80 results about "Cost control" patented technology

The invention discloses an order-driven cross-factory collaborative production system, and relates to the technical field of intelligent manufacturing and supply chain collaboration, and the system obtains the productivity data, logistics cost and tax policies of a plurality of production bases such as Ningbo, Thailand and America in real time, and carries out the intelligent splitting and distribution of orders through a multi-base productivity game algorithm. And dynamic optimal matching of the order and the productivity is realized. Meanwhile, the system integrates WMS inventory data and third-party logistics real-time quotation, a transportation scheme with the lowest total cost is generated by adopting a genetic algorithm, and cross-border logistics and tax expenditure are remarkably reduced. The system overcomes the problems of information isolated island, response lag, extensive cost control and the like in traditional multi-factory production, realizes global productivity collaborative optimization and supply chain integrated intelligent decision, and improves the enterprise order performance efficiency and the overall resource utilization rate.

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 system dynamics, and discloses an electricity certificate carbon market price analysis method and system based on system dynamics, and the method comprises the steps: S1, determining the main body of a green certificate transaction market and the main body of a carbon emission permit transaction market, and determining a renewable energy power generation mode; s2, constructing a TCC cost control mechanism; s3, TCC cost is calculated according to a TCC cost control mechanism; s4, establishing stock flow dynamic model frames of the green certificate market and the electricity market and the carbon emission permit trading market and the electricity market, and combining the two dynamic model frames to generate an electricity certificate carbon market stock flow dynamic model frame; and S5, analyzing the electricity evidence carbon market price. The system comprises an information input unit, a mechanism construction unit, a calculation and analysis unit and a system dynamics model framework construction unit. According to the method, the system dynamics and the method for controlling and optimizing the TCC cost are combined, and the analysis accuracy and reliability are improved.

The utility model provides a refrigerant filling machine to solve the problem that in the prior art, a large amount of manpower and time cost are consumed for achieving high-precision filling. The refrigerant filling machine comprises a booster pump, a storage tank, an electronic scale, a control system, a filling pipeline, a pressure sensor, a roller and a storage chip. The refrigerant filling machine is excellent in cost control, traditional complex assemblies are abandoned, the booster pump and the high-precision online electronic scale are combined, and the manufacturing, debugging and maintaining cost is reduced. The electronic scale monitors the weight in real time, the control system performs comparison operation, and the error of the filling amount is controlled within five thousandths. The whole filling process is automatically executed by a control system, and an operator only needs to simply set parameters and start operation to complete a refrigerant filling task. The outer wall of the storage tank is connected with an external power supply through the leakage protector, the power supply is automatically cut off during leakage, and the alarm sends out a signal during abnormity.

The invention relates to a user behavior fused flow casting dynamic pricing method and device, equipment and a medium. The method comprises the steps of obtaining an original behavior log of a user, performing feature extraction processing on the original behavior log, generating a structured behavior feature vector, performing quantification processing on the structured behavior feature vector, and generating a user-level behavior willingness index; historical transaction data is obtained, the user-level behavior willingness index and the historical transaction data are input into a price elasticity prediction model for processing, a user-level real-time price elasticity coefficient is output, and the price elasticity prediction model is constructed based on a random forest algorithm and a gradient boosting algorithm; and performing dynamic bidding calculation processing based on the user-level real-time price elasticity coefficient and a basic bidding parameter preset by the advertiser to generate a final optimized bidding. According to the method, user behavior feature analysis, price elasticity prediction and dynamic bidding calculation are fused, individuation of flow casting dynamic pricing is achieved, the rate of return on investment of advertisement putting is effectively increased, and cost control is optimized.

The invention discloses a multi-objective optimization decision-making method and system for sewage treatment based on OLAP reinforcement learning, and solves the problems that an existing sewage treatment control method neglects carbon emission, is extensive in cost control and does not integrate a carbon transaction mechanism. The method comprises the following steps: constructing an OLAP cube, and generating an optimal historical strategy set; establishing a state set according to the sewage environment parameters and the carbon price; an action set is established according to the optimal historical strategy set, and an action priority strategy is set according to the carbon emission weight partition; establishing a multi-target reward function dynamically adjusted according to the carbon price; constructing each controller agent model for training until the strategy converges; and dynamically outputting an optimal strategy by the intelligent agent according to the change of the carbon price. According to the method, a multi-dimensional OLAP cube is constructed to analyze the incidence relation between key variables, a plurality of process control agents are constructed, reinforcement learning collaborative optimization of working condition adjustment is achieved, the carbon emission item optimization weight is adjusted according to the real-time carbon transaction price, and dynamic policy adaptation is achieved.

