132 results about "Economic analysis" patented technology

The invention discloses an internet-based intelligent bid invitation management platform, which comprises a data integration and analysis module configured to establish an intelligent comprehensive economic analysis model by integrating internal data and / or external data of the intelligent bid invitation platform; the standardized bid invitation file module is configured to construct an industry lexical analysis and language model by utilizing natural language processing and a knowledge graph; the intelligent question-and-answer type bidding file filling module is configured to complete compiling of a bidding file by guiding a bidder to adopt an intelligent question-and-answer mode; the intelligent bid evaluation tool set module is configured to assist the bid evaluation process by establishing an intelligent bid evaluation tool; the risk early warning module is configured to construct a knowledge graph of a supplier, a subject matter and a project; and the large model application module is configured to construct an AI bid evaluation model by using a large model technology. Through intelligent bid invitation management, bid evaluation work efficiency is improved, and fairness and accuracy of bid evaluation results are ensured.

The invention provides a photovoltaic power station design system and method based on ecological collaborative optimization, and relates to the technical field of data processing. The system comprises an initial configuration module which is used for generating an initial layout structure of a photovoltaic module, performing energy-saving and consumption-reducing calculation and economic analysis according to generating capacity data, and obtaining initial energy-saving and consumption-reducing data and initial economic analysis data; the secondary optimization module is used for optimizing the parameters of the photovoltaic module based on the economical efficiency analysis data and determining energy-saving and consumption-reducing data and economical efficiency analysis data through the generating capacity optimization data; the ecological evaluation module is used for determining ecological benefit data of the photovoltaic power station according to the ecological influence parameters; and the collaborative optimization module is used for setting a power generation income weight and an ecological benefit weight so as to optimize the photovoltaic module layout structure and generate a photovoltaic power station design scheme based on ecological collaborative optimization. The method is used for realizing collaborative optimization of power generation benefits and ecological benefits of the photovoltaic power station, so that the power station gives consideration to ecological protection while improving the power generation efficiency.

The invention discloses a photovoltaic module cleanliness evaluation method and system based on multi-dimensional data fusion. The method comprises the following steps: acquiring multi-dimensional data of a photovoltaic power station, including generating capacity data, power station state data, irradiation data, meteorological data, geographic position data, cleaning record data, weather forecast data and economic index data; preprocessing the data; constructing a multi-dimensional feature; a pre-trained Transform architecture time sequence model is adopted to carry out training; evaluating the cleanliness state of the photovoltaic module in real time and predicting the change trend; and determining the optimal cleaning time and generating decision suggestions based on the cleanliness evaluation result and economic analysis. Through multi-dimensional data fusion and a large model algorithm, precise evaluation and scientific decision making of the cleanliness of the photovoltaic module are realized, the evaluation accuracy is improved by 15-20%, and the method is suitable for photovoltaic power stations at different geographic positions and under different climate conditions.

The invention provides a deep reservoir physical property prediction and oil and gas resource evaluation system based on artificial intelligence. And the problems of physical property prediction and resource evaluation of low-porosity and low-permeability reservoirs in oil-gas exploration are solved. The system fuses earthquake, well drilling and well logging data, and generates a high-quality reservoir database through data cleaning, normalization and interpolation processing. A deep learning model is constructed by adopting a convolutional neural network and a long-short-term memory network, a nonlinear relationship between reservoir physical properties and multi-source data is automatically captured, and high-precision prediction is realized. The system is integrated with a real-time economic evaluation module, and an economic evaluation result is dynamically adjusted through a gradient enhanced tree model in combination with real-time market data. In addition, an automatic feedback mechanism is introduced into the system, and a region with a large error is re-sampled and the model is updated. According to the scheme, the reservoir prediction precision and exploration efficiency are remarkably improved, dynamic economic analysis is supported, and reliable technical guarantee is provided for exploration and development decisions of deep oil and gas resources.

The invention provides a short-time energy storage marginal effect characteristic analysis method based on a pinch point principle and time sequence operation simulation, and the method comprises the steps: generating a planning scene based on historical time sequence data, and obtaining a theoretical available value and load time sequence data of new energy; acquiring amplitude-frequency characteristics of the net load by using a frequency domain decomposition method, and constructing a source-trap combination curve; preliminary configuration of thermal power and energy storage installed capacity is carried out through a pinch point principle; and constructing an operation characteristic model of short-time energy storage, and obtaining an energy storage installed capacity and new energy utilization rate scatter set through a time sequence operation simulation method. And drawing a marginal effect curve of the new energy utilization rate based on a simulation result, and establishing an economic evaluation index of short-time energy storage. The method provided by the invention can effectively improve the consumption capability of new energy, optimize the capacity configuration of the short-time energy storage system, provide economic analysis indexes, and provide a scientific basis for planning and operation of a power system.

