14 results about "Cost control" patented technology

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 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 application discloses a kind of based on unified identification's cross-library ERP-MES fusion single product cost accurate accounting method, it is related to industrial informatization, cross-database data fusion, production financial integration and fine cost accounting technical field.The application is directly cross-library joint calculation by constructing the global unified unique identification system throughout raw material, procurement, production, sales whole process under the premise of without data synchronization, intermediate library, ETL tool and interface service, realizes MES production library, raw material management library, ERP procurement library, ERP sales library;Adopt lightweight temporary table and extremely simple step-by-step batch update mechanism, based on finished product output proportion realizes single product level raw material cost automatic accurate allocation, completes raw material cost, sales income, additional cost whole process automation accounting and whole link traceability.The application solves traditional multi-system data island, cross-library development complex, data synchronization delay, cost accounting extensive, code redundancy, maintenance cost is high, poor generalization and other technical pain points from architecture root, has no invasion access, real-time calculation, accounting precision, high performance, easy maintenance, cross-industry generalization and other outstanding advantages, can be widely applied to the ERP and MES depth fusion and fine cost control scene of various manufacturing enterprises.

This application provides a multi-dimensional, dynamically coupled traffic allocation decision-making method and system. The method includes acquiring user attribute data, business attribute data, channel performance data, and channel cost data; determining channel anomaly indicator data, calculating anomaly weighting coefficients, performing circuit breaker status detection, and generating anomaly management strategies; extracting basic channel cost information for each channel, and determining the dynamic premium factor and effective cost coefficient for each channel based on channel performance data; calculating user weights, business weights, and performance scores to determine the channel score for each channel; converting the channel score into traffic allocation probability; determining the budget ratio based on the real-time call count and effective cost coefficient for each channel; performing a status assessment on the budget ratio to obtain the budget status; and determining cost control parameters based on the budget status. This application addresses the problems of lack of real-time adaptability, crude anomaly handling mechanisms, and a single decision-making dimension.

The application discloses a kind of machining spare parts intelligent inventory management method and system, solve the technical problems such as fuzzy inventory information in traditional spare parts management, blind spare, out-of-stock early warning is not timely and excessive capital occupation;The system includes spare parts information management module, inventory monitoring module, demand prediction module, early warning module and procurement management module, can realize the digitization of spare parts information filing, allocate unique code for each spare part, record its model, specification, applicable equipment, shelf life and other key information.The method includes spare parts filing, inventory monitoring, demand prediction, early warning triggering, procurement execution and inventory optimization and other steps, realize the intelligentization of machining spare parts inventory, fine management, balance spare supply and cost control, reduce the production downtime caused by spare shortage, improve spare parts inventory turnover rate, reduce capital occupation cost, provide reliable spare parts guarantee for machine tool operation.

The application belongs to the technical field of engineering construction management, and discloses a chemical installation measurement visa integrated method and system based on AI. The system contains an AI image recognition calculation engine, an AI voice semantic engine, an AI compliance verification engine, an AI claim analysis engine, a progress margin calculation engine and a team efficiency accounting engine, and is internally provided with a winning bid list library and a 2024 quota specification library, and is realized by using a WeChat applet and a cloud SaaS architecture. The application automatically calculates the quantity by taking photos on site, automatically generates a visa by voice, intelligently verifies compliance and analyzes claims, calculates the real-time progress margin, and automatically exports settlement data, effectively solves the industry pain points of difficult measurement, difficult visa, difficult settlement and poor compliance in chemical installation engineering, realizes the sinking of cost control to the construction front line, and enables construction personnel to distinguish between in-contract and out-of-contract work without professional cost knowledge, automatically determines the claimable construction period and cost, and truly connects the whole process of measurement, visa, claim, progress control, settlement and team efficiency analysis to realize intelligent closed-loop. The application is simple to operate, has high automation, is traceable in the whole process, and is suitable for intelligent management of various chemical installation and bill of quantities valuation installation engineering projects.