The invention specifically relates to a BIM and big data analysis-based construction project construction cost control method, and relates to the technical field of construction project construction management. Cost budgeting and prediction; coordinated management and control of progress resources; cost monitoring and early warning; and collaborative management and system guarantee are realized. According to the method, the BIM model, the Internet of Things and the external data source are integrated, the standardized cost database is constructed, and the accuracy and the real-time performance of the data are ensured; automatically counting the engineering quantity by using a parameterized family library, and predicting a material price trend in combination with an LSTM model in a cost budgeting and predicting stage; generating a cost risk thermodynamic diagram through Monte Carlo simulation, and quantifying the risk probability of each node; meanwhile, indexes such as BCWS and BCWP are calculated in real time based on earned value management, automatic early warning and reason analysis are performed when cost deviation occurs, accurate cost control of the whole process from estimation to budget to construction is achieved, and the cost hyper-branched risk is effectively avoided.

The invention belongs to the technical field of aircraft test design, and particularly relates to a method and a device for determining risks of a manufacturer and an ordering party in a testability test. The method comprises the following steps: step S1, obtaining influence factors of a contractor risk and an ordering party risk; s2, calculating the maximum feature root of a first matrix constructed by the importance among the influence factors, and meanwhile, calculating the maximum feature root of a second matrix constructed by the influence degrees of the influence factors on the acceptor and the ordering party; s3, calculating a correction amount according to a ratio of the maximum feature root of the first matrix to the maximum feature root of the second matrix; and S4, according to the correction amount, correcting a given acceptor risk and a given ordering party risk. According to the method, the design requirements of the acceptor risk and the ordering party risk are met, and scientific balance between cost control and risk prevention and control is realized.

This invention belongs to the field of coal procurement technology, and relates to a procurement decision-making method and system based on multi-timescale coal demand forecasting. It includes: acquiring power generation influencing factor data at at least two time scales, and generating power generation forecast values ​​corresponding to each time scale based on the power generation influencing factor data; fusing the power generation forecast values ​​at each time scale to obtain a fused power generation forecast value; decomposing the fused power generation forecast value into initial demand quantities for different coal types according to the consumption rate of each generating unit for different coal types, and adjusting the initial demand quantities according to a preset blending strategy to obtain the target demand quantity for each coal type; acquiring coal price time series data for each coal type, and generating future coal price forecast values ​​for each coal type based on the coal price time series data; and determining a procurement decision scheme based on the target demand quantity for each coal type and the coal price forecast value. This invention achieves accurate decision-making and cost control in fuel procurement.

This invention relates to the field of power system demand response technology, and provides a user demand response method based on master-slave game theory under cost control constraints. The method includes: establishing a demand response model using master-slave game theory, where electricity retailers design time-of-use pricing strategies, and electricity users respond based on a convex utility function; the utility function includes a quantification term for electricity usage satisfaction and a calculation term for electricity costs; the electricity retailers' revenue function includes four functions: user electricity costs, long-term market electricity purchase costs, current market electricity purchase costs, and conditional risk value, coupled with the characteristics of the electricity spot market and risk management requirements; proving the existence of a Nash equilibrium solution using backward induction; and optimizing the strategy based on a slime mold optimization algorithm. This invention provides important support for electricity retailers to formulate flexible pricing mechanisms and tap demand-side resources in terms of cost control for users with high response potential and optimization of peak-valley load differences.

