18 results about "Cost effectiveness" patented technology

The invention discloses a comprehensive evaluation method and system for a pollutant control line in the iron and steel industry, and solves the problem that the evaluation result of the pollutant control line is inaccurate due to the fact that the evaluation dimension of the pollutant control line is single and full-life-cycle decision cannot be supported in the prior art. Performing cost evaluation and benefit evaluation on the cost index and the benefit index based on the exponential decay model, constructing a fusion evaluation matrix in combination with the cost evaluation and the benefit evaluation, and determining a cost evaluation grade and a benefit evaluation grade based on the fusion evaluation matrix in combination with a close degree method; according to the method, cost evaluation and benefit evaluation are carried out on the cost index and the benefit index based on the exponential decay model, and the change rule of the technical performance along with time can be dynamically reflected, so that the long-term cost-benefit prediction error is remarkably reduced; the cost reference value and the benefit reference value are combined to construct the fusion evaluation matrix, so that the economy and effectiveness of the full life cycle of the technology can be simulated more truly.

The present invention relates to computer implemented adaptive and iterative methods to improve and accelerate a quality control decision or a performance test in a specific technical field while reducing the overall cost of the quality control or performance test process, respectively; the method comprising: constructing a sequential test; iterating the following steps using the sequential test until a decision is made, obtaining a set of samples, checking the decision of the criteria for the set of samples, determining in an adaptive way the optimal number of additional data samples required for the subsequent iterative step if no decision has been made in the current iteration.

The present application relates to the technical field of industrial process control and intelligent manufacturing, in particular to a wood shaving mixture quality control and efficiency optimization management system, comprising a performance factor deconstruction unit for collecting real-time agent attribute data to generate an agent attribute vector; converting the agent attribute vector into a standardized performance factor vector; a total factor exposure evaluation unit for calculating a real-time total factor vector; solving the factor deviation degree of the real-time total factor vector and an ideal factor vector; and discriminating the factor deviation degree to generate a qualified signal, a first-level deviation signal or a second-level deviation signal; a formula dynamic optimization unit for constructing a cost-benefit optimization function, solving a new mixing ratio and issuing an execution; a model closed-loop correction unit for constructing a performance prediction model; and updating a factor mapping matrix; the present application solves the technical problem of difficult unified management and evaluation caused by high heterogeneity of raw materials, effectively ensuring the stability of the final product quality.

The application discloses a line intelligent planning and fault early warning method suitable for power engineering design and relates to the technical field of power engineering. The method comprises the following steps: through spatial semantic segmentation and a cost surface model, quantifying geographic information, geological conditions and construction cost into a continuous decision surface, combining a dynamic clustering algorithm to identify a large-area low-cost area as a primary feasible region; based on spatial features, geological stability and facility correlation data, constructing multi-dimensional decision indicators, and through real-time correlation coefficients, identifying "fault regions" such as terrain mutations or facility conflicts, and triggering an abnormal processing mechanism; selecting a seed region with the optimal construction condition as an anchor point, constructing a joint probability model of spatial features and cost, combining an expectation maximization algorithm and graph optimization technology, and generating an optimal path that takes into account the feasibility probability and cost benefit. The application improves the scientificity and economy of cable planning under complex geological conditions and provides key technical support for the intelligentization of power engineering.

The application discloses a kind of financial data analysis early warning systems based on artificial intelligence, it is related to financial analysis technical field, system includes: data acquisition module, for obtaining the consumption record data of staff;Behavior pattern analysis module, for the behavior pattern analysis of the consumption record data, identifies historical consumption behavior;Consumption mode library construction module, for according to the historical consumption behavior, constructs consumption mode library;Consumption intention identification module, for identifying current consumption intention, the current consumption intention includes consumption type, budget range and time requirement;Consumption optimization suggestion generation module, for according to the current consumption intention and the consumption mode library, generates consumption optimization suggestion.The application can combine historical consumption behavior and current consumption intention to generate consumption optimization suggestion, to realize financial data analysis early warning, improve cost efficiency, reduce operating cost.

The invention discloses an active power distribution network hierarchical autonomous balancing method based on scenarized multiple targets, and belongs to the technical field of power system power distribution network operation control. Comprising the following steps: defining a balance range according to a unit, grid and partition three-level architecture, and dividing a receiving type group, a balance type group and a sending type group by double indexes; a typical scene is described in multiple dimensions, an extreme load day is selected through a convex hull algorithm, a conventional day is selected in normal distribution, and new energy output is fitted in combination with Beta distribution to generate a credible curve; a differential active balance strategy is adopted, candidate measures are matched based on scene features, an optimal scheme is selected by adopting cost-benefit scores, and hierarchical power flow optimization cross-voltage hierarchy collaboration is realized; and full-dimensionally evaluating adequacy and safety, and dynamically iteratively adjusting the full-dimensionally evaluated adequacy and safety. The method improves the power grid balance capability and the new energy consumption rate, reduces the operation cost, guarantees the system stability, and is suitable for the intelligent operation of the active power distribution network.

