204 results about "Accounting method" patented technology

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 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 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 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 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 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 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.

The invention discloses a carbon emission dynamic accounting method and system. The method comprises the following steps: collecting production equipment direct emission, logistics carbon emission, social media / satellite remote sensing and other abnormal event data; extracting unit yield carbon intensity and supply chain path sensitivity through principal component analysis; constructing a QUBO model and solving an optimal transportation path by using quantum annealing; training a prediction model in combination with the sudden emission risk index to output a carbon emission value; dynamically updating an emission factor library according to the cleanliness of the power grid, and accelerating generation of a confidence interval by adopting a quantum random number generator; and when the predicted value exceeds the threshold value and the lower limit of the confidence interval is higher than the threshold value, triggering carbon capture, carbon credit purchase or production regulation compensation according to the priority. The system correspondingly comprises a multi-mode acquisition module, a calculation optimization module, a dynamic accounting module and a carbon compensation module. Full-chain real-time carbon tracking and intelligent compensation are achieved, the problems of traditional accounting data isolation and compensation lag are solved, and the industrial carbon management accuracy is improved.

The invention relates to the technical field of engineering cost tracing accounting, and discloses an engineering financial cost automatic accounting method based on fund chain tracing. The method includes receiving a project-related original financial voucher stream, and generating a standardized fund transaction sequence through structured deconstruction and semantic standardization processing. And according to a preset rule map, the sequence is associated and aggregated into a multi-level fund flow network with a hierarchical relationship, and the edge attribute of the multi-level fund flow network comprises a flow amount and a cost subject direction. On the network, deep mining and propagation tracing from a tail end cost consumption node to a source fund distribution node are executed, and a complete cost influence link set is identified. And performing dynamic cost allocation and re-accounting based on the link set, generating a traceability accounting report for each cost subject, and quantifying the contribution degree of different capital sources to the final cost. According to the method, cost accounting is improved from static subject collection to dynamic tracing along an actual path, and a complete fund context formed by cost is revealed.

The invention discloses a consumer goods carbon footprint accounting method, system and device based on a full life cycle and a readable storage medium thereof, and relates to the technical field of carbon footprint accounting, and the method comprises the steps: collecting consumer goods production process activity data, carrying out the cycle stage division to obtain corresponding carbon emission factor data, and carrying out the calculation of the carbon emission factor data; carbon emission stage intensity values of different periods are analyzed, contribution proportions of period stages are calculated, an inter-stage data flow matrix is defined, consistency verification is carried out based on the inter-stage data flow matrix, if verification is not consistent, carbon emission intensity differences are calculated, and contribution proportions of different activities are sequentially checked. According to the method, the nonlinear relation between coupling points and the whole system is revealed through inter-stage data flow matrix balance analysis, an efficient collaborative emission reduction path is established through sorting of key coupling point sets, and the key coupling point sets are finally formed based on active points with high contribution rates.

The invention relates to a water supply network carbon emission real-time accounting method and system based on hydraulic power-energy consumption dynamic coupling. The invention relates to the technical field of urban water affair engineering and carbon neutralization, and the method comprises the steps: collecting hydraulic data, equipment energy consumption data and regional power grid data of a water supply network through a multi-source sensing layer, and carrying out the time alignment and data cleaning; a hydraulic power-energy consumption digital twinborn model is constructed, and the dynamic efficiency of the pump set is inversed in real time; predicting a real-time carbon emission factor of the regional power grid based on a deep learning model; establishing a virtual carbon flow conduction model based on a graph neural network or a topological structure, and carrying out dynamic tracking and calculation among pipe network nodes by taking the carbon emission intensity as a virtual substance; calculating a carbon leakage index; and finally, generating a pipe network carbon thermodynamic diagram and feeding back an optimization scheduling instruction. According to the method, the problems of factor staticization, low temporal-spatial resolution and incapability of stripping invalid carbon emission of a traditional accounting method are solved.

