42 results about "Estimation" patented technology

The invention relates to the technical field of building engineering cost intelligent estimation, and discloses a building engineering cost intelligent estimation and checking method fusing a domain knowledge graph and a large language model, and the method comprises the following steps: S1, building a building engineering domain knowledge graph (KG), integrating a quota library, a material price library and historical project data, and carrying out the calculation of a building engineering domain knowledge graph (KG); and defining an entity relationship and a dynamic updating rule. According to the intelligent building engineering cost estimation and checking method fusing the domain knowledge graph and the large language model, a closed loop of knowledge structuring (KG) + semantic comprehension (LLM) + multi-modal reasoning is realized for the first time, engineering cost management is promoted to be transformed from experience driving to data-knowledge dual driving, a reusable technical normal form is provided for the field of intelligent construction, and the engineering cost is estimated and checked. The method solves the problems of efficiency, precision, dynamics and interpretability of traditional cost management, has technical innovation and practical value, and provides core technical support for digital transformation of constructional engineering.

The invention discloses a BIM (Building Information Modeling)-based big data-driven project cost collaborative management system in the technical field of project management, and solves the problem of influence of environmental factors on cost prediction. An environmental influence coefficient A is obtained through calculation, the environmental influence coefficient A and building information model data are unified into an input structure, and the intelligent parameter analysis module realizes significance identification of environmental factors influencing the cost by using deep clustering and linear regression; the system is combined with a dynamic display unit, reflects a cost deviation value delta C in real time and supports multi-path decision analysis, so that a project team can quickly optimize a scheme. Through model optimization training, the self-adaptive engineering cost prediction model improves the estimation accuracy under the assistance of historical data and current characteristics, the budget correction frequency and the financial management complexity are reduced, and the accuracy and effectiveness of engineering cost management are systematically enhanced.

The invention discloses a flood disaster loss real-time estimation method and system. Relates to the technical field of flood disaster calculation methods. According to the method, remote sensing satellite data is combined, a loss evaluation system of flood disaster-inducing factors and interaction of the flood disaster-inducing factors is constructed, cross-platform efficient processing can be carried out, precision is improved through multi-algorithm fusion, multi-factor dynamic modeling is established, real-time monitoring is carried out, and an open framework is extensible and has high universality; the method comprises the following steps: carrying out statistical analysis before a disaster by utilizing historical disaster situation data, carrying out a damage situation estimation experiment on the basis of a built flood disaster hydrodynamic model under the condition that disaster-affected units are coupled with disaster-affected body types, constructing a loss state vulnerability curve and a loss rate curve through interaction of a plurality of disaster-inducing factors, and calculating the damage situation of the flood disaster according to the loss state vulnerability curve and the loss rate curve. Regional loss rate calculation and loss amount estimation are carried out, the loss amount is rapidly estimated in real time when an actual disaster occurs, a scientific basis is provided for emergency response and risk management, and then decision makers are helped to formulate scientific disaster response measures.

The invention belongs to the technical field of information and communication for management or supervision, and relates to a management method and system for reckoning progress and income based on cost resource usage amount, and a readable medium, and the method comprises the steps: creating a progress plan of a project; the actual progress is obtained in real time by collecting multi-source data, and the project cost is analyzed according to a progress plan; inputting the data of the actual income and the actual progress into the project calculation model, and calculating the project income by dynamically adjusting the weight of each type of resources; performing project economic activity management on the analysis result of the project cost and the calculated project income; through project economic activity management, early warning is carried out on data which does not reach a progress plan and plan income, and an early warning level is set. According to the method, multi-dimensional and multi-level management control can be performed on the project, key nodes and risk items of the project are automatically displayed through a visual analysis technology, and cost and progress monitoring of the whole life cycle from starting to ending of the project is realized.

The invention discloses a multi-agent active radio map estimation method. The method comprises the following steps: establishing an environment map, a radio map and a multi-agent sampling trajectory planning model; the map estimation module periodically trains a Gaussian process model based on wireless map data historically sampled by an intelligent agent, outputs a mean map, a variance map and a variance threshold value, and further calculates an uncertain map; the regional exploration module divides a task environment into a plurality of Voronoi units, allocates an intelligent agent exploration window, calculates the mass center of an unknown connected region based on the exploration window, and evaluates the mass center with the maximum utility as a waypoint; and the neighborhood exploration module calculates a spatial sampling correlation matrix related to neighborhood sampling density and executes multiple rounds of exploration for ensuring neighborhood uniformity. According to the method, the estimation precision under the fixed sampling time concerned by existing work can be improved, the overall uncertainty of the area can be rapidly reduced, namely the confidence degree of map estimation is improved, and therefore efficient and complete exploration is achieved.

