284 results about "Accounting method" patented technology

The invention discloses a highway full life cycle carbon emission statistical accounting method, and relates to the technical field of carbon emission accounting, and the method comprises the steps: dividing the highway full life cycle into a plurality of stages, and dynamically calibrating the accounting boundary of each stage based on the space-time dimension; setting all types of carbon emission accounting indexes, and collecting multi-modal data corresponding to each stage; establishing a hierarchical computing architecture based on an edge-cloud collaborative technology, checking the carbon emission of each stage, and verifying a carbon emission checking result by using a virtual road model capable of online learning and updating; and drawing a carbon footprint thermodynamic diagram based on a carbon emission accounting result, and displaying a space-time evolution process. According to the invention, the construction, operation and demolition stages of the whole life cycle of the expressway are covered, and the comprehensiveness and systematicness of an accounting result are ensured; a plurality of data sources and collection methods are adopted, and a corresponding accounting method is combined for calculation, so that the accuracy and reliability of an accounting result are ensured, and a scientific basis is provided for low-carbon construction and operation of the expressway.

The invention relates to the technical field of data processing, and discloses a ship enterprise-oriented building and structure carbon footprint fine management and accounting method and a ship enterprise-oriented building and structure carbon footprint fine management and accounting system. The method comprises the steps of establishing a ship enterprise building full life cycle carbon footprint accounting framework, collecting and sorting carbon emission factor data, constructing a matrix mathematical model, developing an accounting tool and performing actual project verification, finally forming a carbon footprint accounting process, a monitoring scheme and an emission reduction strategy, and outputting a management manual and a measure library. And the whole-process carbon emission fine management is realized. According to the invention, on the premise that the calculation accuracy is guaranteed, carbon emission full life cycle management, dynamic monitoring, early warning response and emission reduction decision support are realized.

The invention discloses a multi-source data fusion accounting method for a full-life-cycle carbon footprint, and belongs to the technical field of carbon footprint accounting, and the method specifically comprises the steps: inputting a purchase order number set of a target product, and automatically associating a logistics fuel consumption record, a production process energy consumption log and a supplier indirect emission declaration form according to the purchase order number; constructing a dynamic traceability tree taking a purchase order as a root node, and generating a trunk path through matching of an order material code and a workpiece batch number of a process energy consumption log; when the difference between the logistics real-time energy consumption data and the supplier declaration form exceeds a set threshold value, activating a dispute data branch reconstruction algorithm, and creating parallel branches to temporarily replace dispute data segments while keeping trunk continuity; finally, outputting a full-life-cycle carbon footprint data graph with dispute marks, and reserving original association paths of all data sources; according to the invention, reliable support is provided for accurately tracing the full-life-cycle carbon emission of the product and improving the carbon footprint accounting quality.

The invention relates to the technical field of value accounting, and discloses an ecological system total production value accounting method based on GIS spatial analysis, and the method comprises the steps: carrying out the accounting of regional basic data and satellite image data, and constructing a bidirectional dynamic semantic mapping library corresponding to land change investigation land parcel classification-ecological system type; internet of Things monitoring data and statistical report data are obtained, and a standardized data set is obtained through space-time fusion of spatial interpolation-boundary correction and a sliding window smoothing method; constructing an urban area-typical district double-level accounting index system, and synchronously calculating a real object quantity and a value quantity; a model correction factor is called based on a GIS, indexes are quantified to grid units, a result is obtained through neighborhood analysis, and after parameters are calibrated, a multi-year ecological value trend map is generated in combination with the GIS; and outputting a customized result according to scenes such as ecological compensation, and outputting a final result after the customized result is qualified through three-level quality control verification. According to the method, the requirements of practical affairs such as ecological compensation and EOD projects on accounting precision and practicability can be met.

The invention relates to the technical field of financial accounting and artificial intelligence combination, in particular to an artificial intelligence-based financial data identification and accounting method, which comprises the following steps of: firstly, calculating a fractal dimension by using a multi-level grid splitting technology, and constructing a fractal financial semantic map covering transaction and exchange entities; and performing interference operation by using a quantum mixing aggregator, fusing fractal atlas attributes and subject candidate results to obtain interference scores, and performing symbol rule screening or manual auditing confirmation to generate calibrated subject information. Then, the subject information is used for automatically generating an accounting entry and performing account book archiving, and the whole decision process is recorded under the quantum hash technology; by continuously analyzing archived decision data, the system can adaptively adjust fractal dimension calculation and interference parameters, and precise recognition and efficient accounting of complex financial data are realized.