The invention relates to the technical field of agricultural development, and discloses a characteristic rural industry green planning system combined with economic analysis, and the system comprises a data collection and analysis module which is used for collecting and integrating policy information, environment data, economic data and market demand information; the environment evaluation and grading module is used for dividing the rural industrial area into a green multi-dominant production area, a pollution-free multi-dominant production area, a green less-dominant production area and a pollution-free less-dominant production area; the industrial planning module is used for designing production, processing, packaging and supply chain schemes of characteristic agricultural products and constructing a brand construction scheme in combination with regional historical and cultural characteristics; the economic analysis module is used for analyzing economic benefits of the industry, evaluating risks and providing an optimization scheme; and the intelligent auxiliary decision-making module simulates economic and ecological influences of different planning schemes. According to the method, intelligent and dynamic planning is realized through reinforcement learning, linear planning and a system dynamics model, and the scheme is quickly adjusted according to real-time environment, economy and policy data.

The invention discloses an office building energy-saving reconstruction method based on neural network optimization, and belongs to the field of office building energy conservation, and the method comprises the steps: carrying out the energy audit of a target building, and obtaining the field investigation data; calculating the field research data based on DeST software, and constructing a building energy consumption model; based on the building energy consumption model, performing energy consumption simulation on various external enclosure structure energy-saving reconstruction scheme combinations to obtain energy consumption data under different enclosure structure combinations; constructing an ANN neural network model, and inputting the historical data set into the ANN neural network model to obtain a prediction model; inputting the energy consumption data under different enclosure structure combinations into the prediction model to obtain an optimal energy-saving scheme; and performing technical economic analysis and environmental economic evaluation on the optimal energy-saving scheme, and generating an energy-saving transformation report.

The invention belongs to the technical field of power cost measurement and calculation, and particularly relates to a multi-type adjustment resource response cost measurement and calculation and economy analysis method. Comprising the following steps: S1, carrying out multi-type adjustment resource response cost calculation; s2, establishing a multi-type adjustment resource economy optimization configuration model considering the whole life cycle cost; s3, economic analysis of adjustment resource response in different scenes is carried out; according to the method, for typical adjustable electrical loads including an electric vehicle load, an air conditioner load and an electrolytic aluminum load, response characteristics of multiple types of adjustment resources are analyzed, and a response cost measuring and calculating method is provided; analyzing cost influence factors in the whole life cycle of the typical adjustable electrical load, designing an adjustment resource response model considering the whole life cycle cost, and proposing an economic optimization configuration model; and multi-scene economy analysis is carried out for typical scenes, supply-preserving scenes and consumption-preserving scenes of wind and light loads, and response cost and economic benefits of multi-type adjustment resources in multiple scenes are measured and calculated.

The invention discloses a method for evaluating low-efficiency sea, which evaluates and analyzes the low-efficiency sea by adopting a scientifically constructed evaluation index system, and is beneficial to identifying the low-efficiency sea, accelerating the implementation and exit of the low-efficiency sea and promoting the efficient development of marine economy. Therefore, decision support can be provided for policy formulators, and scientific basis can be provided for management and optimal configuration of marine resources. In addition, the method can also be applied to multiple fields of marine environment monitoring, marine economic analysis and the like, and has a wide application prospect.

The invention discloses a wind turbine generator life extension dynamic evaluation method and system based on multi-source data fusion, and belongs to the technical field of new energy. According to the method, multi-modal detection is carried out on key parts such as blades, a gearbox, a generator and a tower by collecting multi-source data such as basic parameters, historical operation data, environmental data and design files of a wind turbine generator, and residual life evaluation is carried out based on material performance, operation data and numerical simulation. And performing economic evaluation by combining cost-benefit analysis and investment payback period analysis, and finally comprehensively giving a life extension dynamic evaluation conclusion. The method solves the problems of data island, insufficient dynamic prediction capability, lack of economic analysis, low detection efficiency and the like in a traditional evaluation method, provides a scientific and comprehensive basis for the decision-making of the life extension of the wind turbine generator, and has remarkable economic benefits and engineering application values.

