55 results about "Economic analysis" patented technology

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 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 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.

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.

This invention relates to the field of rural economic data analysis technology, specifically an artificial intelligence-based method for rural economic data analysis. The method includes: delineating an economic data perception domain in a geographic information system based on the administrative division vector data of the target administrative village; collecting multi-source heterogeneous economic data through a protocol parser of an agricultural IoT terminal and converting it into standardized economic behavior data; extracting entities using natural language processing technology to generate a structured rural economic behavior fact table; inputting the fact table into a pre-trained economic activity association model and constructing a rural industry relationship graph using a graph embedding algorithm; and calculating the centrality index of economic entities based on the graph topology to identify core operating entities. This method enables accurate processing and association analysis of rural economic data, clearly presenting industry relationships and providing effective technical support for rural economic analysis.

The invention provides a front-end asynchronous blocking rendering control method and system based on SSE streaming isomerous data, belongs to the field of Web front-end rendering control, and aims at realizing the stable rhythm and gradual rendering of streaming contents. Meanwhile, a chart placeholder pre-insertion and asynchronous initialization module is designed, and the chart is asynchronously rendered after data is completely returned, so that the situation that the chart is flash-back due to repeated redrawing of DOM nodes is avoided. A plurality of DOM (Document Object Model) container nodes are dynamically created and maintained through an HTML (Hypertext Markup Language) content and chart node hierarchical management module, so that text and chart elements are separately managed, content update each time only affects a current active container, and frequent page redrawing is avoided. According to the method, the rendering performance bottleneck in the prior art can be effectively solved, the front-end display stability and the user experience of the AI large model generation content are improved, and the method is suitable for complex front-end visualization application scenes in the fields of smart cities, economic analysis, data report automation and the like.

The invention discloses an economics analysis and risk evaluation method and system based on an enhanced retrieval agent, and belongs to the technical field of crossing of artificial intelligence and sociology. According to the method, a knowledge graph is constructed by integrating sociology and financial data, a thinking chain template is trained, and cross-layer calculation and evaluation are realized by using a layer-by-layer conduction model. The core of the method lies in establishing evaluation indexes and methods from a sociology calculation model to social financial data fluctuation, and the problem that an effective evaluation system is lacked in the prior art is solved. The method can more accurately reveal the influence of social factors on financial data, improves the reliability and practicability of the model, and is mainly applied to financial risk analysis and decision support.

The application discloses a kind of track traffic full life cycle economy estimation system based on multidimensional data, it is related to track traffic engineering economic estimation technical field, the system includes following component parts: data acquisition module, time sequence linkage mapping module, substage estimation model module, feedback correction module and dynamic output module;The application is through covering track traffic full life cycle, establishes effective association, to substage estimation model accurately calculates each stage economic cost, provides solid data support for economic analysis;Dynamic feedback correction mechanism is built, real-time response deviation changes, improve estimation accuracy;Whole-process closed-loop optimization design, solve prior art defects, adapt to project dynamic change, provide timely reliable reference for project full cycle economic management.

The application provides a wind power hydrogen production system economic analysis method and device based on a dedicated line power supply mode. The wind power hydrogen production system comprises a heating device for maintaining the temperature of an electrolytic cell within a preset temperature range. The method comprises the following steps: inputting preset wind power output power into the hydrogen production system, determining the size relationship between the wind power output power and the minimum rated power and the standard rated power, and determining the interval of the wind power output power; determining the actual power consumption and the working temperature of the hydrogen production system based on the wind power output power in different intervals; determining the total hydrogen production and the total power consumption of the hydrogen production system within a preset time according to the correlation between the current working temperature, the current actual power consumption and the hydrogen production, and determining the total operation income of the hydrogen production system. The application quantitatively analyzes the system economy under different input conditions or control strategies of the wind power hydrogen production system based on the dedicated line power supply mode under the condition that the alkaline electrolytic cell has a shutdown heat preservation function.

