15 results about "Financial costs" patented technology

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 relates to a financial cost prediction method and device based on machine learning, equipment and a medium. The method comprises the steps of performing dimension reduction processing according to enterprise financial data to obtain a dimension-reduced data set; performing invisible feature analysis to generate an invisible feature set containing periodic fluctuation features and project association features; generating an initial prediction model based on the set training; analyzing the importance of each invisible feature and screening reliable feature subsets; performing cross-scene verification on the initial model through the subset to generate a stability index, and further optimizing the model; and inputting real-time financial data into the optimized model, and outputting a cost prediction result. By adopting the method, the problem of insufficient prediction accuracy and stability caused by ineffective processing of high-dimensional data, excavation of invisible features and verification of model stability in the existing method can be solved, and the accuracy and reliability of financial cost prediction are improved.

The application discloses a kind of high-temperature equipment remote monitoring method and platform based on Internet of Things, it is related to industrial Internet of Things and fault diagnosis technical field.The method is triggered by non-destructive micro-excitation when identifying that measuring point is in steady-state thermodynamics window through edge computing gateway, fitting thermal response time constant;The gradual drift bias of measuring point is extracted based on state space model;Then the above-mentioned extraction features, multi-source heterogeneous high-frequency acquisition data and three time stamp sequences are assembled into multidimensional evidence package, and are reported after being stored by hash encryption signature;After evidence package is signed by cloud platform, the integrated reliability score of measuring point is calculated, and strict according to hard safety threshold Uncontrollable strategy is executed Intelligent alarm grading disposal and maintenance work order scheduling.The application realizes the high-confidence online non-destructive diagnosis of sensor physical degradation without interfering with the underlying main control loop, effectively eliminates false alarm, optimizes the operation scheduling based on financial cost, and provides a completely tamper-proof digital audit chain for industrial monitoring, greatly improving the overall safety and economy of high-temperature equipment operation.

This invention relates to the field of internet data processing technology, and discloses a method and system for dynamic display and price calculation of electronic bidding and tendering. The method includes: responding to the business rule control instructions of the tendering party to generate a switch state vector containing multiple function switch states; when the bidding page is loaded on the bidder's terminal, determining the display and interaction attributes of the input components based on the switch state vector, and controlling the input of bidding data; receiving bidding data containing the original bid value, payment method, and delivery mode, and performing validity cleaning on the data based on the switch state vector; calculating financial cost correction items and logistics cost correction items by combining preset interest subsidy rates and freight parameters; and finally generating the final bid price based on the original bid value and each correction item. This invention achieves the unification of front-end interaction and back-end logic through parameterized control, quantifies non-cash payments and delivery changes as cost corrections, and stores the bid price and settlement price separately.

The invention discloses a business and financial fusion method and system based on data deep interaction, and a storage medium, and the method comprises the steps: collecting equipment operation data, financial cost data and sales prediction data in real time through an edge calculation node, constructing a dynamic classification pipeline through Apache NiFi, and carrying out the real-time collection of the data; in combination with DeltaLake hierarchical storage, structured data ACID transaction control and unstructured data key index extraction are realized; a multi-dimensional interaction model comprising a spatio-temporal feature extraction branch, a time sequence prediction branch and a cross-modal fusion branch is constructed, a graph neural network mining device is associated with topological features, a Transform model processes financial time sequence dependence, and a gating loop unit realizes business-financial feature dynamic weighted fusion; generating a multi-scene decision scheme through Monte Carlo tree search, issuing and executing the multi-scene decision scheme through an MQTT protocol, and constructing a feedback closed loop; a zero-trust architecture data channel and a block chain evidence storage mechanism are set to guarantee security, and the system comprises an edge computing layer, a cloud management layer, a security control layer and a man-machine collaboration layer.

1. Name of the product in this design: Cost Accounting Instrument. 2. Purpose of this design: For financial cost accounting. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D model 2.

The invention discloses a project full-cycle dynamic financial cost prediction and precise control method and system, and the method comprises the following steps: S1, obtaining and preprocessing multi-modal original data in a project full life cycle, the multi-modal original data containing structured financial data and unstructured operation data; and S2, carrying out feature extraction and fusion on the preprocessed multi-modal data by adopting a technical scheme of combining cross-modal feature alignment, attention weighted fusion and feature cascade enhancement. The invention relates to the technical field of project financial cost management. According to the project full-period dynamic financial cost prediction and precise control method and system, multi-modal data are comprehensively utilized, features are efficiently fused, a dynamic cost prediction model is constructed, precise staged prediction is achieved, a dynamic real-time cost control strategy can be generated, the hyperbranched risk is effectively reduced, the system integration degree is high, a one-stop scheme is provided for project management, and the project management efficiency is improved. Popularization and application are facilitated.

