47 results about "Cost effectiveness" patented technology

The invention discloses a common concrete and ultra-high performance concrete performance prediction and mix proportion multi-objective optimization design method and system, and the method comprises the steps: obtaining a comprehensive data set which covers the mix proportion, performance data and cost data of common and ultra-high performance concrete; correlation analysis is carried out, and influence factors strongly correlated with the target variable are determined; constructing a concrete performance prediction model by using a machine learning algorithm, training and testing, then carrying out interpretability analysis, and selecting an optimal concrete performance prediction model; constructing a mix proportion optimization design objective function and an ultra-high performance concrete cost function; establishing a multi-objective optimization design mathematical model in combination with constraint conditions, a cost function and an optimization objective function; and solving by adopting a multi-objective evolutionary algorithm, generating an approximate Pareto frontier solution set, and determining an optimal mix proportion optimization design scheme. According to the method, the concrete performance can be predicted, the mix proportion with the optimal comprehensive performance and cost effectiveness is obtained, and multi-objective optimization design of the concrete mix proportion is achieved.

The invention discloses a line intelligent planning and fault early warning method suitable for electric power engineering design, and relates to the technical field of electric power engineering. The method comprises the following steps: quantifying geographic information, geological conditions and construction cost into a continuous decision curved surface through spatial semantic segmentation and a cost curved surface model, and identifying a large-area low-cost region as a primary feasible region in combination with a dynamic clustering algorithm; a multi-dimensional decision index is constructed based on spatial features, geological stability and facility association data, fault regions such as terrain abrupt change or facility conflict are identified through real-time association coefficients, and an exception handling mechanism is triggered; and selecting a seed region with an optimal construction condition as an anchor point, constructing a joint probability model of spatial features and cost, and generating an optimal path considering feasibility probability and cost effectiveness in combination with an expectation maximization algorithm and a graph optimization technology. According to the invention, scientificity and economical efficiency of cable planning under complex geological conditions are improved, and key technical support is provided for intelligentization of electric power engineering.

A system and method for automated cybersecurity defensive strategy analysis that predicts the evolution of new cybersecurity attack strategies and makes recommendations for cybersecurity improvements to networked systems based on a cost / benefit analysis. The system and method use machine learning algorithms to run simulated attack and defense strategies against a model of the networked system created using a directed graph. Recommendations are generated based on an analysis of the simulation results against a variety of cost / benefit indicators.

The invention relates to the technical field of power distribution network intelligent control, in particular to a power distribution network intelligent planning system and method for scenic spots, and the method comprises the steps: precisely estimating the power demand fluctuation through the time series data analysis of the activity schedule and historical power use mode of the scenic spots, and generating a load prediction table; a power grid topological structure and current and voltage fluctuation are monitored in real time through an isolated forest algorithm, potential fault points are accurately diagnosed, the risk of fault occurrence is effectively reduced, fault prediction has higher sensitivity, potential problems can be recognized in advance, the influence of power grid faults on power supply stability is reduced, and the power supply reliability is improved. The operation cost and saving are analyzed through the random forest, and the cost-benefit ratio of different optimization schemes is quantitatively evaluated, so that more accurate decision support is provided for power grid operation optimization, the flexibility and stability of a power system are improved, and efficient utilization of power resources and maximization of economic benefits are realized.

A system and method for appraising film screenplays and offering predictive insights on their marketability and potential success. The artificial intelligence model and machine learning algorithms consider various production elements and generate management and production outcomes on an expedited timeline. The web services infrastructure implemented creates an enhanced ecosystem for creative development, production, and talent management by minimizing obstacles such as the inaccessibility of information and data about both national and global development trends. Moreover, the system can summarize creative data and create loglines, character breakdowns, titles, and summaries. An A.I generated a sociological analysis that provides a multi-faceted and comprehensive outlook on industry-related research, such as a cost-benefit production analysis.