The invention relates to a pollution and carbon reduction and technical economy multi-target analysis method and system in the lithium metallurgy industry, and belongs to the technical field of environment and economy collaborative evaluation in the lithium metallurgy industry. According to the technical scheme, a pollutant and greenhouse gas life cycle accounting model covering a basic production system, an auxiliary production system, an auxiliary production system and a power generation system is constructed, and the emission amount is calculated by adopting an emission factor method and a classification actual measurement method. Meanwhile, a technical economic analysis model is constructed to calculate marginal emission reduction cost of emission reduction measures and form a marginal emission reduction cost curve, then collaborative emission reduction economic indexes brought into a greenhouse gas emission transaction plan and an environment tax mechanism are calculated, and multi-target performance collaborative evaluation is achieved in combination with regulatory factors. And finally, constructing a comprehensive evaluation framework by adopting a modular architecture. The technology can solve the problems of lagging of traditional evaluation data, narrow accounting range and lack of collaborative evaluation, improves the evaluation accuracy and universality, and provides support for pollution and carbon reduction and related decisions in the lithium metallurgy industry.

The invention relates to the technical field of economic analysis, in particular to a method for identifying an enterprise attribution industry chain link, which comprises the following steps of: capturing text information of attributes or characteristics of an enterprise to be attributed, the information generally comprises product names, product descriptions, product solutions, enterprise qualification information, enterprise supplier names and enterprise customer names; and performing word segmentation processing on the obtained text information, using a word segmentation dictionary as a word segmentation dictionary of a target industry chain, and removing nouns which have word frequencies higher than a first specified threshold value and are not essential in a word segmentation result. According to the method, a high-frequency vocabulary library, a supplier weight library and a customer weight library of each link of a target industry chain are constructed, then information of target enterprise products, customers, suppliers and the like is captured and subjected to word segmentation, and matching with the vocabulary library, the supplier weight library and the customer weight library of each link is carried out, so that the affiliated link node is positioned; the method has the characteristics of objectivity, high accuracy and less time consumption.

The utility model discloses a transportation economy analysis display device, which comprises a base, a support and a display screen, the support is fixedly connected to the upper surface of the base, and the display screen is arranged at the upper end of the support. The base, the support, the display screen, the adjusting frame, the auxiliary supporting device, the expansion assembly, a push plate, a supporting plate, an extrusion rod, a containing groove, a fixing rod, an idler wheel, a linkage assembly, a rotating shaft, a rotating disc, a stroke groove, a torsion groove, a positioning assembly, a positioning rod, a lock head, a push spring, a pull button, an adjusting groove and a moving shaft are used in cooperation. The problem that after the height of the display screen is increased, the display screen cannot be stably supported enough by the base due to the fact that the height of the display screen is increased, and the display screen is unstable and prone to toppling over is solved.

The application provides a kind of integrated energy system capacity planning method and system, belong to integrated energy station capacity configuration technical field, including: the reversible solid oxide cell power generation / hydrogen production system model and integrated energy system model are constructed;The mixed integer linear programming model of the integrated energy system model is established, the objective function is system thermal power total cost, constraint condition includes energy balance, mass balance, reversible solid oxide cell full working condition constraint and each component constraint;Input renewable energy output time series data, user demand time series data and component technical and economic parameters;Solve the solution of objective function under constraint condition, output integrated energy system each component optimal capacity configuration and each typical day under different time scene operation optimization result. By considering the dynamic change of reversible solid oxide cell efficiency with its load in capacity planning process, it is favorable to improve the accuracy of capacity optimization and economic analysis of system components.

The invention discloses a short-term offshore wind power prediction method, and the method comprises the steps: S1, collecting wind power time sequence data, and carrying out the preprocessing of the wind power time sequence data; s2, realizing fine division of the wind power plant group based on multi-source fusion spatial-temporal clustering analysis, and obtaining spatial-temporal correlation among the wind power plants; s3, constructing an offshore wind power prediction model based on a bidirectional space-time convolution module, a space-time attention module and a residual feature fusion module, and performing preliminary prediction on the offshore wind power; s4, performing maximum overlapping double-domain cooperative decomposition on the prediction error of the preliminary prediction of the offshore wind power, and extracting error information of different frequency bands; s5, introducing an attention mechanism to dynamically distribute weights, focusing key information to drive model feedback learning, improving offshore wind power prediction precision, and outputting a prediction result; and S6, performing comparative analysis, error analysis and economical efficiency analysis on the output prediction result. The problem that an existing offshore wind power prediction model is poor in prediction precision is solved.