The invention discloses a multi-objective planning method, system and equipment for an integrated energy system and a storage medium, and the method comprises the steps: carrying out the mathematical modeling of key equipment in the system, building a multi-energy flow balance constraint, and further building a multi-objective optimization function comprising cost, carbon emission and system toughness. On the basis, a marginal cost curve reflecting toughness, environmental protection and comprehensive improvement economic cost is generated through iterative optimization; and further converting the comprehensive marginal cost value into natural logarithmic coordinates and carrying out second-order difference calculation, and taking an inflection point which is generated for the first time from negative to zero or positive as a planning scheme with the optimal cost benefit. According to the method, the toughness is improved and the marginal cost of carbon emission is reduced through quantitative evaluation, and an innovative inflection point identification method is utilized, so that effective balance of economy, toughness and low-carbon property is realized, and a decision-making basis giving consideration to benefits and robustness is provided for planning of a comprehensive energy system.

The invention discloses a multi-channel intelligent customer acquisition and cost optimization method and system, and the method comprises the steps: integrating a plurality of customer acquisition channels, such as a social media platform, a search engine, an offline store, a cooperative merchant, and the like through building a standardized data interface, and collecting customer flow data, marketing activity data and channel putting cost data; the system carries out cleaning, duplicate removal and normalization preprocessing on collected data, and a prediction model is established by using big data technologies such as time sequence analysis, geographic information system analysis and customer portrait analysis in combination with machine learning algorithms such as a decision tree and a random forest. Based on cost-benefit ratio calculation and a Markov decision process, the system dynamically adjusts marketing resource distribution of each channel, including advertisement putting budget and popularization personnel configuration. According to the method, the customer obtaining cost can be remarkably reduced, the customer obtaining efficiency is improved, the market competitiveness is enhanced, scientific data support is provided for management decision, and intelligent customer obtaining and refined cost management of a consumer financial institution are realized.

The invention provides a multi-modal data set construction method and management system, and relates to the technical field of data management and maintenance, and the method comprises the following steps: collecting the related feature information of data in a data set; systematized preprocessing is carried out on the related feature information; generating a storage quality index according to the related feature information score, and constructing a storage value evaluation system; when the storage space is lower than a space threshold value, collecting correction dynamic information of the data, and generating a storage correction coefficient through the correction dynamic information; and generating a storage optimization index based on the storage quality index and the storage correction coefficient, and re-evaluating the data. According to the method, a storage quality index and storage optimization index quantitative index system is introduced, a fine management closed loop which takes the data value as the center and actively adapts to business and resource changes is formed, and the utilization rate of storage resources and the cost effectiveness are remarkably improved while the data quality and the application efficiency are guaranteed.

Systems and methods for generating and implementing real-time decarbonization roadmaps for at least one industrial facility are disclosed. In one embodiment, a method comprises obtaining GHG emissions data from at least one sensor associated with the facility's equipment, storing and categorizing the emissions data according to direct and indirect (Scope 1 and Scope 2) emissions, and forecasting long-term emissions under a business-as-usual scenario. The method further involves receiving and evaluating decarbonization initiatives—such as energy efficiency measures, carbon capture and storage (CCS) projects, or emissions offsetting strategies—based on their applicability and cost-effectiveness. By generating marginal abatement cost curves (MACCs) that consider capital and operational expenses, implementation feasibility, and project timelines, the method identifies prioritized emissions reduction measures. The output includes implementation directives provided to a controlled facility emissions system, which can adjust equipment parameters, integrate renewable energy solutions, or otherwise modify operating conditions to achieve targeted GHG reductions.

The invention discloses a reservoir safety monitoring method based on edge calculation, and particularly relates to the technical field of hydraulic engineering safety monitoring. According to the method, the reservoir geographic grid model is constructed and the static environment parameters are pre-calculated, so that an objective and uniform data base is established for evaluation, a quantifiable index system covering three dimensions of monitoring perception, data timeliness and cost effectiveness is established, and accurate calculation logic is defined for each dimension; different layout schemes are converted into a group of calculable coefficients, and finally a comprehensive and comparable comprehensive efficiency index is generated through weighted fusion, so that quantitative sorting of advantages and disadvantages of the schemes is realized, subjectivity and randomness of decision making are greatly reduced, and scheme comparison and selection are based on basis, scientific and transparent.

The invention discloses an enterprise planning and site selection method based on probability statistics, which relates to a data processing technology and comprises the following steps: acquiring enterprise site selection characteristics from sample enterprises; the method comprises the following steps: converting enterprise site selection characteristics into a quantifiable multi-level index system, dividing a research area into a plurality of grid units, placing sample enterprise data of a sample enterprise in the grid units, and respectively detecting whether each index is related to enterprise site selection through chi-square test; if the indexes are irrelevant to enterprise site selection, the indexes are removed from the multi-level index system; counting probability distribution of each index according to index grading; and calculating a final site selection probability from the multistage index system according to the probability distribution, and endowing the final site selection probability to the grid unit to obtain a grid site selection probability graph. According to the method, probability statistics and geographic information are combined, simplicity, interpretability and cost effectiveness are kept, practicability and fusion with traditional planning are more emphasized, and implementation obstacles caused by excessive dependence on complex technologies are avoided.

