69 results about "Potential analysis" patented technology

The invention belongs to the technical field of three-dimensional geologic modeling, and particularly relates to a three-dimensional geologic model construction method based on multi-source data fusion, and the method comprises the steps: 1, extracting drilling data, and constructing a drilling database; 2, constructing a topographic and geomorphic surface model, and completing the fusion of topographic and geomorphic data and drilling data; 3, coupling information of strata, rock mass, fracture, ore body and the like, and constructing a geologic body comprehensive model; 4, extracting geophysical and geochemical data, and constructing a geophysical model and a geochemical model; and 5, coupling the borehole database, the landform surface model, the geologic body comprehensive model and the geophysical model, and constructing a multi-source data fused three-dimensional geologic model. The method improves the accuracy and precision of the three-dimensional geologic model, improves the data processing and analysis speed, improves the data analysis capability and depth, provides technical support for uranium resource potential analysis and prediction exploration, and guides uranium exploration.

The invention relates to the technical field of multi-source information analysis, in particular to a niobium-tantalum metal ore metallogenic evaluation system based on multi-source information analysis, which comprises a geologic structure association module, a mineral distribution interpretation module, a metallogenic environment adaptation module, a spatial feature analysis module and a potential region judgment module. According to the method, by introducing a multi-source data analysis and fusion method, the evaluation precision and comprehensive capability of resource exploration are effectively improved, analysis after information fusion is combined with relevance and spatial modes of different data types, it is ensured that mineralization potential evaluation is more accurate, the limitation of a single data source and manual analysis is overcome, and the method is suitable for popularization and application. According to the method, the identification precision and reliability of the mineralization law are improved, the potential area can be identified more accurately, resource potential analysis is optimized in combination with the adaptability of the mineralization environment, the efficiency and accuracy of determining the mineralization area are remarkably improved, the problems of information isolation and analysis deviation in a traditional method are avoided, and the scientificity and the practical application value of the exploration process are enhanced.

The invention discloses a large-scale infrastructure intensive land-saving development potential analysis method and system, and the method comprises the following steps: 1) constructing a large-scale infrastructure stock land geospatial database based on Arcgis, and collecting the related element data of the large-scale infrastructure stock land; 2) extracting land suitable for optimizing stock of large infrastructures, and screening and extracting municipal public facility land and road and traffic facility land which are larger than 5 hectare in land scale and are not dangerous; 3) constructing an AHP-entropy weight method hybrid model, optimizing the weight by means of a genetic algorithm to establish a site selection evaluation system, and comprehensively evaluating the alternative land; 4) constructing a land development population service coverage model to obtain the number of each development land service population; and 5) guiding a land redevelopment time sequence in combination with the comprehensive score of the alternative land and the number of serviceable population. The method provides a path for improving the utilization efficiency of land resources, eliminating the neighborhood effect of large infrastructures and realizing high-quality development.

The invention provides an ensemble forecast multi-scale four-dimensional initial value disturbance method based on incremental analysis updating, which comprises the following steps of: firstly, separating initial value disturbance into disturbance of large, medium and small scales by using a scale separation method, and respectively calculating disturbance dispersion of different scales and mutual influence dispersion among different scales; the mutual influence dispersion between different scales is dynamically adjusted in real time by using an adjustment coefficient in combination with a potential analysis method; then, corresponding re-scale coefficients are distributed for different scales, disturbance dispersion of the corresponding scales is adjusted, and then a multi-scale disturbance field is obtained; and finally, adding a disturbance increment formed by a multi-scale disturbance field and a time coefficient in a disturbance mode integration process by utilizing an increment analysis updating method until ensemble forecasting is finished. According to the method, the problems of fast dispersion attenuation, disturbance and weather situation mismatch and the like in traditional initial value disturbance are effectively solved, and the forecasting precision of severe disastrous convective weather is improved.

The invention discloses a regional carbon emission potential analysis and redundant carbon dioxide distribution method and system, and belongs to the technical field of carbon emission reduction potential analysis, and the method comprises the steps: S1, determining a to-be-evaluated region, and constructing a carbon dioxide emission influence factor regression model; s2, determining an input index and an output index of each region in any time period, and constructing an unexpected output super-efficiency SBM-DEA model to obtain a comprehensive efficiency value of each region and redundancy of an expected output index and an unexpected output index; s3, analyzing the carbon emission reduction potential of each region by using the redundancy of the unexpected output indexes; s4, under the constraint of the redundant carbon dioxide distribution objective function with the energy consumption constraint and the equipment health state constraint, searching the redundant carbon dioxide distribution proportion of each enterprise in each region through a GeneticAlgorithm algorithm; and S5, verifying the redundant carbon dioxide distributed by each enterprise, and carrying out necessary adjustment.

The invention discloses an air conditioner load demand response potential analysis method and system. The method comprises the following steps: acquiring historical load and influence factor data of a building air conditioner system, and performing correlation analysis and screening to obtain key influence factor characteristics; constructing a first air conditioner load prediction model based on the screening result and a historical load curve, and pre-training the first air conditioner load prediction model; the pre-training model is adjusted through the historical load and feature data of the target building and the real-time collected data, and a second air conditioner load prediction model is obtained; and based on the second air conditioner load prediction model, the final demand response potential value is obtained by changing the input air conditioner temperature set value and carrying out difference calculation on the model prediction result output. According to the method, different environments and requirements can be adapted, cooperative work is realized by utilizing high-performance computing resources of the cloud and real-time data of the terminal side based on a transfer learning framework, and the prediction precision and the operation efficiency of the model are effectively improved.