The invention relates to the technical field of environmental monitoring, and discloses an uncertainty evaluation method based on establishment of a carbon emission monitoring method and an accounting method, and the method comprises the following steps: establishing an uncertainty evaluation model of a coal-fired unit carbon emission monitoring method to quantify the uncertainty of the carbon dioxide emission of the monitoring method; establishing a coal-fired unit carbon emission accounting method uncertainty evaluation model to quantify the uncertainty of the carbon dioxide emission of the accounting method; based on results obtained by the monitoring method uncertainty evaluation model and the accounting method uncertainty evaluation model, carbon emission data quality is analyzed, and improvement measures are put forward. By constructing an uncertainty evaluation model of a monitoring method and an accounting method, various error sources in the whole process of flue gas sampling, analysis, fuel metering, coal quality analysis and the like are comprehensively considered, and a rigorous mathematical method is adopted for synthesis. The quantitative evaluation enables the accuracy of the carbon emission data to have a clear measurement standard.

The invention relates to the technical field of education, and particularly discloses an intelligent accounting teaching method combined with behavior recognition, which comprises the following steps: collecting behavior data of students in an accounting course learning process through a multi-mode sensor deployed in an accounting teaching environment, the behavior data comprises facial expression data, limb movement data, voice interaction data, handwriting writing data and eye gazing trajectory data, a comprehensive feature vector is generated according to a deep learning model, visual features are extracted by using CNN, voice time sequence features are extracted by using RNN, and multi-modal features are fused through an attention mechanism, so that the visual features are extracted, and the visual features are extracted. According to the method, complementary information of different modal data is effectively integrated, and compared with single modal feature extraction, the learning state evaluation accuracy is improved by about 30%, for example, when the understanding degree of a student on a loan accounting method is recognized, the learning state evaluation accuracy is improved by about 30% in combination with handwriting writing fluency and the professional term use frequency in voice interaction, and the learning state evaluation accuracy is improved by about 30%. And the knowledge point mastering degree can be judged more accurately.

A method and system for calculating and optimizing carbon footprint of a product life cycle are disclosed. A graph method is used to account for the carbon emission on the complicated connecting the product life cycle. A well formulate set of equations are used to optimize the process to reduce overall carbon footprint. Unlike the traditional accounting method, in which human beings are needed to understand fully regarding each of the details of the carbon accounting method, the present system uses an assistant AI to compensate for the insufficient knowledge in the carbon accounting.

The invention belongs to but is not limited to the technical field of carbon emission accounting, and particularly relates to a biomass combustion carbon emission accounting method and system based on artificial intelligence, and the method comprises the steps: obtaining the multi-dimensional data of a biomass combustion process through data collection and preprocessing, and extracting key features through the statistical analysis and machine learning technology; and a suitable machine learning model is constructed to predict the carbon emission, and the carbon emission is calculated in real time. Meanwhile, the accounting process is optimized through adaptive learning and a multi-model integration method, and it is ensured that the model can cope with different combustion conditions and complex nonlinear relations. And finally, performing multi-dimensional analysis and verification on an accounting result, continuously optimizing the model through a dynamic feedback mechanism, and providing long-term carbon emission monitoring and trend prediction functions.

The invention relates to the technical field of artificial intelligence and environmental information processing, discloses a carbon emission AI intelligent accounting method and system, and aims to solve the problems of weak data fusion capability, poor accounting real-time performance, insufficient model generalization and lack of self-evolution capability of the system in the prior art. The method comprises the steps that multi-source heterogeneous operation data are collected in real time, standardized management and spatial-temporal feature extraction are carried out, direct, indirect and implicit carbon emissions are calculated through a fusion graph neural network, a time sequence attention network and an accounting cluster of an integrated tree model, and online iterative optimization of model parameters is driven based on external calibration signals. According to the scheme, carbon emission accounting is converted into a high-precision minute-level response dynamic deduction mode, the transparency and traceability of accounting are remarkably improved, continuous self-adaptive optimization in a large-scale scene is supported, and reliable data support is provided for precise carbon reduction.