The “Good Customer Score (GCS)” consists of the components necessary using data and analytics to effectively identify a “Good Customer.” GCS is to be used in predictive modeling projects designed to help improve the cost effectiveness and the new development of Acquisition, Retention, Recovery, Cross-sell, Reward, and Loss Prevention efforts. Adding the GCS to the Enterprise Data Warehouse would allow the enterprise to begin using GCS to develop specific targeted customer strategies.

The invention relates to the technical field of energy conservation and emission reduction, and discloses an energy conservation and emission reduction measure determination method based on carbon emission prediction, which comprises the following steps: dividing an emission data set to obtain a training set, a verification set and a test set, constructing a prediction model by using the training set and the test set to obtain a trained prediction model, and performing prediction based on the trained prediction model to obtain a prediction result. The method breaks through the limitation of a traditional static model, captures the causal relationship of multiple variables along with time evolution through the emission coefficient, and provides support for prediction; meanwhile, prediction and intervention form closed-loop cooperation, medium-and-long-term emission trend prediction is achieved based on a prediction model of emission coefficient weighting, intervention measures are designed in combination with a generation model embedded with energy conservation constraints, and it is ensured that the measure combination strictly follows the physical law. And the technology maturity, the cost benefit, the social acceptance and the policy compliance are evaluated through the multi-dimensional scoring matrix, and the whole-process scientific guidance from prediction to measure landing is formed.

The invention relates to an intelligent building aided design method, system and device and a medium. The aided design method comprises the steps that a three-dimensional building information model is constructed based on building basic parameters; analyzing a preset technical contradiction matrix to generate a monitoring strategy, and outputting an enhanced building information model and a monitoring strategy file; dynamically adjusting sensor deployment parameters; performing data preprocessing in combination with external environment data to generate a space-time fusion database; performing risk trend prediction and dynamic calculation of an early warning threshold through a machine learning model, and outputting a risk early warning instruction set and a structure damage report; simulating mechanical distribution of different reinforcement schemes, calculating a cost-benefit ratio, and generating an interactive decision panel and a recommendation scheme report; and receiving a feedback score of the user on the recommendation scheme report and an early warning accuracy statistical result through the interactive decision panel, and updating a deployment rule in the monitoring strategy file and a parameter weight of the machine learning model. According to the invention, the safety monitoring precision and the early warning response speed of the building are improved.

The application discloses a curve track-bridge coupling system support stiffness identification method based on a vehicle scanning method, belongs to the field of engineering structure monitoring, and establishes a curve double-beam system mechanical model with a mobile elastic mass, deduces a control equation, and solves the control equation by using a modal superposition method and Laplace transformation, extracts a coupling system frequency from a contact point or a vehicle response, and especially efficiently identifies track modulus by using a fourth frequency component of a first-order modal. The application has the advantages of strong operation maneuverability, high cost benefit ratio and outstanding implementation efficiency, and is suitable for health monitoring of a curve track-bridge coupling system.

To provide a design support system that assists even inexperienced design engineers in appropriately selecting new materials and components suitable for the purpose of product design, and that can also present the annual cost-effectiveness of design changes using new materials and components. [Solution] The design support system 1 is equipped with a database 120, a machine learning means 110, an input means 310, and a display means 320. The database stores design information for multiple materials and parts that make up a product in advance. The machine learning means generates a trained model 130 that extracts design information with a high degree of fit to the design target information, using the multiple design information as training data 112. The trained model then calculates the functional fit and cost fit for existing materials and parts and new design candidates individually, based on the design target values ​​input by the design engineer. Furthermore, the display means displays the respective fit scores side by side so that the design engineer can easily understand the comparison results.

The invention discloses a financial data analysis early warning system based on artificial intelligence, and relates to the technical field of financial analysis, and the system comprises a data obtaining module which is used for obtaining consumption record data of employees; the behavior pattern analysis module is used for performing behavior pattern analysis on the consumption record data and identifying historical consumption behaviors; the consumption mode library construction module is used for constructing a consumption mode library according to the historical consumption behaviors; the consumption intention recognition module is used for recognizing a current consumption intention, and the current consumption intention comprises a consumption type, a budget range and a time requirement; and the consumption optimization suggestion generation module is used for generating a consumption optimization suggestion according to the current consumption intention and the consumption mode library. According to the method, the consumption optimization suggestions can be generated in combination with the historical consumption behaviors and the current consumption intention, so that financial data analysis and early warning are realized, the cost effectiveness is improved, and the operation cost is reduced.