This invention relates to the field of garment production chain collaboration, specifically disclosing a method for querying and quoting garment styles based on the SKU dimension. The method includes: creating and distributing query forms supporting multi-dimensional selection by style, style color, and style color code SKU; the supplier terminal generating a quotation based on the query form, calling its internal standard component cost library to calculate details for SKU entries, updating the status to "quoted" and generating a unique version record after confirmation; the brand performing operations such as accepting or rejecting the quotation; and after order completion, using actual production cost data to calibrate the supplier's standard cost library. This invention achieves refined cost control from the style level to the SKU level, ensures the rigor and traceability of the collaborative process through a versioned state machine, and realizes self-optimization of the cost model through a data closed loop of quotation-production-calibration, significantly improving the collaborative efficiency and cost control capabilities of the garment supply chain.

The invention provides an intelligent warehouse management method based on a WMS, and relates to the technical field of intelligent warehouse, and the method comprises the following steps: 1, environment risk quantitative management: firstly, collecting warehouse environment data through an Internet of Things sensor network integrated by the WMS; then establishing an environmental risk evaluation model, and calculating the risk coefficient of each storage location; according to the invention, an end-to-end smart warehouse management closed loop is constructed through an environmental risk quantification model, a dynamic scheduling decision, multi-party collaborative auditing and dominant cost control; wherein discrete monitoring data is converted into a linkage scheduling instruction, and the splitting state of risk perception and disposal in a traditional WMS is broken; the problem of quality loss caused by single-dimensional scheduling is solved through a two-dimensional decision rule fusing the environmental risk and the service emergency degree; multi-party data mutual trust is realized based on an alliance chain, and a cross-mechanism collaboration barrier is eliminated; and through a risk quantification cost model, the implicit disposal cost is visualized.

The present application relates to a kind of facing polynomial fuzzy control system cost control stability judging method, comprising the following steps: establishing polynomial fuzzy model;According to the first SOS condition based on Lyapunov function, try to solve the first polynomial matrix and the second polynomial matrix, omit non-convex term in solving process, judge whether it is successful, if yes, based on the first polynomial matrix and the second polynomial matrix, obtain feedback gain;Based on feedback gain, according to the second SOS condition, try to solve positive definite matrix, judge whether it is successful, if yes, based on positive definite matrix, construct polynomial Lyapunov function, realize cost control analysis based on polynomial Lyapunov function.Compared with prior art, the present application solves the non-convex optimization problem in cost control in two steps, avoids the influence of the constraint existing in input matrix itself on the flexibility of fuzzy control system design, and improves the performance of control system by obtaining the numerical value of cost J.

The invention relates to the field of business travel cost control, in particular to an employee business travel behavior optimization and cost control method and system based on consumption data, and the method comprises the steps: collecting business travel consumption data of employees within a reference time T, and carrying out the subdivision of the business travel consumption data according to the consumption types; based on the consumption data, calculating a reputation score of the employee, specifically, for each type of consumption behavior of the employee, calculating a single consumption influence score of the employee; performing weighted summation on all consumption data of the employees within the reference duration T based on the single consumption influence score in combination with the time attenuation factor to obtain dynamically updated employee reputation scores; according to the employee reputation score, performing employee reputation grade division in combination with an employee consumption frequency parameter k value; and according to the reputation level and the consumption category, carrying out differential adjustment on the travel expense standard. And the reputation score is calculated according to the consumption behavior, so that the top-order reservation phenomenon is avoided, unnecessary waste is reduced, and the business travel cost is reduced.

The invention discloses a welding production process cost management system and method. The method comprises the following steps: acquiring basic production process data of each process in the welding production process through a data acquisition module; business data analysis is conducted on the basic production process data through a business processing module based on a preset variable dictionary, business detailed data of all production process businesses are obtained, and variable parameters in data calculation are stored in the variable dictionary; and generating a cost summary report corresponding to the to-be-calculated cost item type through a cost summary module according to the to-be-calculated cost item type and the business detailed data. Unified integration of multi-source data, automatic and accurate cost calculation and full-life-cycle management are achieved, and accurate data support is provided for enterprise cost control and strategic decision making.