Based on demographic information of the area being analyzed, the system estimates the distribution of people with user-specified attributes at a given location within that area. [Solution] The human flow information estimation device 2000' includes a calculation device 2100 that performs human flow information analysis based on predetermined demographic information, which includes the number of people located in each of a plurality of predetermined area meshes and information on the attributes of those people. The human flow information estimation unit 2103 identifies a set of unit sub-regions that cover the area to be analyzed without overlapping each other, and based on demographic information and predetermined lifestyle information, it distributes the number of people from the demographic information to the unit sub-regions at predetermined time intervals, based on the type of place and the size of the place corresponding to the classification of people's behavior in each area mesh, and estimates aggregated data for each unit sub-region. Based on the aggregated data, the human flow information estimation unit 2103 calculates a human absorption capacity value, which is the ratio of the number of people with the analyzed attributes for each unit sub-region to a predetermined value.

The invention relates to the technical field of economic measurement modeling, in particular to an economic prediction method and system based on weekly, monthly and quarterly big data, electronic equipment and a medium. The method comprises the following steps: acquiring multi-frequency multi-source economic time sequence data; performing frequency mixing alignment preprocessing on the multi-source economic time series data according to a preset frequency mixing data processing rule to generate a frequency mixing data set; constructing a connection model through a predefined modular architecture and a connection algorithm based on the frequency mixing data set; training the connection model through a parameter estimation algorithm; and inputting multi-source economic time sequence data obtained in real time into the trained connection model, executing high-frequency prediction, and outputting a real-time prediction result. By means of the mode, the technical problem that when an existing mixing dynamic factor model deals with multi-frequency mixing data, prediction precision is insufficient is solved, and the capacity of conducting high-frequency, accurate and real-time monitoring on the macroeconomic trend is improved.

The invention provides a workload assessment method and apparatus, and an electronic device. The method comprises the steps of obtaining a first research and development demand of a research and development project to be assessed; determining a first K-nearest neighbor classification model from the M K-nearest neighbor classification models according to the first research and development demand, wherein the value of the nearest neighbor number K in the first K-nearest neighbor classification model is a first numerical value; determining a first number of neighbor historical research and development demands in front of the first research and development demand in the first training sample according to the first K neighbor classification model; the first training sample comprises historical research and development demands of at least two historical research and development projects and corresponding historical workloads, and the first training sample is divided into at least one cluster based on a first K-nearest neighbor classification model; and estimating the workload of the first research and development demand according to the historical workload of the historical research and development demand in the first cluster, wherein the first cluster is a cluster in which the first number of neighbor research and development demands are located at the most same clusters in the at least one cluster of the first training sample. Therefore, the workload estimation accuracy is improved.

The invention discloses a project planning and site selection method based on available land analysis and land development cost estimation, and the method comprises the steps: carrying out the land current situation analysis of land parcels to be selected one by one, i.e., carrying out the spatial overlay analysis of the screened land parcels to be selected meeting conditions and the land utilization current situation data of adjacent years, analyzing the land current situation of each land parcel, and carrying out the calculation of the land development cost of each land parcel; comprising the following steps: further analyzing the areas and proportions of cultivated land and forest land for the agricultural land, estimating the land cost based on the land current situation analysis result of a to-be-selected land parcel, and calculating the land cost according to the agricultural land area, the cultivated land area, the forest land area and the current policy. According to the method, cultivated land purchase indexes and capital costs required for land acquisition compensation are estimated, land parcels to be selected are sorted according to different dimensions such as occupied cultivated land areas, land capital costs, landforms and the like, government departments can conveniently check land element input-output ratios and land performance evaluation, and the pertinence of investment attraction and the efficiency and accuracy of project planning and site selection are improved.