The invention relates to the technical field of project accounting, in particular to a small and medium-sized enterprise single-project accounting method based on a business financial minimum data unit, which comprises the following steps of: matching collection and fulfillment nodes, distributing account affiliation, marking change of difference between income and expenditure directions, generating a cash flow recursion path, and uniformly writing in details of a total classification account to obtain accounting chain structure data. According to the method, time matching and amount identification of project collection information are realized by mapping contract node amounts and actual collection data in sequence, a node amount association chain with clear affiliation is constructed in combination with a mode of matching receivable nodes with account amounts step by step, and a linkage judgment mechanism of voucher numbers and revenue and expenditure identification is matched; according to the method, the income and expenditure directions of each stage of the project are distinguished, the fund change trajectory is reflected by sequence number difference operation, the directions of positive and negative items of cash flow are clear, and the response speed and accuracy of single-project accounting in dynamic fund tracking, cost control and accounting concentration are effectively improved.

The invention relates to the technical field of urban traffic management and carbon emission reduction accounting, and provides a bus travel carbon emission reduction accounting method fused with Beidou spatio-temporal data, which comprises the following steps: acquiring spatio-temporal trajectory data based on a Beidou satellite navigation system, and constructing a passenger-trajectory-station three-dimensional correlation model for passenger flow analysis; constructing a passenger transfer analysis system based on the passenger flow analysis result; constructing a dynamic'perception-prediction-optimization 'dynamic scheduling optimization system for passenger flow detail analysis on the basis of space-time trajectory data and a reinforcement learning algorithm; and constructing a mileage-frequency distribution model and a station efficiency evaluation model based on the spatio-temporal trajectory data, respectively generating a trajectory matching optimization strategy and a differentiated station optimization scheme, and realizing adaptive optimization of the public transportation system under dynamic demand change. Compared with a traditional static data dependence method, the method achieves the dynamic and fine-grained monitoring of the operation process of the public transportation system, and effectively improves the timeliness and integrity of data.

The invention provides a carbon emission accounting method, system, equipment and medium in a port and aviation container transportation process, and belongs to the technical field of logistics carbon management and intelligent algorithm crossing. The method comprises the following steps: collecting transportation and energy consumption data of roads, waterways, railways and logistics storage links in a classified manner, and preprocessing the transportation and energy consumption data to form a standardized data set; a carbon emission factor parameter library is created in combination with industrial standards, different transportation modes and cargo types, and dynamic updating is performed through a machine learning algorithm. And special accounting sub-models are constructed for different transportation modes, and carbon emission accounting is carried out by using corresponding formulas and parameters. And inputting the standardized data into the nuclear operator model, calculating the carbon emission and screening an optimal path. And model parameters are calibrated by using historical data to ensure accuracy. And finally, collecting data in real time, inputting the data into the accounting sub-model, generating a decision support report comprising implementation steps, resource demands and expected effects, and assisting in realizing low-carbon and efficient management of the transportation process.

The invention relates to a power fee accounting method based on intelligent management, and the method comprises the following steps: S1, obtaining multi-source heterogeneous data, carrying out the preprocessing, and carrying out the collection, data standardization, time calibration and automatic tagging of the multi-source heterogeneous data, and obtaining a standard structured data stream; s2, constructing a dynamic accounting rule data set based on the standard structured data stream and transaction data, market rules, contract terms, regions and type price standards; s3, constructing an intelligent prediction model based on LSTM and ProphetAI models, automatically detecting reasonability and correcting a prediction interval according to the dynamic accounting rule data set, and obtaining a pre-accounting result set; s4, according to the pre-checking result set, in combination with the price standard and the amount fee strategy, configuring subsidy and refunding policies and parameter processing, automatically matching a settlement unit and a settlement rule, and flexibly applying different checking templates according to distributed, direct-purchase and non-direct-purchase power plants to obtain a checking intermediate table; and S5, generating a final settlement packet according to the accounting intermediate table and the user configuration parameters.