The invention discloses a power transmission and transformation project economic evaluation method, system, equipment and medium fusing adaptive fuzzy entropy weighting and a multi-target grey wolf optimization algorithm, and belongs to the technical field of power system economic analysis, and the method comprises the steps: constructing an economic index system, building a fuzzy membership matrix, and calculating an index weight through combining fuzzy entropy and information entropy; a comprehensive weight is generated by adopting a self-adaptive fusion mechanism, then a multi-target weighted evaluation model is constructed, and finally multi-target search is performed by utilizing a swarm intelligence optimization algorithm. According to the invention, by constructing a self-adaptive weighting mechanism fusing the fuzzy entropy and the information entropy and combining the global search capability of the multi-target grey wolf optimization algorithm, multi-index weight dynamic optimization and multi-target cooperative solution in the economic evaluation of the power transmission and transformation project are realized; the method effectively overcomes the limitation of a traditional method in the aspects of weight distribution subjectivity, insufficient index coupling processing and multi-target balance, and forms a closed-loop evaluation system from index processing to intelligent decision making.

The invention discloses a calculation method for waste aluminum optimal proportion and raw material cost in 6-series aluminum alloy round ingot smelting, which comprises the following steps of: firstly, determining suitability and maximum additive amount of waste aluminum: determining component calculation values of all elements according to a preset rule by comparing target alloy component requirements with actual components of the waste aluminum; and calculating the additive amount limited by each element, taking the minimum value of the additive amount as the theoretical maximum additive amount, and judging whether the economic threshold value is reached or not. And for the waste aluminum suitable for addition, cost-benefit analysis is carried out subsequently: the reference cost of not using the waste aluminum and the scheme cost of using the maximum addition amount of the waste aluminum are calculated respectively, and the economic feasibility of purchase and use is evaluated by comparing the reference cost and the scheme cost. According to the method, technical feasibility and economic analysis are combined, a quantitative decision support method is formed, whole-process optimization from casting matching to purchase decision is achieved, and the resource utilization rate is remarkably increased and the production cost is reduced while the stable quality of aluminum alloy products is guaranteed.

The embodiment of the invention relates to the technical field of simulation, in particular to a new energy hydrogen production system economic index evaluation method based on a simulation workstation and the simulation workstation, and the method comprises the steps that a building demand and an evaluation demand input by a user are acquired, and the evaluation demand comprises to-be-evaluated economic indexes and economic parameters selected by the user; selecting a corresponding simulation model from the simulation model library according to a building requirement, and building a new energy hydrogen production system model; setting economic parameters for the new energy hydrogen production system model according to evaluation requirements, operating the new energy hydrogen production system model, and recording simulation data in simulation operation; and after the simulation operation is finished, calculating an evaluation result corresponding to the to-be-evaluated economic index according to the recorded simulation data. According to the scheme, accurate economic data can be provided for economic analysis of a new energy hydrogen production project.

The invention relates to the technical field of economic analysis, in particular to an economic analysis device for economic management finance. Comprising a sand table, a base, a connecting line, a supporting frame, a fixed displayer, movable displayers, trundles, a movable support, a supporting mechanism and a pressing mechanism, the sand table is connected with the base through the connecting line, the supporting frame is connected to the top of the base, the fixed displayer is installed on the upper portion of the supporting frame, and the movable displayers are arranged on the left side and the right side of the fixed displayer. And shaft rods are arranged at the upper end and the lower end of the movable display. According to the invention, by introducing the adjustable movable display, the user can flexibly adjust the display angle and orientation according to the actual demand, so that the demand of watching from different angles by multiple persons is met, and team cooperation and discussion are promoted. The camera is unfolded to enlarge the field of view in use, and is retracted in a non-use state to reduce the volume, and is convenient to carry and store.

Generative Al systems and methods are provided to produce leading indicators of economic activity based on, for example, agricultural, fishing, mining, lumber harvesting, environmental, or ecological attributes and other factors determined from a range of available data sources. A consistent, semantic metadata structure is described as well as a hypothesis generating and testing system capable of generating predictive analytics models in a non-supervised or partially supervised mode. Users may then subscribe to the date for the use in economic forecasting.

The invention relates to the technical field of electronics, and discloses a comprehensive energy management and control method, device, equipment and medium considering economic analysis, and the method comprises the steps: solving an optimization model based on different forms of output flows in a comprehensive energy system, the energy quality coefficient of each form of flow and the unit economic cost of each form of input flow; obtaining the target output power of each device in the integrated energy system; and controlling the integrated energy system based on the target output power of each device in the integrated energy system. According to the method provided by the invention, the target output power of each device in the integrated energy system is obtained by solving the optimization model, and the integrated energy system is managed and controlled based on the target output power of each device, so that the integrated energy system can operate orderly according to the optimization scheme; deep energy conservation and equipment optimization of the comprehensive energy system are realized from the aspects of stream input and equipment economic input, the realization cost is lowest, and the economic benefit optimization of the system is promoted.