The invention relates to the technical field of cost accounting, and discloses an offline production caliber cost accounting method, which comprises the following steps: building a cost accounting data model to provide a basis for improving the efficiency and accuracy of cost management, optimizing resource configuration and supporting decision making; establishing a uniform interface platform of the integrated heterogeneous system, and collecting actual production data of the offline caliber; and accounting the output of offline products of different production lines according to a cost accounting model. The method achieves the accounting of the production cost at the product offline time node of the iron and steel enterprise, and improves the management and control timeliness level of the production cost. A uniform interface platform of an integrated heterogeneous system is established, and actual production data is collected according to production characteristics of different production lines, so that an accounting result is close to actual production to the greatest extent; the informatization system implemented based on the method realizes the function of timing automatic cost accounting, avoids a large amount of tedious and low-efficiency work, and saves a large amount of labor cost.

The invention relates to a ship pipe section manufacturing change management and cost accounting method and related products. By automatically integrating design change, waste return state feedback and cost accounting, the problems of data dispersion and inconsistency are solved. The system automatically tracks and analyzes the specific influence of design change on pipe section manufacturing, so that whether the pipe section needs waste return or not is automatically determined, manual operation dependence is reduced, and waste return state determination efficiency and accuracy are improved. And detailed and reliable financial data support is provided by automatically calculating the discarding cost and the newly-added cost of the pipe section parts caused by design change. Through seamless joint and data sharing among departments of design, manufacture, finance and the like, the enterprise management efficiency is remarkably improved, the extra cost caused by change is effectively reduced, and reliable support is provided for project management and cost control.

The invention provides a server instance cost optimization system, and relates to the technical field of resource optimization. In the application, the cost optimization system comprises a data acquisition module, a data fusion module, a utilization rate analysis module, a cost analysis module and an optimization suggestion module. Through the cost optimization system, the data fusion module fuses the data of each dimension, so that the problem that the cost analysis is difficult to comprehensively reflect the actual resource efficiency due to the data of a single source is solved, the cost analysis of the server instance based on each analysis dimension is realized, the cross-business and cross-department cost analysis is realized, and the efficiency of the server instance is improved. The optimization suggestion module is determined based on the resource dimension and the budget dimension, so that the accuracy and practicability of the cost optimization suggestion are ensured, resource waste and budget hyper-branched can be avoided, early warning of the server instance and optimization of resources and cost corresponding to the server instance can be realized based on the cost optimization suggestion, and the user experience is improved. And thus, refined cost control of the server instance is realized.

The financial information integrated management platform comprises a data acquisition module which is used for acquiring historical financial data, current financial data, disease types and patient numbers in different periods of each department, and the historical financial data comprises income amounts and cost amounts over the years; the current financial data comprises money income and cost money from the beginning of the current year to the previous day; and the income prediction module is used for predicting the income amount in a period of time in the future according to the disease development trends in different periods and the historical income condition of each department. According to the financial information integrated management platform and management method provided by the invention, the income condition can be analyzed and predicted according to the previous financial data, and the cost is checked in multiple aspects to realize cost management and control, so that intelligent management of financial information is realized, and refined and intelligent management is realized.

The invention belongs to the technical field of Internet of Things and enterprise cost accounting, and particularly relates to an enterprise dynamic cost accounting method based on Internet of Things perception driving, and the method comprises the steps: collecting a multi-dimensional original data source in real time through an Internet of Things perception node, and transmitting the multi-dimensional original data source to an edge computing gateway; the method comprises the following steps of: preprocessing an original data source, extracting six types of cost factors, constructing a judgment matrix by adopting an analytic hierarchy process, performing consistency check and calculating to obtain a final weight value of each cost factor; based on the final weight value, accounting the six types of sub-item costs, and summarizing to obtain the real-time dynamic total cost of the enterprise; calculating a cost deviation rate and dynamically adjusting related parameters according to a threshold value judgment result; and calculating a fitting degree, judging and accounting effectiveness according to a fitting degree result, and if not, performing loop optimization until reaching the standard. According to the invention, a whole-process closed-loop accounting system is constructed, the real-time performance, the accuracy and the intelligent level of cost accounting are improved, the cost control difficulty is reduced, and reliable support is provided for enterprise cost control decisions.