The invention provides a blue carbon market adaptive accounting method based on multi-source data and Bayesian updating, and belongs to the technical field of natural resource planning and ecological management. The method comprises the following steps: firstly, constructing a standardized multi-source fusion data set through a systematic process, and then preprocessing collected data to generate a standardized blue carbon multi-source fusion data set; then, through a Bayesian-based carbon reserve estimation model, outputting a monitoring point carbon reserve prior value, fusing a monitoring point carbon reserve mean value with a spatial prior value, and updating monitoring point carbon reserve distribution; and finally, constructing a carbon credit risk index system, calculating risk indexes of the plot layer and the region layer, updating a plot layer carbon reserve mean value by using the updated monitoring point carbon reserve distribution, and generating a blue carbon project reference transaction price according to the carbon reserve mean value and the risk indexes. According to the invention, a full-chain blue carbon intelligent accounting system is constructed, and interdisciplinary fusion of an ecological model, deep learning and a carbon market mechanism is realized.

The invention provides a carbon footprint accounting method and device based on a knowledge graph, and the method comprises the steps: determining a to-be-accounting object, and obtaining the carbon footprint data corresponding to the to-be-accounting object; constructing a knowledge graph according to the carbon footprint data; based on the knowledge graph, carbon footprint accounting is conducted on the to-be-accounting object, and a carbon footprint accounting result corresponding to the to-be-accounting object is obtained.According to the method, the knowledge graph is constructed through the carbon footprint data, integration of the multi-source heterogeneous carbon footprint data and accurate expression of the carbon emission relation are achieved, and based on the knowledge graph, the carbon footprint accounting result of the to-be-accounting object is obtained. And obtaining the carbon footprint accounting result corresponding to the to-be-accounted object. The carbon footprint accounting result corresponding to the to-be-accounted object can be obtained more accurately and efficiently.

The invention relates to the technical field of carbon emission, in particular to an on-chain enterprise carbon emission accounting method and system. The method comprises the following steps: acquiring energy consumption, process flow and supply chain collaborative data of an enterprise in links of raw material acquisition, production processing, logistics transportation, equipment operation and recovery processing through Internet of Things equipment, and generating a carbon emission data set; based on a life cycle evaluation theory, boundaries of direct emission, indirect energy emission and supply chain associated emission are divided, and enterprise-level, product-level and supply chain-level carbon emission accounting models are constructed. A machine learning algorithm is utilized to analyze production fluctuation data in real time, carbon emission factor weights and accounting boundary parameters are dynamically adjusted, and an accounting result is optimized. And outputting a result to a green purchase decision-making system, a carbon asset management system and a supply chain collaboration platform. The system integrates industrial Internet of Things equipment, block chain nodes and enterprise resource planning system interfaces, collects and verifies full-link data in real time, solves the problem of data collection, and improves the accounting reliability.

The invention discloses a carbon flow monitoring and accounting method based on the Internet of Things. The method specifically comprises the following steps: S1, collecting power flow information of a power system; s2, performing flow calculation on the power network to obtain an active power flow matrix F of the whole power network; s3, performing hierarchical iterative calculation on the power grid carbon flow density, and gradually obtaining carbon flow data of the whole power grid; s4, arranging the carbon flow data to obtain a carbon flow matrix C, and providing a final visual result; s5, collecting carbon emission data; s6, establishing a carbon flow neural network model; s7, training the carbon flow neural network model; and S8, checking the carbon emission of the whole system by using the carbon flow neural network model. According to the invention, an Internet of Things data acquisition technology and a data analysis visualization technology are mainly utilized, the flow path of the carbon flow in the whole power network is visually displayed for a power system manager, and low carbon and greenization of the whole system are helped to be realized.

The invention discloses a forestry carbon sink dynamic accounting method, a forestry carbon sink dynamic accounting device, forestry carbon sink dynamic accounting equipment, a storage medium and a program product, and relates to the technical field of forestry carbon sink accounting. And further determining actual contents of key accounting factors of the forestry carbon sink accounting project based on the project characteristics, and finally performing forestry carbon sink accounting according to an accounting scheme obtained by adopting the actual contents of the key accounting factors. In this way, compared with the situation that it is difficult to accurately and comprehensively determine the accounting core factors of different accounting periods through manual maintenance, the project features of the forestry carbon sink accounting project of the current accounting period are obtained through recognition, and the actual content of the comprehensive and accurate key accounting factors is determined; therefore, accurate forestry carbon sink accounting is carried out according to the accounting scheme obtained by adopting the actual content of the key accounting factors.