The invention discloses an energy flow and carbon flow monitoring, evaluating and optimizing system for an aluminum electrolysis production process, and belongs to the technical field of energy conservation, emission reduction and intelligent control in the metallurgical industry. The system design method comprises the following steps: designing an edge layer of the aluminum electrolysis production process energy flow and carbon flow control system, and inputting data collected by the edge layer into an energy flow-carbon flow coupling model in the cloud layer through the communication layer to execute analysis operation; an improved multi-objective genetic optimization algorithm is constructed in the cloud layer, and an optimal process parameter combination is obtained by optimizing an objective function; performing dynamic regulation and control, closed-loop feedback and exception handling operation through an execution mechanism of the edge layer; and performing comparative analysis and economic analysis on the designed aluminum electrolysis production process energy flow and carbon flow control system. Key parameters of an aluminum electrolysis process are monitored in real time through a multi-source data fusion technology, an energy efficiency-carbon emission correlation evaluation system is established in combination with big data analysis, and an electrolytic cell process parameter dynamic adjustment strategy is generated based on a self-adaptive optimization algorithm.

The invention provides a lithium metallurgy pollution reduction and carbon reduction multi-target performance evaluation method based on machine learning, and the method comprises the steps: carrying out the annual pollutant and greenhouse gas production and emission node carding and life cycle accounting of the whole production process of a lithium metallurgy enterprise based on a preset accounting boundary, determining a basic emission amount and a lithium metallurgy pollution reduction and carbon reduction scheme, and carrying out the calculation of the model. Carrying out life cycle accounting of pollutants and greenhouse gases on each lithium metallurgy pollution reduction and carbon reduction technology of the lithium metallurgy pollution reduction and carbon reduction scheme to obtain pollutant emission reduction and greenhouse gas emission reduction of each technology; based on each emission reduction amount, annual investment cost, operation and maintenance cost and annual economic benefit, economic analysis is carried out, and marginal emission reduction cost of each technology is calculated; according to the method, pollutant emission, greenhouse gas emission, each emission reduction and marginal emission reduction cost form a high-dimensional data set, a machine learning model is adopted to process the high-dimensional data set, evaluation results of each technology are output, and comprehensive quantitative evaluation of cooperative control effects of all pollutants and greenhouse gases is realized.

The invention relates to an AI-based automatic enterprise financial and economic analysis method, device and equipment and a medium, and the method comprises the steps: carrying out the conceptualized mapping of multi-source financial and economic data, and generating a conceptualized data set with financial semantic tags; reasoning prediction is carried out on the set based on a graph neural network, and an index prediction value and an interlayer dynamic attention matrix representing an internal reasoning process are generated; constructing a logic evidence chain by using the matrix, and generating an enhanced logic evidence chain conforming to financial logic through backtracking and screening; and finally, generating a visual analysis report supporting interactive traceability based on the evidence chain and the specific numerical value. According to the method, the information flow in the prediction model is converted into a traceable and verifiable professional logic chain, so that the problems that the prediction result of an existing AI financial analysis method is poor in interpretability and non-transparent in logic are effectively solved, and the credibility and auditing performance of the analysis result in professional decision making are remarkably improved.

The invention discloses a boiler heating surface soot blowing optimization method based on safety and economy analysis, and belongs to the technical field of coal-fired power plant operation optimization. The method comprises the following steps: acquiring historical operation data from a DCS (Distributed Control System), pre-processing the data, establishing an initial data set, determining a real-time ash and dirt coefficient by judging the load stability of a unit and calculating ideal and actual heat exchange coefficients of a heating surface, identifying an ash and dirt growth prediction model and predicting an ash deposition trend. The optimal soot blowing frequency and duration are solved by taking soot blowing net income maximization as a target and combining engineering experience constraints, the critical soot pollution coefficient is calculated, and soot blowing operation is triggered when the actual soot pollution coefficient exceeds the critical value on the premise that safety parameters such as the main reheat steam temperature and the hearth outlet temperature meet the standard. By accurately predicting the soot deposition state and optimizing the soot blowing strategy, energy consumption is reduced while equipment safety is guaranteed, soot blowing medium waste is reduced, and the economical efficiency and safety of boiler unit operation can be remarkably improved.