The application discloses a kind of track traffic full life cycle economy estimation system based on multidimensional data, it is related to track traffic engineering economic estimation technical field, the system includes following component parts: data acquisition module, time sequence linkage mapping module, substage estimation model module, feedback correction module and dynamic output module;The application is through covering track traffic full life cycle, establishes effective association, to substage estimation model accurately calculates each stage economic cost, provides solid data support for economic analysis;Dynamic feedback correction mechanism is built, real-time response deviation changes, improve estimation accuracy;Whole-process closed-loop optimization design, solve prior art defects, adapt to project dynamic change, provide timely reliable reference for project full cycle economic management.

The invention discloses a line parameter identification method based on a collaborative variance matrix, and the method comprises the following steps: S1, building a parameter model, and representing a line parameter as an undetermined coefficient; s2, constructing an optimization objective function about an undetermined coefficient by using historical measurement data and a power flow equation; s3, performing optimization solution of line parameters based on the collaborative variance matrix, adding physical constraint conditions, and searching the line parameters; and S4, judging according to the iteration condition of the optimization algorithm, and finally outputting the identified line parameters. According to the method, the line parameter identification technology based on the CMA-ES optimization algorithm is provided, and the population fitness is evaluated by adopting the Newton-Raphson method; a physical-information fusion driven power distribution network power flow state estimation model based on line parameter identification is designed, the problem of inaccurate or missing line parameters is effectively solved, and reliable data support is provided for planning and operation of a novel power system.

The invention provides a mixed data regression model-based pm2.5 influence factor analysis method and system, and the method comprises the steps: building a mixed data regression model of which covariables are component data and numerical data and dependent variables are functional data: the mixed data regression model is a pm2.5 concentration curve of a city, is the functional data, is the proportion of first yield, second yield and third yield of the city, and is called the proportion of third yield for short; the data is component data, logarithm of per capita GDP, average temperature and numerical data, is a to-be-estimated component type coefficient changing along with time, is distributed to a component type covariable at any moment, is a to-be-estimated function type coefficient and is a function type residual error; obtaining robust M-estimation based on equidistant logarithmic ratio transformation, functional basis expansion and an iterative reweighted least square method; and according to the estimated values, analyzing the influence of the three-yield ratio, the per capita GDP and the average temperature of each city on the pm 2.5. The method can be used for analyzing the pm 2.5 influence factors.

This invention provides a method and system for calculating the construction progress and cost variances of power transmission and transformation projects. The method includes performing multivariate correlation analysis on construction period data to calculate the planned duration of each process; identifying critical path processes that affect the total project duration, determining the time percentage of each critical path process within the critical path, and calculating the total project duration based on the time percentage of each process within the critical path and the planned duration of each process; determining alternative project execution plans based on the total project duration; calculating the personnel and machinery costs of each process based on the alternative project execution plans; accumulating the costs of each process, and comparing the cost differences between different alternative project execution plans. This invention develops a quantitative analysis tool for the correlation between construction period and cost through an innovative method, constructing a multi-dimensional linkage model of "schedule-cost-resources" to accurately quantify the intrinsic relationship between construction efficiency losses and cost fluctuations, avoiding errors from empirical estimations.

The invention discloses an evapotranspiration Bayesian model average fusion method based on a hybrid statistical framework in China, and relates to the technical field of crossing of ecological hydrological remote sensing and Bayesian statistical modeling. According to the method, the four types of ET products are selected to be fused; the core algorithm can avoid structural deviation caused by a single model; the space-time coverage is complete, the space-time coverage covers the research area in 2007-2021, and the data consistency requirement of the fusion model is met; the reliability of a public data set which is widely used at home and abroad is widely verified in multiple independent researches. And the fusion process is realized through weighted average of the prediction probability density function of each model, and finally monthly ET estimation is generated.

The invention discloses a diffusion model efficient fine tuning method for open recognition, and relates to reasoning space compression based on a Top-K rule. Constructing a local sorting graph based on HodgeRank and accelerating posteriori estimation; generating an open sample based on semantic consistency; on the basis of joint discriminant optimization of consistency indexes, on the premise that closed category classification accuracy is kept, the sampling number and calculation time needed by the model in the reasoning stage are remarkably reduced, and reasoning efficiency is greatly improved; and meanwhile, through explicit modeling, a semantic boundary and a discrimination mechanism of the samples are opened, so that the recognition and rejection capabilities of the model on the samples with unseen categories are effectively enhanced. In conclusion, the method realizes good balance among accuracy, efficiency and open generalization ability, and has wide application value and popularization potential in industrial deployment, scientific research application and high-risk identification tasks.