A system and method for automated cybersecurity defensive strategy analysis that predicts the evolution of new cybersecurity attack strategies and makes recommendations for cybersecurity improvements to networked systems based on a cost / benefit analysis. The system and method use machine learning algorithms to run simulated attack and defense strategies against a model of the networked system created using a directed graph. Recommendations are generated based on an analysis of the simulation results against a variety of cost / benefit indicators.

The invention aims to provide a mountain building green low-carbon technology cost-benefit evaluation method based on matter element extension, and belongs to the technical field of green building cost-benefit evaluation. An evaluation index system covering six dimensions of land saving, material saving, water saving, energy saving, indoor environment and operation management is constructed; the incremental cost and benefit of the green low-carbon technology are estimated, a subjective weight is determined by adopting a G1 method, an objective weight is determined by adopting an entropy weight method, and a comprehensive weight is obtained through game theory combination. The method comprises the following steps: dividing evaluation characteristics into a basic level, a first-star level, a second-star level and a third-star level by utilizing a matter element extension evaluation model, determining a classical domain, a node domain and matter elements to be evaluated, calculating correlation degree and comprehensive correlation degree, and finally determining the level of an evaluation index. The invention provides a scientific and comprehensive evaluation method for the cost benefit evaluation of the green low-carbon technology of the mountain building, fills up the research blank in the field, and promotes the application of the green low-carbon technology in the mountain building.

The invention provides an operation system and an operation control method of an intelligent agent product. According to the system, through a knowledge base templated import and dynamic maintenance mechanism, batch rapid import of multi-format product documents can be supported, and manual operation is greatly reduced. According to the system, a fine-grained multi-role authority management system is constructed, authority boundaries of a super administrator, an operation administrator, customer service personnel and equipment developers are clearly divided, and the safety and manageability of the system are enhanced. The system can comprehensively collect and analyze operation data including question and answer logs, control logs, model calling times, cost and the like; a multi-dimensional operation result is generated through hotspot problem analysis, control frequency statistics and the like, meanwhile, the cost-benefit ratio is calculated, and a data basis is provided for identifying user requirements and optimizing an intelligent agent response strategy. According to the system, through standardization and configuration design of an equipment adaptation process, a novel equipment access template is provided, a data demand and a test process are defined, a new product access period is shortened, and the market response speed is improved.

The invention relates to the technical field of enterprise resource management, in particular to an enterprise management optimization method and system based on big data, and the method comprises the following steps: capturing data of employee skills, a project execution process and customer interaction according to enterprise resource planning in an enterprise, analyzing the captured data, and carrying out the multi-dimensional information classification processing; and constructing an enterprise resource comprehensive data set. According to the method, the flow and utilization efficiency of the resources is improved by establishing the graphic database to integrate the enterprise resources and converting the data elements into the network nodes and the connecting edges, and the resource flow and utilization efficiency is improved by identifying and analyzing the association strength of the nodes and the weights of the edges in the resource network. Through detailed flow path analysis, an enterprise can formulate a scientific resource allocation strategy according to market requirements and current resource situations, resource allocation and use are optimized after dynamic resource allocation is implemented, the strategy is adjusted in time by comparing and analyzing resource efficiency and cost effectiveness before and after optimization, and the market response speed and competitiveness of the enterprise are remarkably improved.

The invention discloses a BIM-based fabricated building management method, and relates to the technical field of fabricated buildings, and the method comprises the following steps: extracting the type of a prefabricated part, the demand of the prefabricated part, and the use condition of the prefabricated part in a corresponding construction stage through a BIM model through a data collection module; according to the building management method, dynamic factors such as the construction speed and weather influence are considered, accurate prediction of the requirements of the prefabricated parts of the BIM fabricated building is achieved, project managers can better master the supply condition of the prefabricated parts, comprehensive optimization of logistics cost is achieved through accurate calculation of delay cost, and the construction efficiency is improved. According to the technical scheme of the invention, a manager can timely take targeted optimization measures, the direct cost and the indirect cost can be comprehensively analyzed, the comprehensive evaluation of the cost benefit is realized, the project manager can accurately understand the economic benefit and progress control condition of the project, more scientific and comprehensive support is provided for decision making, and an excellent management effect is achieved.

