58 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 climate mode deviation correction method based on ensemble Kalman filtering and deep learning, and the method comprises the steps: obtaining first climate historical simulation data and future climate estimation data in a research region, and obtaining historical observation data corresponding to climate variables; performing deviation correction on the first climate history simulation data point by point by adopting an ensemble filtering method; carrying out lag processing on the first climate history simulation data; constructing a long short-term memory network model; performing feature engineering processing on future climate estimation data; and performing deviation correction on future climate estimation data by using the average deviation of the Kalman gain sequence and the historical sequence of each time period in the future. According to the method, the dynamic correction capability of the ensemble Kalman filtering and the nonlinear prediction advantage of the deep learning model are combined, the correction precision of climate mode simulation data is improved, and effective deviation correction is carried out on future climate estimation data.

The invention discloses a scientific and technological achievement value estimation system, and the system comprises a data collection module which is configured to obtain technical data, market data, legal data and social data through an API interface; the feature fusion module is configured to adopt a heterogeneous data converter to convert the multi-source heterogeneous data into a unified feature space, and the feature fusion module comprises a text data conversion unit, a numerical data conversion unit and a time sequence data conversion unit; the correlation analysis module is used for constructing a cross-domain knowledge graph; the dynamic evaluation module is configured to adopt an attention mechanism weight distribution model; by integrating the multi-source heterogeneous data acquisition module, the system can comprehensively collect information from technologies, markets, laws and society, limitation of a single data source is avoided, the cross-modal alignment unit realizes alignment of multi-source data spaces through comparative learning, information consistency among different data sources is ensured, and the accuracy of the multi-source data space alignment is improved. And the reliability of the evaluation result is further enhanced.

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 discloses a rural ecological environment comprehensive planning system and method, and relates to the technical field of rural ecological environment planning, and the system comprises the following components: a data collection module, a data processing and analysis module, a dynamic planning model construction module, and a planning strategy generation and adjustment module. According to the method, historical data and real-time monitoring data are widely collected, an advanced climate trend prediction model and an advanced population dynamic prediction model are combined, a comprehensive space-time big data set can be formed, a scientific basis is provided for planning, and meanwhile, a self-defined data feature extraction algorithm and a space-time adaptive deep learning algorithm are applied, so that the planning efficiency is improved. The data value can be deeply mined, the change trend of the ecological environment and the association between different factors are found, and powerful support is provided for formulating a scientific and reasonable planning strategy.

The invention discloses a method for estimating subsidence of ground around a subway under construction by considering weather factors. Selecting a ground subsidence research area around the subway under construction, and obtaining ground subsidence data and weather data in the research area; a settlement estimation subarea module is built based on a time sequence clustering algorithm, monitoring points in a research area are divided into a plurality of settlement estimation subareas according to settlement rule similarity, and the influence of data heterogeneity of different areas is reduced; a graph neural network is adopted to construct a rule capturing module, and the spatial topological relation between monitoring points in the settlement estimation subarea is analyzed; a weather factor module is built through a gating circulation unit neural network, time sequence data corresponding to weather factors are processed, and the influence of the time sequence data on land subsidence is captured; and fusing the settlement spatial-temporal characteristics and the weather characteristics to obtain a land settlement estimated value of the research area. Compared with an existing estimation method, the land subsidence estimation method can obtain more accurate regional future land subsidence data, and reliable data support is provided for subway construction.

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 relates to the technical field of intelligent tourism data analysis, in particular to an intelligent tourism data analysis system based on user behaviors. According to the system, the ratio of the preprocessed actual data, obtained by the second data acquisition unit, of the current quarter to the estimated data, obtained by the data estimation unit, of the current quarter is compared with the preset ratio through the verification unit, so that the relation between the actual data and the estimated data can be judged more accurately; the result of judging whether the pre-estimation is qualified or not subsequently is more accurate; and the data analysis unit verifies whether the estimation is qualified based on the comparison result, preliminarily judges the reason for the unqualified estimation according to the verification result, and adjusts the corresponding parameter of the estimation process to the corresponding value according to the reason, so that the estimation process is more accurate, the deviation generated by the subsequent statistics and analysis of the tourism data is further reduced, and the accuracy of the tourism data estimation is improved. Therefore, the accuracy of follow-up tourism data estimation is improved.

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 measurement economics analysis models, and discloses a measurement economics analysis model and a measurement analysis method, and the system comprises a data collection and management module which is used for collecting economic data from a plurality of data sources; the model construction and selection module is used for providing various models; the parameter estimation and optimization module estimates model parameters by using an advanced algorithm; the result analysis and visualization module is used for carrying out detailed statistical analysis on an estimation result of the model; and the risk assessment and early warning module is used for assessing data and model risks in measurement analysis. According to the invention, the data acquisition and management module provides a high-quality data basis for other modules and improves the accuracy and reliability of the model, and the model structure and type determined by the model construction and selection module and optimized parameters can present more valuable results in the result analysis and visualization module.

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 present invention provides a method and system for quantifying the degree of influence of construction uncertainty on construction carbon emissions, belonging to the field of carbon emission calculation. To solve the problem that the existing construction carbon emissions are static estimates based on construction organization design and construction drawings, and the data deviation caused by the influence of uncertainty in the construction process is not considered. By collecting theoretical construction consumption data and actual construction consumption data, the two are statistically analyzed according to the type of resource consumption or structural part, and then the difference between the two is made and multiplied by the corresponding carbon emission factor, so as to complete the quantification of the degree of influence of construction uncertainty, perform difference analysis on the quantified data, and give early warning prompts according to the intensity, proportion exceeding the limit, and abnormal fluctuation of the construction uncertainty, so as to help various construction projects quickly quantify the impact of construction uncertainty on construction carbon emissions, and then provide management guidance and decision-making basis for construction management and low-carbon construction.

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.

System and methods are disclosed for a task-based approach to the generation of a project estimation. The systems and method described herein generate design patterns associated with a software development project based on historical information at a task level. Validate the design patterns. Decompose the design patterns into scenarios having a plurality of tasks. Survey the scenarios. Develop a plurality of estimate baselines based on past actual estimates and survey information. Develop an estimation model based on the plurality of estimate baselines; and provide feedback to the historical information of the estimation model based on actual task based performance metrics for use in generating design patterns for future projects.

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.

The invention provides a project development cost prediction method and device based on principal component analysis, and relates to the technical field of data mining. The method comprises the following steps: respectively acquiring numerical values of a plurality of projects under each type of indexes and the total cost of each project; the contribution rate of each principal component is calculated through a principal component analysis method, the cumulative contribution rate of the first k principal components in all the principal components is calculated through the contribution rate of each principal component, the cumulative contribution rate is larger than or equal to a preset contribution rate, and each principal component comprises the product of the mean value of the numerical values of the multiple items under each type of indexes and the corresponding coefficient; k is less than or equal to the number of all types of indexes; selecting a preset number of principal components from the k principal components as target principal components, and constructing a multi-dimensional space pricing model by using each target principal component and the total cost of each project; and predicting the total cost required by the target project based on the multi-dimensional space pricing model. According to the invention, the cost estimation accuracy can be greatly improved.

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.