This invention discloses a soft measurement modeling method for multiphase intermittent processes based on an improved geodesic manifold kernel. The method includes: collecting platform parameters from a cloud server; projecting source and target domain data onto a common manifold subspace using a geodesic manifold kernel method based on linear local tangent space arrangement to reduce the data distribution differences between the source and target domains; using a time-series-based fuzzy clustering method to divide the source domain data into phases, obtaining phase division points; and establishing sub-phase soft measurement models based on different phase characteristics using different modeling methods. For phases with slowly changing process characteristics, partial least squares regression is used to establish the soft measurement model; for phases with rapidly changing process characteristics, partial least squares regression based on real-time learning is used to establish the soft measurement model. This method establishes sub-phase soft measurement models for multiphase intermittent processes, enabling the estimation of difficult-to-measure variables and improving the performance of the soft measurement model under varying operating conditions.

The invention discloses a transpiration and evapotranspiration ratio data set fusion method, system and device based on triple matching, a medium and a product, and relates to the field of ecological hydrology. The method comprises the following steps: firstly, acquiring three sets of transpiration T and evapotranspiration ET data sets from different sources, and preprocessing to obtain three preprocessed T and ET data sets; for the three preprocessed T and ET data sets, respectively calculating error variances of T and ET in each data source by using a triple matching method; according to the error variance of the T and the ET in each data source, distributing the weight of the T and the ET in each data source; performing fusion calculation according to the weight of the T and the weight of the ET in each data source to obtain the fused T and the fused ET; and calculating the ratio of T to ET after fusion to obtain a T / ET data set after fusion. According to the method, the problem of systematic deviation of multi-source T / ET data can be effectively solved, the estimation precision is remarkably improved, and the adaptability to regional heterogeneity is enhanced.

The application discloses a kind of data missing scenario under city low carbon level evaluation method and device, method includes the following steps: step S1, the multi-source index data of the city to be evaluated is obtained, the completeness of the multi-source index data is analyzed, and the data completeness is calculated;Step S2, based on the data completeness corresponding evaluation mode is enabled and corresponding index set is called;Step S3, the index set called is judged to be missing, according to the index type of missing data from the proxy rule library corresponding estimation rule is selected, and the estimated value of missing index is generated based on estimation rule;Step S4, the real observation data in the index set called is fused with the estimated data generated based on estimation rule, and the complete evaluation data set is constructed;Step S5, the evaluation model of city low carbon development level is constructed, and the city low carbon level evaluation is carried out based on the evaluation data set and the evaluation model.The application can reasonably evaluate the city low carbon level when data is incomplete.

The invention belongs to the technical field of construction progress management, and particularly relates to a construction progress management method and system based on improved BiLSTM and PERT three-point estimation, and the method comprises the steps: firstly obtaining a historical construction task progress data set, inputting the historical construction task progress data set into an improved BiLSTM model, and carrying out the dynamic prediction of the future construction task progress; then based on the predicted future construction task progress prediction result data set, the completion probability that the construction task is completed before the target time point is calculated through a PERT three-point estimation method, progress risk quantification is achieved, and finally construction progress management is achieved according to the completion probability that the construction task is completed before the target time point. It can be ensured that high-risk tasks obtain sufficient resource support, and then it is ensured that construction tasks can be completed on time. Dynamic prediction of future construction task progress and quantitative evaluation of progress risks are integrated, the efficiency and the intelligent degree of construction progress management are improved, and the method is suitable for progress management of large-scale construction projects.

The invention relates to the technical field of urban planning and computer decision support, and discloses a portable estimation tool and method convenient for counting urban updating and demolition cost, firstly, a hierarchical evaluation index system is constructed based on an improved analytic hierarchy process through a basic value evaluation module, and individual basic value of each updating unit is scientifically calculated; then, through a cooperative benefit evaluation module, each updating unit is constructed into a network model, and the cooperative benefit between any two units is quantitatively calculated based on coupling functions such as infrastructure sharing and industrial linkage; and finally, the combination benefit decision-making module updates the combination according to the user designation. According to the method, the limitation of traditional individual evaluation is overcome, the systematic value-added effect of the vast update is revealed and quantified, a more scientific and accurate quantitative decision basis is provided for urban update planning, and the comprehensive benefits of planning are remarkably improved.

