carries out numerical treatment on the abnormal judging result to form a risk mark, forms a feature vector with the material consumption cost data of the corresponding construction site, combines the feature vectors of all the construction sites, and establishes a construction site material consumption feature matrix; the space aggregation analysis sub-module calls the material consumption characteristic matrix of the work points, a K-means clustering algorithm is adopted to initialize clustering centers according to a preset clustering quantity K value, euclidean distances between a plurality of work point data and the clustering centers are calculated circularly, the work points are attributed to the closest clustering centers and the central positions are updated until the clustering center positions are not changed any more, and material consumption space clustering attribution is obtained; And the risk linkage identification sub-module counts the number of work points with risk identification in each cluster according to the attribution of the material consumption space clusters, calculates the duty ratio in the cluster, compares and judges the duty ratio with a set risk identification reference value, screens cluster clusters with duty ratio exceeding the risk identification reference value, and generates material space linkage risk information.
6. The system of claim 5, wherein the consumption weight is calculated by the formula: ; Calculating the moving average weight coefficient; Wherein, the Represent the first The moving average weight coefficient of each cycle, Represents the first The length of the device run for a cycle, Representing the total number of cycles used to calculate the weighted moving average, Representing all Sum of the running time of the equipment of each period; The consumption dynamic correction submodule specifically uses the formula: ; calculating the material consumption after the environmental factor correction; Wherein, the Indicating the amount of material consumed after the environmental factor correction, The constant terms representing the regression equation, Represent the first Regression coefficients corresponding to the individual core influencing factors, Represent the first The current value of the individual core influencing factors, Representing the total number of core impact factors of the multiple regression model, Representing the random error term of the model.
7. The system of claim 6, wherein the meteorological parameters obtained by the regression variable screening submodule include a daily average temperature, a daily accumulated precipitation amount, a daily average wind speed and a daily average air humidity of a construction area; the abnormal types in the material consumption cost abnormal judging result comprise cost hyperbranched abnormality and cost balance abnormality; The cost hyperbranched anomaly is subjected to traceability analysis according to deviation of a material unit price actual value and a planned value and deviation of material actual consumption and the material consumption after the environmental factor correction, and is divided into unit price fluctuation anomaly, consumption excessive anomaly and comprehensive influence anomaly in an iterative manner; The risk identification reference value used by the risk linkage identification sub-module is obtained by acquiring historical finished project data with similarity exceeding a preset similarity threshold value with the current project in engineering geology, construction scale and climate partition, the duty ratio distribution of abnormal working points in a risk cluster in the historical project is counted, and the 90 th percentile of the distribution is used for generating the risk identification reference value.

Description

Road construction material cost control system Technical Field The invention relates to the technical field of cost management, in particular to a road construction material cost control system. Background The technical field of cost management relates to monitoring, accounting and optimizing various resource consumption and economic expenditure of enterprises or engineering projects, and mainly comprises core matters such as cost accounting, cost budget, cost prediction, cost analysis, cost control and the like, and the whole process from cost data acquisition, collection and distribution to decision support is covered. The traditional road construction material cost control system refers to a management system for carrying out cost statistics and control on purchasing, transporting, storing and consumption of materials required in the road construction process, and the traditional road construction material cost control is generally managed by means of manually counting material in-out data, manually compiling a standing book, periodically summarizing material consumption conditions, comparing budgets with actual expenditure and the like. The prior art is highly dependent on manual statistics and manual account setting in the material cost management process, has hysteresis in data acquisition and summarization, is difficult to reflect actual consumption conditions in time, is easy to reduce data accuracy due to omission or misjudgment in the manual operation process, cannot dynamically adjust consumption references, lacks real-time feedback and adjustment capability based on actual field conditions, is weak in space relevance recognition capability on abnormal material consumption and risks, and is easy to cause problems of material consumption exceeding, cost deviation budgeting and the like under the conditions of large material usage amount, long project period or scattered working sites, and management efficiency is influenced and project risks are increased. Disclosure of Invention The invention aims to solve the defects in the prior art and provides a road construction material cost control system. In order to achieve the above purpose, the invention adopts the following technical scheme that the road construction material cost control system comprises: The material consumption data acquisition module is used for acquiring actual consumption, planned consumption, progress percentage and equipment operation time of the material through the field equipment, correcting the planned consumption of the material by adopting a weighted moving average model, generating weighted corrected consumption of the material and transmitting the weighted corrected consumption of the material to the material dynamic consumption reference generation module; the material dynamic consumption reference generation module is used for acquiring the weighted corrected material consumption, meteorological parameters and material unit price, correcting the material consumption by adopting a multiple linear regression model, generating a material dynamic consumption cost reference interval and transmitting the material dynamic consumption cost reference interval to the material consumption cost abnormality judgment module; The material consumption cost abnormality judging module is used for calculating the material actual consumption cost according to the material actual consumption and the material unit price, calling the material dynamic consumption cost reference interval to judge the interval, generating a material consumption cost abnormality judging result, and transmitting the material consumption cost abnormality judging result to the material space risk linkage identifying module; and the material space risk linkage identification module is used for carrying out space aggregation analysis by adopting a K-means clustering algorithm through acquiring the abnormal discrimination result of the material consumption cost and the material consumption cost of the same-construction work point, and outputting material space linkage risk information. As a further scheme of the invention, the weighted corrected material consumption is specifically corrected consumption and correction basis parameters, the material dynamic consumption cost reference interval comprises a cost lower limit, a cost upper limit and an interval fluctuation range, the material consumption cost abnormality judgment result is specifically an abnormal state, an abnormal type and associated risks, and the material space linkage risk information comprises a space aggregation degree, a risk distribution type and an influence range. As a further aspect of the present invention, the material consumption data collection module includes: The method comprises the steps that a field data acquisition submodule acquires actual consumption of materials, planned consumption, progress percentage and equipment operation time of field equipment, calculates consumption differ