The invention relates to the technical field of building engineering construction management of the Internet of Things, and provides a multi-modal data fusion-based reinforcing steel bar loss rate dynamic accounting method, which comprises the following steps of: acquiring multi-modal original data, serializing the multi-modal original data into structured entries, identifying corresponding points of video frames and weighing events, selecting the corresponding points as calibration anchor points, and calculating the loss rate of reinforcing steel bars according to the calibration anchor points. The timestamps of all the devices are mapped to a unified timeline through multi-point fitting; splitting according to a blanking rule to form a consumption baseline of component granularity, carrying out quantitative scoring on candidate components, screening accounting units, and obtaining a residual error by solving the difference between the actual consumption amount and the consumption baseline; searching multi-modal evidences in a corresponding time window for the residual exceeding the tolerance, calculating the effectiveness score of each evidence, defining an evidence support weight matrix for each candidate attribution category, multiplying and summing to obtain a candidate category confidence coefficient, and automatically attributing according to the confidence coefficient; and summarizing attribution statistical data indexes according to process dimensions, and checking and analyzing the indexes and historical baselines to identify anomalies.

The application belongs to the technical field of big data calculation, and particularly relates to a top-down urban carbon emission accounting method and system. The top-down urban carbon emission accounting method comprises the following steps: S1, gridizing map data to obtain carbon dioxide column concentration molar concentration data corresponding to each grid; S2, obtaining a carbon dioxide concentration difference between an accounting area and a surrounding area of the accounting area according to the carbon dioxide column concentration molar concentration data; S3, obtaining carbon dioxide concentration data of the accounting area according to the carbon dioxide concentration difference; S4, obtaining a carbon dioxide emission amount of the accounting area according to the carbon dioxide concentration data and a volume of the accounting area; and S5, obtaining a carbon emission amount of the accounting area according to the carbon dioxide emission amount. The top-down emission accounting method can avoid the problem of statistical inaccuracy in the traditional layer-by-layer reporting of carbon emissions by various industries.

The invention discloses a carbon emission accounting method and system based on big data and a medium, and belongs to the field of carbon emission monitoring, and the method comprises the steps: transmitting collected multi-source data of carbon emission to an edge node, and transmitting the data to a cloud; the edge node arranges the multi-source data, divides the multi-source data into real-time data streams and near-real-time data according to a data form, processes the real-time data streams and the near-real-time data through a space-time adaptive weighted fusion algorithm of the edge node to obtain a multi-source fusion data matrix, and sends the multi-source fusion data matrix to the cloud; and the cloud receives the sent multi-source data, constructs a multi-source database according to the labels of the energy domain, the production domain and the environment domain, extracts data related to carbon emission from the multi-source database after receiving a multi-source fusion data matrix sent by the edge node, and calculates the final carbon emission through a carbon emission accounting algorithm. The real-time performance and the analysis depth of data processing are improved.

This application relates to artificial intelligence technology and provides an accounting processing method, apparatus, computer device, and storage medium, comprising: acquiring a first accounting dataset and a second accounting dataset; matching first accounting data in the first accounting dataset and second accounting data in the second accounting dataset to obtain a target accounting dataset; determining the target language corresponding to each target accounting data in the target accounting dataset and the accounting subject corresponding to the target language; determining the accounting behavior corresponding to the accounting subject; determining the part-of-speech information of the accounting subject and the accounting behavior; and combining the accounting subject and the accounting behavior according to the part-of-speech information in a preset part-of-speech concatenation format to obtain a target accounting language. This application can improve the speed of accounting language determination and promote the rapid development of smart cities.