The invention discloses an economic data analysis method and device and a medium, and relates to the field of data processing.The method comprises the steps that a data analysis demand input by a user is received and analyzed, a corresponding economic analysis type and demand information are extracted, and a to-be-queried data index list is determined based on the demand information; the economic analysis types comprise attribution analysis, trend prediction and influence simulation; obtaining original data corresponding to the data index list through a plurality of preset economic data sources, and constructing an economic data set; calling a target economic analysis model corresponding to the economic analysis type, and outputting an economic analysis calculation result based on the economic data set through the target economic analysis model; and based on the economic analysis calculation result, generating an economic data analysis report so as to construct and display an economic data analysis map. By accurately routing the natural language requirements to the special economic analysis model, the spanning from simple data query to deep economic insight is realized.

The present disclosure provides a real-time data management and statistics method and system for wide load index of thermal power generating unit. The method comprises: collecting and managing multi-source real-time operation parameters from SIS; dividing multiple continuous load intervals based on rated power; in a statistical period, judging the interval to which the real-time load belongs, and respectively calculating the statistical values of performance indexes in each interval. Through pre-data management and fine load segmentation statistics, the present disclosure solves the problems of poor data quality and different statistical caliber under wide load operation, realizes accurate calculation of indexes, and provides reliable data support for unit operation optimization and economic analysis.

The invention belongs to the technical field of comprehensive energy service and energy storage, and relates to a big customer comprehensive energy online and offline full-cycle service method and system, the system and the method are driven by data, user load characteristics are automatically analyzed to identify peak-valley difference users, energy storage economic optimal capacity is calculated in physical and investment constraints by adopting a traversal algorithm, and energy storage efficiency is improved. An executable charging and discharging strategy is generated, automatic report generation and multi-terminal interaction are achieved, online and offline platforms are integrated, full-period service management from customer intention and technical analysis to operation is achieved, and the problems that enterprise user energy storage investment decision depends on experience, technical and economic analysis is complex, and the service process is split are solved. The technical effects of improving investment decision scientificity, ensuring global optimization of configuration, reducing energy consumption cost and optimizing service efficiency and customer experience are achieved.

The invention relates to a pollution and carbon reduction and technical economy multi-target analysis method and system, belongs to the field of industrial environment and economy collaborative evaluation, and is suitable for high-pollution and high-carbon emission industries such as thermal power, cement and steel. According to the scheme, three industrial production systems and whole-process emission category accounting are covered, a hybrid model is adopted to calculate emission, an equivalent value, a collaborative emission reduction degree and marginal emission reduction cost, and a high-dimensional data output technology priority is processed through a random forest, a support vector machine and LASSO linear regression. The problems of incomplete accounting, low precision, difficult high-dimensional processing and the like in the prior art are solved, quantitative reference is provided for technology screening and policy making, and pollution reduction, carbon reduction and economic collaborative development are promoted.

The invention discloses an economic trend analysis system based on big data, and belongs to the technical field of data analysis, and the system comprises a data collection module which collects data related to an enterprise market environment from multiple data sources according to a preset collection rule and frequency, and carries out the preprocessing of the collected data, the data storage module adopts a distributed storage architecture to carry out classified storage on the preprocessed collected data, carries out classification according to the source, the type and the time dimension of the data and establishes a corresponding index, and the economic analysis module carries out multi-dimensional analysis on the data processed by the data processing module to obtain a current market environment analysis result. The trend prediction module establishes a prediction model, predicts in combination with a current market environment analysis result, historical data of an enterprise and a development strategy, obtains an enterprise development trend analysis result, can provide rich and accurate data support for enterprise development trend analysis, helps the enterprise to better cope with market competition, and improves the enterprise development trend analysis efficiency. And the competitiveness and economic benefits of enterprises are improved.

The application claims a cascaded feature extraction method for agricultural product price prediction, belonging to the technical field of artificial intelligence and agricultural economic analysis. The method adopts a three-level cascaded processing architecture: first, a filter-type coarse screening is realized through K-neighbor mutual information estimation, realizing preliminary dimension reduction; second, embedded feature selection is realized through an XGBoost model, and core prediction features are screened out; finally, multi-scale enhancement is realized through discrete wavelet decomposition on the time series core features, and trend and fluctuation components with clear physical meaning are constructed. Based on the processed enhanced features, a bidirectional long short-term memory network prediction model is constructed, and an ablation experiment of the system is designed to verify the effectiveness of each level of processing. Through systematic feature extraction and enhancement, the precision and stability of agricultural product price prediction are significantly improved, providing reliable technical support for market early warning and agricultural economic decision-making.