The invention relates to a reservoir physical property parameter prediction and evaluation system for oil-gas exploration, and aims to deal with exploration challenges under complex geological conditions. The system comprises a multi-source data acquisition module, a self-adaptive data processing module, a self-learning prediction module, a dynamic model correction module and a visual result display module. By integrating logging, core analysis, earthquake and historical exploration data, the system performs high-precision prediction on the porosity and permeability of the reservoir, and updates the model in real time through a dynamic correction technology to ensure the accuracy and reliability of a prediction result. In addition, the system also provides two-dimensional and three-dimensional visual display and uncertainty analysis functions, and assists a decision maker in identifying a high-potential reservoir area and making an optimal development scheme. The system has the interface connection capability with an external data management system, can realize automatic updating and economic analysis of data, and effectively improves the efficiency and success rate of oil-gas exploration.

The invention relates to an efficient refrigerating machine room system performance verification and optimization method, which comprises the following steps of: firstly, carrying out annual dynamic load calculation on a building, and establishing load characteristic data; determining a design performance index according to the load characteristic data; verifying the energy efficiency of the design scheme, and calculating the energy consumption and the energy efficiency of the cold source system; then system optimization and design scheme evaluation are carried out, and the optimal scheme of the cold source system is determined through technical economy analysis; and finally, storing feasibility schemes and optimal schemes obtained after iterative calculation of all different optimization measures and data thereof to form a callable database. According to the method, the annual energy efficiency ratio design target value of the efficient machine room cold source system is determined according to factors such as building functions, load characteristics and project positioning, then through target decomposition, cold source equipment model selection and verification of each sub-item index, under the principle that the whole life cycle cost is the lowest, through comparison and selection of different combination schemes, the energy efficiency ratio design target value of the efficient machine room cold source system is obtained. And selecting an optimal design scheme.

The present invention discloses an energy management platform and method for wind turbines in wind farms, and relates to the field of wind power generation technology, including data acquisition and monitoring systems, wind resource assessment and prediction, energy optimization and fault diagnosis, economic analysis and user interface, safety protection and system integration. The present invention, through the implementation of the data acquisition and monitoring system, makes the collection and monitoring of real-time data more efficient and accurate, enhances the quality of data and management efficiency, and improves the overall operation level of the wind farm. In terms of wind resource assessment and optimization, accurate wind speed and wind direction prediction can be achieved by combining historical data and real-time data. These prediction results provide energy optimization and fault diagnosis functions. The operating status of the wind turbine can be optimized according to the prediction results and grid demand, thereby maximizing the power generation and minimizing the cost. By reducing the downtime of the wind turbine, the economic benefits and operational efficiency of the wind farm are further improved.

The invention relates to an economic management analysis terminal display device which comprises a base, a box body is fixedly arranged at the top of the base, an economic analysis main body is arranged in the box body, a supporting plate is fixedly arranged at the top of the box body, driving grooves are formed in the two sides of the box body, and lifting columns are slidably connected into the driving grooves; a driving mechanism used for enabling the lifting columns to move up and down is arranged on one side of the driving groove, the tops of the lifting columns on the two sides penetrate and extend out of the supporting plate and are rotationally connected with a display screen, and an adjusting mechanism used for enabling the display screen to rotate is arranged on one side of the upper portion of each lifting column; a linkage assembly used for enabling the adjusting mechanism to synchronously act along with lifting of the lifting column is arranged on one side of the lower portion of the lifting column. The state of the display screen is adjusted at the same time through lifting of the display screen, the display screen gradually rotates to the vertical direction during lifting and gradually rotates to the horizontal direction during descending, the storage and protection effects on the display screen are achieved, and damage caused by collision when the display screen is not used is avoided.

The application discloses a park energy-carbon coordination early warning management and control method, relates to the technical field of energy saving and emission reduction and intelligent decision support, and comprises the following steps: establishing a unified atomic time reference, setting a unified time reference for a plurality of energy subsystems, generating a cross-source time anchor set under the unified time reference, and using the time anchor set to calibrate the sampling start time of each energy subsystem. The application realizes time alignment and real time sequence restoration of energy consumption data of multiple energy subsystems by establishing a unified atomic time reference and a cross-source time anchor set, and improves energy consumption fusion accuracy. By introducing conflict isolation and breathing time domain patching mechanism, the time distribution and load balance of peak value aggregation section are dynamically controlled, the energy consumption superposition amplification effect is inhibited, and the accuracy and stability of carbon emission reduction simulation and economic analysis results are ensured.