The application discloses an intelligent accounting method for industrial water consumption, and relates to the technical field of industrial water consumption monitoring and intelligent accounting, and comprises the following steps: step one: receiving and analyzing water consumption accounting requirements, simultaneously acquiring historical data and real-time data from a historical data warehouse and a real-time data acquisition system, respectively, pre-processing, and generating a pre-processed data set. The intelligent accounting method for industrial water consumption realizes real-time self-adaptive adjustment of time-varying factors in industrial water consumption accounting by adopting multi-level data fusion, an improved deep learning network, data sliding window online learning, feedback closed-loop control and a hierarchical incremental updating strategy, significantly improves the prediction accuracy and system response speed of nonlinear water consumption behavior, and thus effectively overcomes the deficiency of static offline training of an accounting model in the prior art.

The invention discloses a business and financial integrated financial accounting method and device based on a rule engine, and relates to the technical field of financial accounting. The method comprises the steps that service data from a service system are received, and the service data are associated with specific source data and receipt types; based on the values of the influence factors contained in the business data, determining a target accounting book of the business data according to an accounting rule; based on values of influence factors contained in the business data, determining accounting subjects of the business data according to the classification definition and a subject comparison table; according to a conversion template corresponding to the target accounting book and the bill type, combining the field value of the business data with the accounting subject to generate a real-time voucher; and storing the real-time voucher as an accounting voucher under the target accounting book.

We provide an accounting system that centrally manages household accounts and business accounting. [Solution] The accounting system includes a management module that selectively registers multiple detail-level account items as either household ledger or business account items to generate journal entry data, registers the journal entry data in a database based on double-entry bookkeeping, and centrally manages household ledger and business account items using double-entry bookkeeping. The accounting system further includes a transaction information recognition module that analyzes character information or codes contained in supporting document images to recognize transaction information, and a journal entry proposal module that analyzes the transaction information obtained from the transaction information recognition module and proposes multiple detail-level account items as either household ledger or business account items, and the management module selectively registers the multiple detail-level account items proposed by the journal entry proposal module as either household ledger or business account items.

A carbon footprint dynamic accounting method based on a graph neural network and long-distance dependence is provided, a multi-level carbon footprint accounting heterogeneous graph is constructed; a relational graph convolutional neural network model RGCN is used for local aggregation of subdivided links to generate enhanced total link features; the total link feature sequence is input into a transformer encoder, long-distance dependence is captured through a multi-head self-attention mechanism, and globally optimized total link features are output; a multi-level path prediction model (RGCN + transformer encoder + link prediction decoder) is jointly trained to capture potential inter-link relationships for expanding the multi-level carbon footprint accounting heterogeneous graph; and local parameter adjustment or incremental learning with graph structure updating is used for dynamic adaptation of the model. The present application provides a method capable of automatically reasoning and expanding carbon footprint accounting paths, and is used for optimizing carbon footprint accounting precision.

The invention relates to the technical field of financial accounting and benefit analysis, and particularly provides a product-based benefit accounting method and device, and the method comprises the following steps: S1, a multi-source data fusion engine; s2, a rule configuration management center; and S3, performing accounting execution and monitoring. Compared with the prior art, the accounting efficiency and accuracy can be improved, and an efficient and accurate product benefit accounting solution is provided for enterprises such as communication operators.

The invention relates to a low-carbon park optimal scheduling method based on dynamic carbon flow tracking, and the method comprises the steps: constructing and describing a park integrated energy system multi-energy flow coupling model, and building a dynamic carbon flow calculation model based on a dynamic carbon flow tracking mechanism; carrying out carbon constraint based on a dynamic carbon flow calculation result by using a park integrated energy system hour-level rolling optimization scheduling model with operation cost and carbon emission minimization as a target; and converting the optimal scheduling model into a mixed integer linear programming problem, and obtaining a Pareto optimal solution set by using an epsilon-constraint method and taking the minimum operation cost as a target and carbon emission as a constraint. Compared with the prior art, the method provided by the invention overcomes the defect that the traditional static accounting method cannot reflect the spatial-temporal dynamic characteristics of the carbon flow, and provides an accurate carbon measurement basis for implementing low-carbon scheduling in a park.