The application discloses a single-phase intelligent electric energy meter with a fee control function and a method thereof, and relates to the field of electric energy fee control. The complete new fee rate strategy is encapsulated into a transaction data packet for overall transmission. After receiving the transaction data packet, the electric meter side first performs presetting and integrity checking on the whole data packet, and only when it is confirmed that the data packet is correct, the electric meter enters a ready state, so that data inconsistency caused by interruption of updating is avoided. The use of the new strategy is triggered by a unified effective time stamp, so that the synchronization of activation is ensured. Finally, through an activation state proof mechanism based on a random challenge number, the master station can remotely verify that the electric meter is operated under the correct new strategy, so that the atomicity, accuracy and traceability of the whole fee control process are ensured.

The invention discloses a blast furnace batching optimization system, method and equipment and a computer storage medium, and relates to the technical field of blast furnace ironmaking automation. The system comprises a data acquisition module, a data processing module, a computational logic module and a front-end presentation module. The method comprises the following steps: automatically collecting real-time component data of crude fuel; carrying out batch average processing on the data to obtain a calculation condition; based on a material balance and thermodynamic principle, performing batching calculation to obtain blast furnace production parameters and cost indexes; and displaying a result through a front-end interface. Through automatic data acquisition and integrated calculation, the defects that traditional manual batching calculation is low in efficiency, large in error and lagged in cost control are overcome, accurate, rapid and optimized blast furnace batching is achieved, production decisions are effectively guided, and the production cost and the labor intensity of operators are reduced.

The invention discloses a production logistics global modeling and joint optimization method based on demand prediction, and the method employs a LightGBM model to carry out middle and short term periodic demand prediction, and considers the influence of time lag nonlinear factors on demands. A production-inventory strategy joint optimization model taking periodic replenishment as a core is constructed, and a (T, s, S) strategy framework is adopted to perform joint modeling on a safety inventory level s, a target inventory level S and a production quantity q in each period. The model adopts an improved self-adaptive differential evolution algorithm, minimizes total cost as a target function, comprehensively considers inventory holding cost, stockout cost, production cost and transportation cost, meanwhile, restrains the service level not to be lower than a preset standard, and realizes production-inventory coordinated optimization under the condition of prediction uncertainty. The whole-process production logistics model is constructed, the expandability is good, and the service level and the operation cost control level are remarkably improved.

The application discloses an AI-based intelligent logistics pricing method and system, and belongs to the field of logistics information technology. Historical logistics order data, real-time market data, cargo attribute data and transportation environment data are collected, multi-dimensional feature engineering is constructed, and a gradient boosting tree algorithm is used for feature importance screening. The screened effective features are input into a hybrid AI prediction model combining gradient boosting tree and deep neural network for basic freight prediction. A dynamic pricing system containing a hierarchical holiday special factor is introduced to correct the basic freight. Isolation forest anomaly detection and data re-verification mechanism are combined to filter abnormal quotes. Finally, personalized and real-time accurate logistics quotes are generated. The application solves the problems of low efficiency, poor accuracy, and inability to respond to market fluctuations and special holiday needs in traditional logistics pricing, significantly improves the pricing efficiency of logistics enterprises and customer satisfaction, and optimizes enterprise cost control.

The invention discloses a raw material ratio control method and system for a degradable self-adhesive label, and relates to the technical field of material engineering.The method comprises the steps that a use scene of the degradable self-adhesive label is established, and performance targets including mechanical strength, adhesive force, degradation speed, flexibility, cost control and the like are determined; and according to the scene adaptation degree and the historical data optimization priority, the target is classified into a primary target and a secondary target. An initial population is constructed, each individual represents a raw material proportioning scheme, fitness calculation is performed based on a performance target, and a result is used for iterative optimization. When a preset requirement is met, tolerance space balance optimization is triggered, a convergence result is generated, and finally label raw material proportion control is carried out. The technical problem that in the existing adhesive label raw material proportioning process, it is difficult to meet optimization of multiple performance targets at the same time is solved, and the technical effect that the raw material proportioning of the degradable adhesive label is optimized, so that the degradable adhesive label achieves balance of the performance targets in different use scenes is achieved.