The present application relates to the technical field of engineering cost tracing accounting, and discloses an automatic engineering financial cost accounting method based on fund chain tracing. The method comprises receiving project-related original financial voucher flow, generating a standardized fund transaction sequence through structured deconstruction and semantic standardization processing. According to a preset rule atlas, the sequence is associated and aggregated into a multi-level fund circulation network with hierarchical relationships, and the edge attributes of the network include circulation amount and cost subject direction. On the network, deep mining and propagation tracing are performed from the end cost consumption node to the source fund allocation node, and a complete cost influence link set is identified. Based on the link set, dynamic cost allocation and re-accounting are performed, a tracing accounting report for each cost subject is generated, and the contribution of different fund sources to the final cost is quantified. The method improves the cost accounting from static subject collection to dynamic tracing along the actual path, and reveals the complete fund context of cost formation.

This method, platform or patent is planned economy under a market economy, eliminates random or blind production by factories and random or blind consumption by consumers and supply according to demand all people in the world from birth to death with the best product, goods, and service quality and the lowest prices through “non-retail” in a nontraditional sense, “no fixed cost expenses such as bank interest required by typical businesses,”“eliminating random or blind production by manufacturers and consumption by consumers,”“thoroughly eliminating waste in the production and consumption process,”“substituting, eliminating, and thoroughly eliminating inefficient small, medium, large, and even huge enterprises in every industry for every product, commodity, or service,”“consumers being able to buy the best quality, lowest price, and best value products, commodities, or services in the world,”“saving people's time and money in consumption,”“helping the poor and reducing poverty,”“green and low-carbon,”“helping to address global climate change,” and so on. Therefore, this method, this platform, and this patent change the way people work and live, as well as the way enterprises produce products in the production process.This patent represents a revolutionary and disruptive redefinition, reshaping, and replacement of modern economic theory, including micro and macroeconomics, since the patent changes, replaces, disrupts, redefines, and reshapes modern business rules and revolutionizes and redefines the course of human civilization and human civilization itself.This method will establish a wave that includes Industry 4.0 or 5.0, and transform manufacturing into a service industry this method eliminates the traditional concept of primary, secondary, and tertiary industries and merge into one.Producers under the method or patent have no advertising expenses, no sales expenses or costs, and no market expenses or costs even no financial costs, This method's revolutionary and transformative reshaping and redefining of the traditional financial industry, especially the banking sector, and human social and economic activities. This method will help and serve almost all consumers from birth to near-death around the world save time and money, optimize the way they spend their money, helps poor people and reduces the poverty rate, eliminates waste in various industries from production to consumption, therefore, is environmentally friendly and low-carbon and effectively respond to global climate change.

The invention relates to an enterprise financial cost control and analysis system, which comprises a data acquisition layer, a data preprocessing layer, a cost calculation layer, a deviation analysis layer, a decision support layer and an early warning layer, and each layer sequentially realizes data circulation and function collaboration. According to the method, a time variable t is introduced through a dynamic unit cost formula (Cink (t)), high-frequency data collection of 1-10 minutes per time is combined, the cost accounting delay time is shortened to the minute level, a system can capture raw material unit price fluctuation and production working hour abnormity in real time, the cost response speed is improved, an attention mechanism is fused with an LSTM algorithm, and by dynamically distributing feature weights, the cost accounting delay time is shortened to the minute level. The cost prediction error rate is reduced, accurate data support is provided for an enterprise to lock low-price suppliers in advance, the system is in butt joint with an existing enterprise system, a data system does not need to be reconstructed, the implementation cost is reduced, a visual report and an executable optimization scheme are output, a manager is assisted to make a quick decision, the cost is prevented from being out of control through a multi-level early warning mechanism, and enterprise losses are reduced.

The invention relates to the field of logistics, and discloses a logistics price dynamic pricing method, device and equipment and a storage medium, and the method is used for carrying out dynamic pricing on waybill prices. The method comprises the following steps: acquiring and preprocessing historical financial cost data, historical transportation operation data and historical market supply and demand data to obtain preprocessed data; performing feature engineering processing on the preprocessed data to obtain a plurality of key indexes related to the freight rate, and performing analysis to obtain association scores among the plurality of key indexes; based on the plurality of key indexes and the association scores among the plurality of key indexes, constructing an intelligent decision model based on a graph neural network; acquiring real-time financial cost data, real-time transportation operation data and real-time market supply and demand data, and performing prediction by using the intelligent decision model to obtain a cost prediction result and a demand prediction result; and generating a dynamic price in combination with the cost prediction result, the demand prediction result and a preset service target.

