13 results about "Incremental costs" patented technology

The invention belongs to the technical field of project management and intelligent supervision, and discloses a project cost accounting management method and system for project supervision, and the method comprises the steps: inputting a preprocessing data packet into an edge calculation node, carrying out the dynamic data cleaning through employing a noise filtering matrix algorithm, and outputting a structured data set with a quality label; on the basis of the structured data set with the quality label, scanning a construction part through augmented reality glasses, comparing actual coordinates with building information model design coordinates in real time, and when a deviation accumulated value exceeds an early warning threshold value, generating an acceptance evidence chain which cannot be tampered; and accumulating the incremental cost of the plurality of standardized visa file packages, carrying out time sequence analysis through a long-short term memory prediction model, and outputting a project cost analysis report with a risk level. The problem of loss of acceptance evidence chains in traditional cost accounting is solved, and the strong dependence of a conventional prediction model on data distribution is broken through.

The invention belongs to the technical field of environmental risk assessment, and particularly discloses a BIM-based fabricated steel structure assembly scheme comparison and selection method and system, and the method comprises the steps: building a three-dimensional building model based on BIM software, and extracting component information and GIS data; establishing national and local standard libraries, matching applicable standards through building positioning information, and generating parameterized assembly rules; generating a plurality of assembly type combination schemes according to rules and component logic, and interactively binding with the BIM model; calculating an assembly rate and a standard score of each scheme, and screening candidate schemes meeting structural safety and a cost threshold value; and constructing an incremental cost library, completing cost difference analysis of the candidate schemes, and outputting an optimal assembly type steel structure combination scheme. And data driving and automatic comparison and selection in the whole process are supported, the method can be applied to prefabricated building scheme design and optimization links, and the design efficiency and the scheme economy are improved.

The present application relates to the technical field of intelligent manufacturing and production scheduling, and particularly relates to a garment multi-process digital twin monitoring method, which comprises the following steps: establishing a process digital twin by using a colored time-delay Petri network and an event dictionary; hierarchically updating a processing time distribution and a line change cost matrix online; obtaining a coupling matrix and calculating a dual price vector by using a regularized optimal transport, and quantifying a work-in-process capacity upper limit as a work-in-process quota; calling a Koopman operator driven counterfactual generator to evaluate an incremental cost and generate a release sequence by optimal sorting within a rolling prediction window; locking and issuing a process path according to the quota, implementing a reversible fine-tuning based on a deviation, and triggering a withdrawal and path diversion according to a topological structure abstract. The present application reduces work-in-process peak value and line change loss, and improves production capacity utilization and stability of on-time delivery.

The invention relates to the technical field of intelligent manufacturing and production scheduling, in particular to a clothing multi-process digital twinning monitoring method, which comprises the following steps of: establishing process digital twinning by using a colored time delay Petri network and an event dictionary; the processing time distribution and the line changing cost matrix are updated through layered online assimilation; a coupling matrix is obtained through regularization optimal transmission, a dual price vector is calculated, and the upper limit of the capacity of the work-in-process is quantified into the quota of the work-in-process; an anti-fact generator driven by a Koopman operator is called in the rolling prediction window to evaluate increment cost and preferentially sort to generate a release sequence; and locking and issuing the process path according to the quota, implementing reversible fine adjustment based on the deviation, and triggering withdrawal and path change according to the topological structure abstract. The product peak value and the line change loss are reduced, and the stability of capacity utilization and on-time delivery is improved.

This invention belongs to the technical fields of engineering management and intelligent supervision, and discloses a project cost accounting management method and system for engineering supervision. The method includes inputting preprocessed data packets into edge computing nodes, using a noise filtering matrix algorithm for dynamic data cleaning, and outputting a structured data set with quality labels. Based on the structured data set with quality labels, the construction site is scanned using augmented reality glasses, and the actual coordinates are compared with the design coordinates of the building information model in real time. When the accumulated deviation exceeds the warning threshold, an unalterable acceptance evidence chain is generated. The incremental costs of multiple standardized visa document packages are accumulated, and time series analysis is performed using a long-short-term memory prediction model to output a project cost analysis report with risk levels. This method solves the problem of the lack of acceptance evidence chain in traditional cost accounting and overcomes the strong dependence of conventional prediction models on data distribution.

An online system computes an incremental cost prediction for each of a set of user-treatment pairs to select a set of treatments to apply to users to satisfy a predicted interaction gap. The online system generates a set of candidate user-treatment pairs that each include user data for a user of the online system and treatment data for a treatment of a set of treatments. The online system computes an incremental interaction prediction and a treatment cost prediction for each of the candidate user-treatment pairs by applying an incremental interaction model to the user data and the treatment data in each user-treatment pair. The online system computes incremental cost predictions for each of the user-treatment pairs based on the computed incremental interaction predictions and treatment cost predictions and selects which users to apply treatments to and which treatments to apply to those users based on the incremental cost predictions.

This invention discloses a near-zero energy building design optimization method for service areas based on the NSGA-II algorithm, belonging to the field of building design technology. The method includes: selecting a set of near-zero energy building technologies based on the heat distribution and environmental factors of the service area location; establishing a benchmark building and a building energy consumption analysis model using candidate technologies; using the benchmark building and the building energy consumption analysis model using candidate technologies to obtain energy consumption simulation results, calculating the building's comprehensive energy consumption and incremental cost; based on the comprehensive energy consumption and incremental cost, using the NSGA-II genetic algorithm model to form feasible solutions, and generating multi-dimensional indicators based on the feasible solutions; selecting the optimal near-zero energy building design optimization scheme for the service area through the multi-dimensional indicators. This method utilizes the efficient multi-objective optimization capability of the NSGA-II algorithm to comprehensively analyze various influencing factors and provide energy utilization efficiency for service area buildings in actual operation.