The invention discloses a geostatistical modeling method uncertainty quantification method based on a mutual information entropy framework, and relates to the technical field of geostatistical modeling quality control, and the method comprises the steps: collecting the space sample data of an estimation domain, determining target methods, constructing a parameter matrix for each target method, and carrying out the calculation of the parameter matrix; carrying out multiple modeling on each target method according to the parameter matrix on the estimation domain to generate a plurality of modeling results; dispersing each realization modeling result to a unified grid to obtain a realization modeling result set of each grid, counting distribution of a plurality of realization modeling results for each grid, constructing probability distribution of each grid, calculating point entropy of each grid based on the probability distribution, and forming a spatial uncertainty entropy field. According to the method, quantification of spatial uncertainty is achieved by achieving probability distribution and entropy measurement, IMUI indexes are constructed through joint entropy, conditional entropy and mutual information, and evaluation of output convergence and structural consistency of the method is achieved.

This invention provides a fine-scale population spatialization method that integrates geospatial and internet data. The method includes: obtaining residential building footprint data within the study area; constructing geographic grid data for the study area and determining the proportion of residential building footprint area in each geographic grid unit; obtaining the number of floors in internet-connected buildings within the study area, establishing a residential building floor estimation model, and determining the initial input values ​​for the residential building floor estimation model; calculating the estimated population for each administrative region, performing error verification with the corresponding administrative region's population statistics, iterating based on the error verification results, and optimizing and adjusting the parameters of the residential building floor estimation model. This invention constructs a population spatialization model by integrating land use (residential land), surface-covered building areas, and the number of floors in internet-connected buildings, classifying the population living in urban and rural areas to estimate the floor height of residential buildings, achieving fine-scale population spatialization with high accuracy.

The invention discloses an engineering cost calculation method and system based on digital sand table plotting, and relates to the technical field of engineering cost calculation, and the method comprises the steps: carrying out digital sand table data modeling, and plotting an engineering structure for information association; establishing a dynamic engineering cost calculation rule base, and calculating the cost of the engineering module; and generating an engineering cost distribution map, and performing three-dimensional visual display. According to the engineering cost calculation method based on digital sand table plotting, the construction cost calculation process is more intelligent and dynamic due to establishment of the rule base, proper rules can be matched in real time according to input conditions, and the efficiency and accuracy of cost estimation are improved. Through visual display, complex cost data becomes visual and readable, so that project managers and related parties can quickly know cost distribution and influences thereof, and cooperation efficiency and decision-making quality are improved. The method has better effects in the aspects of automation, calculation efficiency and accuracy.

Based on demographic information of the area being analyzed, the system estimates the distribution of people with user-specified attributes at a given location within that area. [Solution] The human flow information estimation device 2000' includes a calculation device 2100 that performs human flow information analysis based on predetermined demographic information, which includes the number of people located in each of a plurality of predetermined area meshes and information on the attributes of those people. The human flow information estimation unit 2103 identifies a set of unit sub-regions that cover the area to be analyzed without overlapping each other, and based on demographic information and predetermined lifestyle information, it distributes the number of people from the demographic information to the unit sub-regions at predetermined time intervals, based on the type of place and the size of the place corresponding to the classification of people's behavior in each area mesh, and estimates aggregated data for each unit sub-region. Based on the aggregated data, the human flow information estimation unit 2103 calculates a human absorption capacity value, which is the ratio of the number of people with the analysis target attributes for each unit sub-region to a predetermined value.

The application discloses a kind of land space planning management system and method based on big data, it is related to spatial planning management technical field, in the flood season waterlogging and project approval collaborative scene, using risk and utility double threshold value automatic parameter estimation desensitization, sensitive data can be shared and available are realized, through event time anchoring synchronization, time uncertainty and version pedigree, make cross-source data alignment traceable, can be calculated, control line and index threshold are constructed as constraint atlas, conflict identification and repair candidate are automatically output, and optimal planning scheme is selected with non-dominated solution set, generates approval and land adjustment signal issue, improves decision interpretability and landing efficiency.