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 logistics distribution, in particular to a logistics distribution method and system based on the Internet of Things, comprising: calculating the predicted travel time cost of each road section in the road network in multiple future time windows through a space-time prediction model; generating a discrete signing success probability distribution for each order within the multiple time windows using a Bayesian inference model; applying a multi-objective optimization algorithm to obtain a set of Pareto optimal distribution scheme sets; selecting a final distribution route from the Pareto optimal distribution scheme set according to a preset risk preference or cost benefit strategy, and issuing it to the vehicle terminal for execution. The present application can provide decision makers with a scientific basis for selection based on different business strategies, making the final distribution decision more flexible and strategic.

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 present invention relates to the technical field of task allocation, and in particular, to a method and system for regional classification in a crowdsourcing environment with multi-level task allocation. The method includes obtaining historical data of crowdsourcing workers; using a random forest model to predict the number of workers in each grid after grid division based on the historical data of crowdsourcing workers; obtaining a density ratio based on the predicted number of workers, and dividing the task area into low-ratio, medium-ratio, and high-ratio areas, wherein based on the goal of maximizing cost-benefit, a delay strategy is adopted in the low-ratio area, a balance strategy is adopted in the medium-ratio area, and a collaboration strategy is adopted in the high-ratio area; cross-grid area recruitment is used for the remaining tasks to complete the task allocation. The present invention provides a multi-level task allocation strategy for the regional classification method in a crowdsourcing environment. The solution divides the entire sensed area after gridification into low-ratio, medium-ratio, and high-ratio areas through the corresponding density ratio, fully considering the characteristics of different areas.

The invention relates to the technical field of industrial process control and intelligent manufacturing, in particular to a wood shaving mixing quality control and efficiency optimization management system which comprises a performance factor deconstruction unit used for collecting real-time agent attribute data to generate agent attribute vectors; converting the proxy attribute vector into a standardized performance factor vector; the total factor exposure evaluation unit is used for calculating a real-time total factor vector; calculating the factor deviation degree of the real-time total factor vector and the ideal factor vector; the factor deviation degree is judged, and a qualified signal, a first-level deviation signal or a second-level deviation signal is generated; the formula dynamic optimization unit is used for constructing a cost-benefit optimization function, solving a new mixing proportion and issuing and executing the new mixing proportion; the model closed-loop correction unit is used for constructing a performance prediction model; updating the factor mapping matrix; the technical problem that unified management and evaluation are difficult due to high heterogeneity of raw materials is solved, and the quality stability of final products is effectively guaranteed.

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 relates to the technical field of cloud-side cooperation processing, and particularly discloses a scenic spot data analysis method and system based on cloud-side cooperation, a terminal and a medium, and the method comprises the steps that an edge node generates a preliminary event processing result through local processing logic, determines a data reporting strategy according to an event grade division result, and carries out data reporting; collaborative semantics representing a processing purpose are carried during data reporting. The cloud end portraits the to-be-processed tasks according to the task parameters and the current overall operation situation of the scenic area to obtain portraying features of the to-be-processed tasks; screening out a processing unit for executing the current to-be-processed task according to the portrait features in combination with the task priority, the data affinity and the cost effectiveness; the processing unit performs execution according to a pre-constructed scenic region knowledge graph to generate a processing result; and performing multi-level early warning according to a processing result, and generating and issuing a system control instruction. According to the invention, unnecessary data uploading is reduced, and end-to-end response time is shortened; and the accuracy and efficiency of model processing are improved.