The invention relates to the technical field of regional carbon emission quantitative management, in particular to an accounting method, system, equipment and medium for regional carbon emission statistics, and the method comprises the steps: collecting carbon emission accounting basic data, and building a dynamically updated historical database; performing prediction and trend analysis on the carbon emission through a composite model fusing regression analysis and time sequence analysis on the basis of a historical database; monitoring the change of an energy structure, and dynamically adjusting a carbon emission factor and a weight parameter of the energy structure; and updating the composite model based on the dynamically adjusted weight parameters, and generating an optimized regional carbon emission statistics and prediction result. The method has the beneficial effects that the accuracy and reliability of the input data are ensured by collecting the carbon emission accounting basic data and performing strict data preprocessing. Regional electricity utilization carbon emission is analyzed by utilizing ridge regression and a time sequence algorithm, the prediction accuracy is improved, and a scientific basis is provided for a local government to optimize an energy structure and promote green and low-carbon development.

The invention relates to the technical field of drainage and waterlogging prevention, and discloses an urban low-lying road drainage and waterlogging prevention capability accounting method, device and equipment, and the method comprises the steps: obtaining and quantifying road features, and constructing a road feature parameter library; then, session rainfall, road ponding data and the parameter library are associated to form a road ponding scene parameter library; taking the submerged area or the ponding depth as a target, screening characteristic parameters from the scene library, and training a prediction model; and finally predicting the ponding index of the target road through the model by using the actual characteristic parameters of the target road. The method solves the problems that a traditional method is single in data dimension and depends on experience, prediction targets can be selected according to needs to adapt to different scenes, feature screening and model training are combined, factors such as terrain, rainfall and drainage efficiency are considered, dependence on complex data and professional software is reduced, accounting is more efficient, the result better fits the reality, and the method is suitable for large-scale popularization and application. The method can quickly complete road ponding index accounting, and provides a reliable basis for ponding risk prejudgment.

The present invention automates, via smart contracts in a Distributed Ledger, the negotiation between a buyer and seller for the purchase / sale of a resource or asset in which: the buyer offers purchase terms, and the seller determines if the terms can be fulfilled at a satisfactory price. If the parties cannot negotiate mutually acceptable transaction terms, then the process terminates. If the negotiation succeeds, then the present invention automates transaction recording through seller's delivery and buyer's remuneration, completing the transaction. Once the purchase / sale transaction is complete, the operator executes smart contracts to record the accounting treatment for the asset or resource in multiple methods of accounting. Rather than posting accounting entries to legacy databases, the present invention posts each journal entry's debits and credits to the distributed ledger as discrete blocks, which can be: summarized in historical or prospective financial reports; used in mathematical computations; or, satisfy conditional statement hypotheses.

The invention provides a carbon emission source and boundary identification and accounting method, system and device and a medium, and belongs to the technical field of carbon emission management. The method comprises the following steps: collecting enterprise organization related information, including an organization structure, a business range, a financial statement and production process flow data; performing text formatting processing on the related information of the enterprise organization, inputting the information into a pre-training generation type large model based on a Transform architecture for analysis, and identifying carbon boundary and carbon emission source information of the enterprise organization; constructing an accounting method library containing a plurality of carbon emission source accounting methods, and analyzing and inputting emission source types, industry ranges, accounting formulas and required data suitable for each accounting method; according to the identified carbon emission source information, matching and screening are carried out by synthesizing semantics and rules, and an applicable accounting method is matched in an accounting method library; and issuing an identification result and a matched accounting method, and displaying the carbon emission source information and the accounting method through a visual interface.

The invention discloses a user income accounting method based on CNN-LSTM potential evaluation and a related device, and belongs to the technical field of prediction and electric power spot market operation strategies, and the method comprises the following steps: determining parameters required by a scene, processing existing data, and constructing an input data set; constructing a CNN-LSTM model, and predicting the upper and lower limits of the load regulation potential corresponding to the time period; layering the load regulation potential predicted by the model as a corresponding capacity, and calculating the corresponding confidence of each interval layer; and constructing a response capacity hierarchical accounting model, and respectively calculating the total income E corresponding to the report capacity of each interval according to the confidence of each interval and a reward and punishment mechanism. According to the user income accounting method based on CNN-LSTM potential evaluation, the response capacity can be reported more reasonably, and a more effective market strategy can be made, so that the optimization of the income is realized.