This invention relates to the field of computer technology for temperature estimation, aiming to address the pain points of existing technologies, such as reliance on single-phase data, insufficient capture of temporal and global information, and lack of spatial uncertainty assessment. The technical solution includes: preprocessing multi-source data, extracting and standardizing key features related to climate, geography, and time in multiple dimensions, constructing a multi-scale time-series dataset to determine the optimal time series; designing and testing various models, selecting the HyTC-TaNet model, which combines Transformer and CNN through a specific layer sequence to capture global temporal dependence and local spatial features respectively; using SHAP technology to analyze the impact of features on the estimation results; and constructing a difference index through AOA evaluation to define the model's applicable area and extrapolation area. This invention significantly improves the accuracy of daily average temperature estimation, overcomes the "black box" problem of deep learning, compensates for the inability to quantify spatial error distribution, adapts to complex and heterogeneous surface environments, and provides a technical framework reference for similar research.

The invention discloses a block chain-based subentry fund budget and statistical analysis method, and particularly relates to the technical field of block chain data management. The method comprises the following steps: acquiring original budget data submitted to a block chain account book by a plurality of project participants, and performing segmented indexing to form a historical budget version sequence; performing evolution comparison on the historical budget version sequence to generate a failure budget set; performing feature extraction in combination with the associated execution data, and constructing a multi-dimensional index set; performing grade evaluation based on the multi-dimensional index set and the evaluation context, and outputting a validity label result set; performing budget data filtering and tagging based on the effective tag result set to generate a refined budget statistical sample set; according to the method, the refined budget statistical sample set is subjected to comprehensive trend evaluation, a statistical analysis result is generated, a traceable traceable path index is provided, identification, isolation and efficient utilization of failure budget data are achieved, and the accuracy of fund analysis and the reliability of management decision are remarkably improved.

The application discloses a subjective city performance visualization question and answer method based on a large language model, which is characterized by using a large language model (LLM) to perform query rewriting, knowledge base retrieval and prompt integration on the natural language query of a user, effectively identifying the user's intention, combining semantic information and spatial distribution of points of interest (POIs), generating an accurate semantic density map through a semantic self-adaptive kernel density estimation algorithm, positioning a significant area based on a density-based spatial clustering algorithm, analyzing geographical relationships of different scales, and providing a detailed interactive visual answer. Compared with the prior art, the application solves the complex visualization automatic question and answer problem of city performance, enhances the adaptability of subjective city performance analysis to different scenarios through the large language model, and improves the accuracy and generalization ability of the analysis. The application can be widely applied to various practical application scenarios such as city site selection and travel planning, and has high practical value and good development prospect.

A headcount estimation system (1001) according to the present disclosure comprises an image capture unit (11), an image processing unit (21), a congestion level evaluation unit (22), and a correction unit (23). The image capture unit (11) captures an image of a prescribed area. On the basis of the image captured by the image capture unit (11), the image processing unit (21) calculates the number of people in the prescribed area and the number of people in each of a plurality of sections obtained by dividing the prescribed area. The congestion level evaluation unit (22) evaluates the level of congestion in the prescribed area. The correction unit (23) identifies the section to be referred to on the basis of the level of congestion, and corrects the number of people in the prescribed area on the basis of the identified section.

The invention discloses a power transmission and transformation project cost prediction method and system based on data mining, and relates to the technical field of project cost prediction, and the method comprises the steps: collecting multi-dimensional data covering project attributes, environmental factors and historical cost, and building a project database; performing missing value filling and preprocessing on the data, and calculating a correlation coefficient matrix; determining the number of principal components based on principal component analysis, calculating a principal component load matrix, and extracting a candidate key field set; and carrying out partial correlation analysis, cross validation and regression significance test on the candidate fields and the project cost data, identifying key factors which have significant influence on the cost, constructing a project cost prediction model based on the key factors, and carrying out scientific prediction on the cost of a new project. According to the method, the problems of high dependence and low data utilization rate of traditional experience estimation are solved, systematic identification and cost prediction of key factors of the cost are realized, and support is provided for investment decision and cost control of power grid construction.