The invention discloses a project full life cycle cost control method and system, and relates to the technical field of enterprise project management and cost control. The method comprises the following steps: accessing heterogeneous cost data from a plurality of service systems through a multi-source data acquisition framework, and realizing quasi-real-time data synchronization by adopting a change data capture technology; performing real-time processing on the accessed data by using a stream processing engine and a memory computing framework, and constructing a distributed cost knowledge graph based on a graph database, the knowledge graph being used for modeling a causal relationship among cost elements; based on the knowledge graph and the real-time data, at least one intelligent analysis operation is executed, and the intelligent analysis operation comprises self-adaptive process optimization based on reinforcement learning, self-adaptive cost anomaly detection based on multi-model fusion and high-performance cost analysis based on a multi-dimensional data cube engine. The technical problems that all links of a traditional cost management system are separated, and data flow is not smooth are solved.

The invention discloses a school canteen cost accounting method. The method comprises the following steps: firstly, automatically matching a corresponding cost accounting rule according to a school type and a meal supply mode; then, cost basic data from a canteen business system, a financial system and other channels are collected; and then, according to a matching rule, the cost is collected and shared according to nutrition improvement plan funds, nutrition food partner food fees, non-nutrition food partner food fees and other types, and the number of food of nutrition food, non-nutrition food and the like, specifically, purchasing and receiving settlement sharing are carried out by adopting a proportional sharing or preferential sharing mode; and carrying out indirect cost allocation by adopting an income-expenditure matching method or a workload method. And finally, calculating the cost of each meal and the unit cost of dishes based on the shared data. According to the invention, the problems of multi-fund source mixing, unclear cost accounting and difficult accurate management and control of special fund in the school canteen are solved, automatic and fine management of cost accounting is realized, and effective technical support is provided for scientific pricing, cost control and fund supervision.

The application discloses an artificial intelligence driven SPD inventory dynamic optimization and cost control method, which belongs to the technical field of inventory optimization and cost control. The normalized data is time series reconstructed to obtain medical consumable data sequences in time sequence, so that the medical consumable data sequences are demand predicted through a medical consumable prediction model to obtain accurate future medical consumable prediction results, which can effectively and accurately predict the use trend of medical consumables, thereby reducing inventory backlog and capital occupation. A group optimization algorithm is used to collaboratively solve an SPD cost double-layer control model to obtain an optimal inventory strategy and a corresponding cost control strategy. Based on the optimal inventory strategy and the cost control strategy, all suppliers are dynamically scored, and the selected suppliers share the optimal inventory strategy and the cost control strategy, so that the dynamic optimization and adjustment of the inventory and the replenishment strategy are realized, the total cost is optimized, and the application and promotion are facilitated.

This invention provides a method and system for optimizing electricity purchase plans on the retail side based on load fractal characteristics, belonging to the field of electricity market technology. This invention extracts load fractal characteristics reflecting their correlation features by performing modal decomposition on historical load and bidding data; analyzes electricity market rules to form constraint units and identifies risk-sensitive nodes that cause fluctuations in electricity purchase costs; performs perturbation correction on the fractal characteristics based on these sensitive nodes to generate corrected load forecast results; maps the forecast results to the constraint structure to construct the correlation topology between load characteristics and electricity purchase costs; further extracts the cost sensitivity distribution, establishes a hierarchical mapping model, performs structured optimization, and outputs the electricity purchase plan. This invention improves the responsiveness of electricity purchase strategies to market changes and the level of cost control under complex market conditions.

The invention provides a production and marketing planning method and system, electronic equipment and a storage medium, and the method comprises the steps: constructing a plurality of first constraint conditions and first planning targets according to first planning information and first planning cost information under a first granularity; determining a first planning result based on a plurality of first constraint conditions and the first planning target; if the first planning result meets the preset total demand condition, a plurality of second constraint conditions and second planning targets are constructed according to the first planning result, second planning information under the second granularity and second planning cost information; wherein the time length indicated by the first granularity is greater than the time length indicated by the second granularity; determining a second planning result based on a plurality of second constraint conditions and a second planning target; and based on the second planning result and the second planning information, determining a production main plan, a package sale plan and a capacity utilization rate of each factory so as to realize the purposes of optimizing production efficiency and controlling cost.