The invention belongs to the field of power system dispatching automation, and discloses a new energy consumption cost quantification method and system based on joint clearing, and the method forms a direct comparison reference through the construction of double scenes including a new energy scene and a virtual coal-fired unit replacement scene, and determines the incremental cost of new energy consumption. The system cost is defined as the electric energy cost, the standby cost and the frequency modulation cost, which is more suitable for the actual operation scene. The operation constraint and cost characteristics of a conventional unit are simulated through the virtual coal-fired unit, and it is ensured that a replacement scene and an original scene have comparability in the aspects of power output, system balance and the like. And finally, calculating the comprehensive cost of new energy consumption by comparing the combined clearing cost of the power market in the scene with the new energy and the scene without the new energy. The comprehensive cost not only can effectively reflect the power production cost saved by new energy grid connection instead of coal-fired unit power generation, but also can reflect the adjustment cost increase of standby, frequency modulation and other systems caused by new energy output volatility.

An online system computes an incremental cost prediction for each of a set of user-treatment pairs to select a set of treatments to apply to users to satisfy a predicted interaction gap. The online system generates a set of candidate user-treatment pairs that each include user data for a user of the online system and treatment data for a treatment of a set of treatments. The online system computes an incremental interaction prediction and a treatment cost prediction for each of the candidate user-treatment pairs by applying an incremental interaction model to the user data and the treatment data in each user-treatment pair. The online system computes incremental cost predictions for each of the user-treatment pairs based on the computed incremental interaction predictions and treatment cost predictions and selects which users to apply treatments to and which treatments to apply to those users based on the incremental cost predictions.

The application relates to the technical field of architectural design, and provides a three-star green building cost optimization method, device, equipment and medium, which can construct a full-life cycle incremental cost prediction model of a green scheme based on the interaction between technical measures, so as to accurately perform building cost prediction; a plurality of to-be-optimized technical measures are selected from each technical measure included in the green scheme through cost sensitivity analysis, so as to lock the technical measures with high conversion rates for optimization; a target function is constructed according to annual total energy consumption, annual carbon emission and the full-life cycle incremental cost prediction model, and a constraint condition is constructed according to a three-star green building scoring rule, so that multiple optimization targets can be considered; a Pareto front solution set of the optimization model is solved based on an orthogonal table, so that the solving efficiency can be improved; and a target scheme is selected from a plurality of candidate schemes according to a value coefficient and a dynamic benefit balance point, so that an optimal three-star green building cost optimization scheme can be reasonably selected.

The invention discloses a BIM project amount and quota matching cost integrated calculation method and system, and belongs to the technical field of cost calculation. The method comprises the following steps: establishing an integrated database integrating list quota, market price and unit carbon emission factors, establishing an intelligent matching rule of BIM component characteristic parameters and list items, generating a dynamic mapping relation, extracting component engineering quantity, and associating and integrating unit price and carbon emission factors; by introducing external parameters such as a carbon transaction price and a green building material standard, incremental costs such as a carbon transaction cost, a green premium and an energy-saving profit net present value are accurately calculated; and finally generating a comprehensive cost prediction report integrating the conventional construction and installation cost and the incremental cost. According to the method, automatic and integrated prediction of the cost and the carbon emission is realized, the calculation efficiency and the decision support capability are improved, and a key technical support is provided for economic evaluation of green buildings.

The invention discloses a near-zero-carbon residential building multi-objective optimization method and system, and relates to the field of building energy saving and optimization design, and the method comprises the steps: setting a design variable parameter, an optimization objective and a critical threshold, and constructing a multi-objective optimization model based on an NSGA-II algorithm; establishing a building three-dimensional model and carrying out energy consumption simulation to obtain a calculation result sample set containing performance indexes; screening up-to-standard schemes and calculating scores of three dimensions of incremental cost, technical effect perceptibility and technical integration maturity; evaluation indexes with consistent directions are obtained through normalization processing based on percentile, and a comprehensive evaluation index is calculated in combination with dynamic weight configuration; and finally, outputting an optimal scheme. According to the method, the problem that the cost is increased sharply due to traditional single-dimensional optimization is solved, multi-target collaborative optimization under the condition of meeting near-zero carbon performance constraints is achieved, and the method has important practical value and popularization significance.

The present invention discloses a method for calculating the incremental cost of a distribution network node based on conditional value at risk, comprising the following steps: (1) modeling the extreme value of line flow. The tail distribution of the line flow is fitted using the super-threshold method to obtain an analytical expression for the expected power outage loss of users based on the generalized Pareto distribution; (2) determining the initial investment time based on the expected future load loss, and triggering investment when the expected user power outage loss is equal to the future investment cost limit; (3) calculating the new line investment years after the node injects (or flows out) power; (4) calculating the net present value change caused by the node injecting (or flowing out) power, and finally obtaining the long-term incremental cost of the node from the annual incremental cost. The present invention can reflect the impact of the user power outage loss risk on the power grid investment by considering the conditional value at risk through the incremental cost calculation method of the distribution network node, can significantly delay the investment time of the power grid components, and better reflect the investment strategy of the power grid components when the power flow exceeds the limit risk.