The invention discloses a park shared energy storage optimal configuration and economical efficiency analysis method and system considering energy conservation and emission reduction requirements. By introducing the carbon emission constraint, the energy consumption and emission model of the park multi-type equipment is established, and coordinated optimization of the park energy system between economy and environmental protection is realized. The method comprises the following steps: firstly, comprehensively considering shared energy storage capacity configuration and park equipment operation characteristics from a planning level, secondly, constructing an optimization model taking park comprehensive benefit maximization as a target from an operation level, covering shared energy storage operation constraints, energy power balance constraints, capacity planning constraints, equipment operation constraints and the like, and finally, constructing an optimization model taking the park comprehensive benefit maximization as a target. A mixed integer linear programming method is adopted to solve the model, optimization characteristics of discrete decision and continuous control are considered, and global optimality and implementability of a model solution are ensured. According to the method, the energy utilization efficiency of the park and the economic benefits of the energy storage system can be effectively improved, the carbon emission level and the energy consumption can be remarkably reduced, and a technical path capable of being popularized is provided for achieving green, low-carbon and efficient operation of the park.

The invention discloses a power transmission and transformation project cost technical and economic index analysis method, relates to the technical field of electric power project technical and economic analysis, and aims to solve the problem that a conventional economic index analysis method is inconvenient to dynamically adjust according to project progress and market change. The method comprises the following steps of: S1, collecting and processing data; s1.1, data source integration; a database, Internet of Things equipment and cloud service are integrated, and comprehensive, automatic and real-time collection of related data of the power transmission and transformation project is achieved; s1.2, data processing is carried out; data cleaning, verification and standardization processing technologies are adopted, the accuracy and reliability of data are ensured, five-calculation data are formed in the modes of estimation, budget, budget, settlement and final settlement, and corresponding processing flows are established respectively; the method has the advantages that real-time adjustment and optimization are carried out according to engineering progress and market changes, and the timeliness and applicability of an evaluation result are ensured.

The invention belongs to the field of regional economy analysis, relates to a gravitational model technology, and aims to solve the problem that it is difficult to simply exclude economic indexes of a target region to construct pure external economic influence indexes in the prior art, in particular to a regional economy development internal and external driving effect separation method based on a gravitational model. Comprising the following steps of data acquisition, index construction, regression analysis and effect separation. According to the method, by constructing the external influence field intensity index irrelevant to the characteristics of the target area, the problem that internal economic parameter interference is difficult to eliminate by a traditional model is effectively solved, and the space attenuation characteristic of the gravitation model can accurately describe the distance attenuation rule of the economic influence; a residual error separation technology after regression analysis can quantitatively distinguish internal and external driving effects; the index system established by the method is completely based on external region characteristics, endogenous interference is avoided, and accurate quantitative separation of the driving effect is realized through combination of field intensity calculation and statistical analysis.

This invention discloses a peak-valley electricity pricing intelligent equipment control system based on multimodal video analysis, including a video acquisition module, an electricity pricing strategy acquisition module, an AI multimodal analysis engine, a dynamic scheduling controller, and an economic analysis module. The advantages of this invention compared to existing technologies are: Instead of focusing solely on energy costs in traditional equipment control, this invention introduces equipment lifespan and carbon emissions as optimization objectives, constructing a multi-objective optimization model to achieve synergistic optimization of economic and environmental benefits, aligning with the global trend of low-carbon development. Through this innovation, in industrial applications, the total lifespan cost of equipment can be reduced by 15%-20%, and carbon emissions reduced by 10%-15%.

This invention discloses a method, system, equipment, and medium for multidimensional data analysis and supply chain collaborative decision-making, belonging to the field of intelligent economic analysis and decision optimization technology for the supply chain. The method includes: collecting multidimensional raw data; preprocessing the multidimensional raw data through regression analysis; extracting latent components of independent and dependent variables; constructing low-dimensional feature representations; purifying the output value of the power grid company through a first-level algorithm; establishing the correction relationship between the output value of upstream and downstream enterprises and long-term cointegration and short-term errors; performing regression analysis on the purified independent and dependent variables; decomposing the output value of the power grid company; and generating supply chain collaborative adjustment decision-making suggestions. This invention provides precise support for supply chain collaborative adjustment decisions, overcoming the limitations of existing methods in terms of insufficient flexibility and insufficient consideration of the combined influence of multiple external factors when facing complex electricity demand, thus improving the accuracy and effectiveness of electricity analysis under volatile market conditions.