The application provides a marine industry and finance fusion decision-making method, medium and system based on big data analysis, belongs to the technical field of big data analysis, and achieves the spatiotemporal alignment and collaborative feature domain classification of multi-source heterogeneous data by adopting a multiscale pattern Laplacian operator evolution dynamics atlas clustering algorithm, removes mixed noise through a fractional calculus complex time-varying diffusion dynamics denoising algorithm, compresses high-dimensional sparse features by using a self-encoder and t-SNE fusion dimension reduction technology, inputs an adaptive spatiotemporal feedback skip graph neural network model based on wave equation constraint to obtain a dynamic financial cost prediction result, and finally maps high-dimensional non-Gaussian industry and finance distribution to a standard Gaussian space by using a deep flow artificial intelligence model based on manifold alignment and performs reverse inverse transformation to output disaster prevention budget compilation and capitalization budget suggestions, thereby solving the technical problem that after multi-source heterogeneous marine industry and finance data are fused under the condition that the spatiotemporal scales do not match, false features are generated, and financial decision-making is misjudged.

The invention relates to an AI-based financial cost accurate measurement and calculation and risk dynamic prevention and control system, which comprises a hardware layer, a data layer, an AI engine layer and an application layer, and is characterized in that each layer is cooperatively linked with a communication protocol through a standardized data interface; the hardware layer provides computing power, storage and data acquisition support for the system; and the data layer realizes collection, analysis and standardization processing of total financial data. The AI model fusing XGBoost and LSTM not only can accurately analyze cost influence factors and realize fine accounting of real-time cost, but also can predict a future cost fluctuation trend, the limitation of post accounting of a traditional system is solved, an enterprise is helped to formulate a cost control strategy in advance, and through a mode of combining association rule mining and an anomaly detection algorithm, the cost control strategy is optimized. The comprehensive identification of dominant and hidden financial risks is realized, the timeliness and pertinence of risk prevention and control are ensured by a three-level early warning mechanism and a risk tracing function, and the financial risk loss of an enterprise is effectively reduced.

This method, platform or patent is planned economy under a market economy, eliminates random or blind production by factories and random or blind consumption by consumers and supply according to demand all people in the world from birth to death with the best product, goods, and service quality and the lowest prices through “non-retail” in a nontraditional sense, “no fixed cost expenses such as bank interest required by typical businesses,”“eliminating random or blind production by manufacturers and consumption by consumers,”“thoroughly eliminating waste in the production and consumption process,”“substituting, eliminating, and thoroughly eliminating inefficient small, medium, large, and even huge enterprises in every industry for every product, commodity, or service,”“consumers being able to buy the best quality, lowest price, and best value products, commodities, or services in the world,”“saving people's time and money in consumption,”“helping the poor and reducing poverty,”“green and low-carbon,”“helping to address global climate change,” and so on. Therefore, this method, this platform, and this patent change the way people work and live, as well as the way enterprises produce products in the production process.This patent represents a revolutionary and disruptive redefinition, reshaping, and replacement of modern economic theory, including micro and macroeconomics, since the patent changes, replaces, disrupts, redefines, and reshapes modern business rules and revolutionizes and redefines the course of human civilization and human civilization itself.This method will establish a wave that includes Industry 4.0 or 5.0, and transform manufacturing into a service industry this method eliminates the traditional concept of primary, secondary, and tertiary industries and merge into one.Producers under the method or patent have no advertising expenses, no sales expenses or costs, and no market expenses or costs even no financial costs, This method's revolutionary and transformative reshaping and redefining of the traditional financial industry, especially the banking sector, and human social and economic activities. This method will help and serve almost all consumers from birth to near-death around the world save time and money, optimize the way they spend their money, helps poor people and reduces the poverty rate, eliminates waste in various industries from production to consumption, therefore, is environmentally friendly and low-carbon and effectively respond to global climate change.

The invention relates to the technical field of financial cost optimization, and discloses a financial data mining driven cost optimization method and system. The method comprises the following steps: firstly, collecting a financial data set comprising a plurality of cost dimensions, and carrying out standardized preprocessing to integrate dispersed cost information to form a unified and normative data basis; a cost optimization analysis model is established, a cost mode and a potential optimization opportunity are mined from financial data, traditional analysis limitation is broken through, and an optimization space is accurately positioned; secondly, aiming at a selected business scene, applying the model to a simulation environment to execute a simulation process, dynamically displaying cost changes under different conditions, and enhancing the perspectiveness of an optimization scheme; and finally, making a cost optimization decision scheme based on a simulation result, and outputting an executable optimization instruction set, so that the optimization scheme is converted into specific operation. According to the method, the availability of cost data, the analysis depth, the scheme adaptability and the execution effectiveness are improved, and enterprises are assisted to realize more efficient cost management.