The invention discloses a clothing production effective labor hour accounting method and system based on the Internet of Things, and the method comprises the steps: obtaining the production assignment task data of a current sewing machine station, and judging whether the current sewing machine station is an effective labor station or not according to the production assignment task data; if yes, continuously monitoring and collecting a bottom-layer operation parameter sequence of the current sewing machine station through Internet of Things sensing equipment, and performing effective labor state judgment on the bottom-layer operation parameter sequence based on a predefined effective labor hour judgment logic rule; recording the duration of entering the effective working state each time by using a high-precision timer, and carrying out accumulation to generate effective working hour structured data; and generating a visual report and analysis data for performance management, production efficiency analysis and process optimization based on the effective man-hour structured data. Automatic accounting can be realized completely based on real operation data of the equipment, personal errors and faking are avoided, and justice, credibility, objectivity and accuracy of the data are ensured.

The invention provides a pollution source VOCs emission accounting method and system based on electric power data analysis, and relates to the technical field of city management, and the pollution source VOCs emission accounting method comprises the following steps: S1, obtaining a basic data set of an enterprise in a grid based on a grid matching strategy; the basic data set comprises release time, and VOCs monitoring data, meteorological data and electric power data collected within a moment T; s2, mining data features of the release time, the VOCs monitoring data, the meteorological data and the electric power data, and integrating the data features into the basic data set to obtain a feature data set of an enterprise in the grid; and S3, based on a model fusion strategy of a linear regression model, a Light GBM model and a neural network model, estimating the VOCs at the moment T according to the feature data set to obtain VOCs estimation data at the moment T.

The invention discloses a casting part multi-mode intelligent cost accounting method and system, and relates to the technical field of casting engineering and intelligent cost accounting. The casting part multi-mode intelligent cost accounting method comprises the steps that process information in casting engineering is extracted and processed in a structured mode, and missing information of a plane drawing is automatically supplemented; matching a target casting process route and key parameters based on the process information subjected to the structured processing; and calculating the basic total cost according to the target casting process route, and correcting the basic total cost in combination with the historical data deviation, the real-time market data and the order variables to obtain the corrected total cost. Unified automatic analysis of the plane drawing and the three-dimensional drawing is achieved, the problem that information of the plane drawing is incomplete is solved through image recognition and rule completion, and the limitation that only a single drawing type is supported is broken through; the casting process constraint extracted from the three-dimensional drawing is directly used as a core parameter of process matching, and the plane drawing indirectly maps process requirements through feature recognition, so that quantitative association of drawing information-process parameter-cost is realized.

The invention discloses a federated learning time series data analysis method based on shuffling differential privacy, which comprises the following steps that: a central server initializes global model parameters and distributes an initial model to all federated learning clients; each client uses a local time sequence data training model, calculates a gradient, then cuts the gradient, and adds Laplacian noise; the client uploads the disturbed gradients to a shuffling device, and the shuffling device allocates random delay time to each gradient and disrupts an uploading sequence to realize privacy amplification; the central server aggregates the gradients processed by the shuffling device to generate a global gradient, and broadcasts the updated model parameters to the client; repeating the above steps to perform iterative training, and tracking privacy budget consumption in real time through a privacy accounting method until a preset privacy budget threshold value or model convergence is reached; according to the invention, privacy amplification is realized, and noise injection is reduced.

The invention provides a ceramic industry carbon footprint accounting method and system based on PINN and multi-level process path modeling, a medium and a processor, and the method comprises the steps: S1, constructing a level process path network based on a process node and a carbon factor interface according to a ceramic processing process; s2, analyzing the hierarchical process path network, and determining an application hierarchy of a PINN model; s3, constructing a PINN model corresponding to the application hierarchy and training the PINN model; s4, fusing the trained PINN model and the hierarchical path network, and performing carbon emission prediction; and S5, real-time on-line monitoring of actual carbon emission data is carried out, and comparison evaluation is carried out on the actual carbon emission data and a prediction result so as to correct the prediction precision of the PINN model. The method can comprehensively consider the thermodynamic mechanism and the data-driven prediction capability, has the advantages of physical consistency, strong generalization capability, online deployment and the like, and effectively solves the problems of strong static property, poor physical consistency, weak regional adaptability and the like of the existing accounting model.