The invention relates to the technical field of logistics distribution, in particular to a logistics distribution method and system based on the Internet of Things, and the method comprises the steps: calculating the predicted passing time cost of each road section in a road network in a plurality of time windows in the future through a space-time prediction model; using a Bayesian inference model to generate discrete sign-in success probability distribution for each order in the plurality of time windows; a multi-objective optimization algorithm is applied to solve and obtain a group of Pareto optimal distribution scheme sets; and selecting a final delivery route from the Pareto optimal delivery scheme set according to a preset risk preference or cost benefit strategy, and issuing the final delivery route to a vehicle terminal for execution. According to the invention, scientific basis for selection based on different business strategies can be provided for decision makers, so that the final distribution decision is more flexible and strategic.

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.

This invention proposes a method, device, and medium for evaluating the benefits of demand-side reactive power compensation. Grid companies and equipment manufacturers work together as service providers to serve users, taking on different roles. A cost-benefit model is established for each participant, comprehensively considering the economic benefits of demand-side reactive power compensation and its impact on power supply reliability. An evaluation parameter matrix is ​​constructed, and the comprehensive benefit evaluation results of each demand-side reactive power compensation scheme are derived based on the relative proximity of each reactive power compensation scheme to the ideal solution. This invention comprehensively evaluates the benefits of each compensation scheme, deriving the optimal solution and achieving a win-win situation for all parties.

The invention discloses a curve track-bridge coupling system support stiffness identification method based on a vehicle scanning method, which belongs to the field of engineering structure monitoring, and comprises the following steps: establishing a curve double-beam system mechanical model with moving elastic mass, deducing a control equation, and solving by adopting a modal superposition method and Laplacian transformation to obtain the support stiffness of a curve track-bridge coupling system. Coupled system frequencies are extracted from contact points or vehicle responses, in particular track moduli are efficiently identified using fourth frequency components of first order modalities. The method has the advantages of being high in operation maneuverability, high in cost-benefit ratio and outstanding in implementation efficiency, and is suitable for health monitoring of the curve track-bridge coupling 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 new energy output prediction method and system based on a Mama model, and the method comprises the steps: collecting historical new energy output data and natural environment data in the same period, and carrying out the multi-dimensional data fusion according to a time sequence, and forming a historical data set; performing normalization processing on the data in the historical data set; based on the normalized historical data set, adopting a progressive training strategy to train a pre-constructed Mamba model; and inputting the current natural environment data into the trained Mamba model, and outputting a new energy output prediction result. The method has the advantages of being high in prediction accuracy, high in prediction speed, high in adaptability, remarkable in cost effectiveness, efficient in data utilization and good in expandability.

The invention relates to the technical field of information management, in particular to a constructional engineering material information management method and system, and the method comprises the following steps: recognizing the material requirements of constructional engineering, decomposing the constructional engineering into a plurality of construction stages, defining the material requirements and budget for each stage, collecting required key materials, and generating a stage material requirement table. According to the invention, the whole building engineering is decomposed into a plurality of construction stages, and the material demand and budget are defined in detail for each stage, so that the transparency and budget control capability of the project are remarkably improved, and the material cost and supply risk of each construction stage are evaluated more specifically and prospectively. Based on a material purchasing state transition logic defined by a cost risk assessment result, inventory management is further optimized, dynamic balance between material supply and project requirements is ensured, a purchasing plan is flexibly adjusted according to real-time market changes and a construction project progress, and cost benefit maximization is achieved.

The present application relates to a kind of intervention effect analysis method, device and equipment based on illegal accident, and it is related to the field of intelligent transportation.The intervention effect analysis method based on illegal accident provided by the present application not only pays attention to the change rate of illegal accident data, but also emphasizes the role of two key factors, intervention cost and intervention efficiency.In particular, this method calculates the cost-benefit ratio of each intervention measure by dynamically monitoring the illegal and accident data of a certain section of a road within a certain period of time, combined with the changes before and after the implementation of specific intervention measures, thereby achieving a more comprehensive and in-depth evaluation of the effectiveness of intervention measures.In this case, it can be revealed which types of intervention measures are most likely to bring significant safety improvements, and it can also help identify strategies that may consume excessive resources but have little effect, providing strong data support for policymakers.