This invention discloses a simulation method for determining different snow storage material cover options. The method includes: a simulation method for snow storage experiments, including mathematical methods for calculating the total amount of solar radiation on any slope and mathematical methods for unsteady-state heat transfer; and a numerical method for simulating the performance of snow storage cover options, including finite difference methods and economic analysis methods. This method solves the existing problem of selecting snow storage cover material options for different regions and climate conditions.

The invention relates to the technical field of industrial economy analysis and power data mining, and provides a power utilization mode change-based industrial transfer implementation effect evaluation method, which comprises the following steps of: acquiring power utilization time sequence data before and after transfer; extracting multi-dimensional features; the relative change rate is calculated, and direction unification is carried out according to index'lifting / descending '; constructing a comprehensive effect index; performing grade judgment by adopting ordered judgment / ensemble learning; and outputting a result and confidence. An index system covering the dimensions of load, efficiency, stability and the like is constructed by establishing a power utilization mode base line and comparison before and after transfer, and an effect quantification mechanism and an integrated learning model with unified directions are introduced, so that the industrial transfer effect is objectively and interpretably evaluated and graded; the confidence coefficient adopts geometric weighting of calibrated probability, stability, integrity and time span, and the method can be selectively combined with synthetic contrast / causal recognition to eliminate hybrid influences of seasons, prices, meteorology and the like, so that the evaluation robustness is improved.

The invention relates to a high-temperature superconducting cable economical efficiency analysis method for urban power capacity increase, and belongs to the field of superconducting application. The method comprises the following steps: acquiring population data, electric vehicle permeability and charging pile configuration data of an urban area, and predicting the number of public charging piles and private charging piles newly added in the urban area; predicting a newly added load peak interval according to the predicted number of the public charging piles and the predicted number of the private charging piles in combination with an automobile charging coincidence rate; designing a superconductive low-voltage capacity increasing scheme based on the newly added peak load interval; acquiring system line loss data of the superconducting low-voltage capacity increasing scheme under different load conditions; and obtaining the annual operation and maintenance cost of the superconductive low-voltage capacity-increasing scheme based on the system line loss data, and carrying out economic analysis on the superconductive low-voltage capacity-increasing scheme based on the annual operation and maintenance cost. The objective of the invention is to solve the problems of lack of systematic economic evaluation means and difficulty in accurately judging the economic applicability of the high-temperature superconducting cable under the background of urban capacity increase in the prior art.

This invention discloses a multi-dimensional analysis system and method for regional economic development potential, aiming to solve the problems of scattered data, single dimensions, and subjective and lagging assessments in traditional regional economic analysis. It adopts a three-layer architecture: a data layer, a model layer, and an application layer. The data layer integrates multi-source data from statistical yearbooks, government information disclosure, the internet economy, and geospatial data, forming a unified analytical foundation through standardization and outlier processing. The model layer constructs a six-core dimension indicator system, including economic scale and industrial structure, and uses entropy weighting, TOPSIS, and regression analysis to achieve quantitative assessment, supporting dynamic updates and adjustments. The application layer outputs analysis results through visualization and customizable functions. This invention achieves deep integration of multi-source data, comprehensive characterization of multi-dimensional potential, and objective, accurate, and timely assessment results, adapting to various scenarios such as government decision-making and corporate investment, providing scientific and efficient decision support for high-quality regional economic development.

The invention relates to the technical field of data processing and economic analysis, and discloses a self-trade area tax intelligent analysis system fusing multi-dimensional economic indicators, which comprises a data fusion and factor extraction module, a causal pedigree identification module, a dynamic baseline modeling module, a compliance risk monitoring module, a pedigree adaptive reconstruction module and an anti-fact decision deduction module. The method comprises the following steps: firstly, extracting potential core factors in multi-dimensional economic indexes, constructing a causal conduction pedigree for reflecting a conduction relationship between the factors and tax indexes, and establishing a dynamic baseline model on the basis of the causal conduction pedigree; in the operation stage, the system evaluates the state of the model in real time by monitoring the structure sudden change risk and the systematic disturbance risk in parallel. According to the method, a closed-loop mechanism of risk monitoring and model self-adaption is established, so that the system can dynamically respond to external impact, the robustness and long-term effectiveness of analysis and prediction are guaranteed, and reliable support is provided for prospective decision making.