The application relates to the technical field of computer-aided design, in particular to a packaging design scheme generation method fusing a field knowledge base, which comprises the following steps: determining reference indexes of each reference surface of each historical packaging design three-dimensional model of a target object, combining the number of trend connecting lines corresponding to each contact point to obtain the reference degree of each contact point, and screening to obtain a deviation point; obtaining an enhanced weight of the deviation point based on the distance difference of the deviation point and other deviation points in a preset adjacent range of the deviation point to a corresponding standard surface of a standard model; obtaining a packaging enhancement buffer thickness of the deviation point from the enhanced weight, so as to generate a packaging design scheme of the target object. With the aid of computer-aided design, the packaging design scheme of the target object is obtained, the transportation safety of the target object is improved, the cost increase caused by blindly increasing the global buffer thickness is avoided, and a fine balance between safety and cost control is achieved.

The invention discloses an actual cost accounting method and system based on order and batch. The method comprises the following steps: S1, calculating an actual cost rate according to an order and a production batch; s2, sorting the current production products, and calculating the actual cost and the average moving price step by step from bottom to top according to the sorting; and S3, generating a cost accounting report according to the order batch, the actual cost rate and the actual cost, and carrying out order benefit analysis. According to the invention, through order and batch two-dimensional management and control, production lean, supply chain agility and cost refinement are realized; and performing accurate cost accounting and profit insight, and performing order-level cost and profit analysis: accurately accounting materials, manpower and manufacturing fees to a single order, and identifying high-gross-profit products and customers.

Through information analysis and processing, we aim to better evaluate costs, improve cost control, optimize resource allocation, and enhance the efficiency of cost data processing. We process cost data more efficiently and accurately using computers, present optimized evaluations based on smart predictions and feedback, and provide smarter, data-driven decision-making support for construction costs. [Solution] The decision support system consists of a data digitization module that constructs a digital cost database from construction data according to time and site relationships, a data analysis module that analyzes related data and obtains relational parameters, a data knowledge processing module that uses the relational parameters to construct the results after knowledge data processing in the digital cost database and a knowledge cost database, and a data smartening module that uses the data in the knowledge cost database to construct a model by combining it with actual on-site cost level parameters, etc., performs intelligent cost evaluation, and obtains a score.

This invention relates to the field of contract review technology in the construction and real estate sector, and particularly to an intelligent review method and system for contracts in this sector. The invention includes: constructing a rule knowledge base for the construction field based on knowledge samples; performing deep semantic collaboration and dynamic aggregation on long texts based on contracts in the knowledge base to obtain aggregated contracts; performing semantic consistency reasoning on the aggregated contracts to obtain inferred contracts; and optimizing the review efficiency of ultra-long contracts based on the inferred contracts to obtain optimized contracts. By introducing a scalable rule base and adaptive model configuration, this invention not only optimizes engineering contracts but also seamlessly adapts to other professional fields such as consulting, intellectual property, trademark registration, and agency contracts, thus significantly outperforming existing general contract review products in terms of accuracy, efficiency, and cost control.

This application provides a method, device, and electronic device for managing advertising campaign costs based on a dual-track online and offline classification system. By integrating a dynamic knowledge graph with a prompting learning model that efficiently fine-tunes parameters, it achieves high-precision automatic classification of advertising campaign cost categories. The method acquires the user-inputted cost description text and specified category, utilizes the dynamic knowledge graph for key entity extraction and multi-hop reasoning, and generates a first classification result and confidence score. Simultaneously, the text is input into the prompting learning model, which guides fill-in-the-blank prediction through soft prompts, outputting a second classification result and confidence score. Combining the confidence scores of both, a decision fusion rule is used to determine whether to trigger user correction prompts, and the knowledge graph and model parameters are dynamically updated based on user feedback. The system supports new entity recognition and incremental learning, forming a closed-loop optimization mechanism. This solution effectively solves the problems of inaccurate budget allocation, low execution efficiency, and difficulty in cost control caused by the fragmentation of data from online and offline channels, improving the accuracy, interpretability, and adaptability of cost classification, and achieving intelligent and refined advertising campaign cost management.