The invention relates to the technical field of special equipment accident prevention, and discloses a special equipment accident prevention optimization potential analysis method and system based on a TRIZ functional model. Comprising a data collection module, a function analysis module, an optimization potential analysis module, a decision support module, a system operation module, a user interface module, a data storage module, a system maintenance module and a user management module. A data collection module, a function analysis module, an optimization potential analysis module, a decision support module, a system operation module, a user interface module, a data storage module, a system maintenance module and a user management module are integrated, so that potential accident risks of the special equipment can be effectively identified and prevented, and the safety of the special equipment can be improved; the risk of accident occurrence is reduced, a scientific basis can be provided for continuous improvement of equipment by optimizing potential analysis, and the efficiency and effect of accident prevention are improved, so that the safety management level of the whole industry is improved.

The invention discloses a digital intelligent marketing method and system applying an AI large model, and relates to the technical field of digital intelligent marketing, and the method comprises the following steps: multi-source data collection, user activeness analysis, potential analysis, marketing comprehensive evaluation, user rating through a marketing strength algorithm in combination with the data of an activeness analysis algorithm and a potential analysis algorithm, and marketing evaluation. According to the method, users are divided into low-marketing users, medium-marketing users and high-marketing users, different marketing intensities are adopted for the users of different grades to optimize resource allocation, marketing content generation and pushing according to different marketing intensities, and the method has the advantages that the activity degree and purchase potential of the users are quantitatively evaluated through an activity analysis algorithm and a potential analysis algorithm; in combination with a marketing strength algorithm, the users are graded according to a set threshold, high-grade users are ensured to obtain more marketing resources, reasonable resource allocation is realized, the product sales volume and the customer conversion rate are improved, and the marketing quality is remarkably improved.

The invention belongs to the field of oil exploitation, particularly relates to an intangible production potential analysis and evaluation method and system for a sucker-rod pump well of a pumping unit, and aims at solving the problems that in the prior art, evaluation factors are single, and effective analysis and detection cannot be achieved. The method comprises the following steps: setting a first layer factor set which affects the intangible upper production potential of a sucker-rod pump well of a current oil pumping unit, and setting a second layer factor set based on the first layer factor set; determining an evaluation value of each factor set in the second-layer factor set on the intangible production potential, and calculating a backup set based on the evaluation value of each factor set in the second-layer factor set on the intangible production potential; determining an influence weight coefficient of each influence factor in the second layer factor set on the intangible productivity potential; constructing a weight coefficient set by using all the influence weight coefficients; and according to the standby selection set and the weight coefficient set, the intangible production potential of the current pumping unit sucker-rod pump well is calculated. Various factors are considered, effective analysis and detection can be achieved, and the method is scientific and reasonable.

This invention discloses a method for predicting load time-series adjustment potential based on error correction, comprising the following steps: S10, acquiring raw load response data; S20, performing RF processing on the raw load response data to obtain complete time-series data; S30, using SSA decomposition to extract time-series sub-modes and performing potential prediction, then summing the predictions of each sub-mode to obtain a preliminary time-series adjustment potential prediction result; S40, subtracting the preliminary time-series adjustment potential from the raw time-series adjustment potential to obtain the time-series adjustment potential error, and using a dynamic mode decomposition algorithm to correct the time-series adjustment potential error in the preliminary time-series adjustment potential prediction result to obtain the final time-series adjustment potential prediction result. This invention solves the problems of excessive complexity and limited generalization ability in traditional time-series potential prediction, effectively handles the influence of data disturbances, and improves the accuracy of potential analysis.

The present application relates to the technical field of industrial load frequency modulation, and particularly relates to a polysilicon plant frequency modulation potential analysis method and system, which comprises the following steps: constructing a mathematical model of a polysilicon production process; establishing a benchmark operation curve optimization model, solving the optimal production operation curve and the corresponding load baseline of the enterprise under normal production state; using an inverse optimization method to deduce the decision preference of the enterprise under different operation conditions, generating operation curves corresponding to multiple operation modes; progressively analyzing the frequency modulation capacity of the polysilicon plant, analyzing the frequency modulation feasibility and economy under different operation conditions; determining the frequency modulation potential interval of the polysilicon plant under different operation conditions, and outputting an optimized frequency modulation scheme. Through the present application, the problem that the prior art cannot accurately evaluate the frequency modulation potential under the condition of meeting the complex production process and operation constraint conditions of polysilicon is effectively solved, and the real potential of the polysilicon plant participating in power frequency modulation under different operation conditions is systematically analyzed.

The invention relates to an adjustable potential analysis method for adjustable load resources in a building park. The method comprises the following steps: constructing an adjustable load resource adjustment power model in the building park; calculating the dynamic carbon emission of the adjustable load resource; establishing an adjustable load resource multi-target aggregation model; and calculating the comprehensive adjustment potential of the adjustable load resources in the building park. The low-carbon contribution of each adjustment behavior of the park is accurately quantified, and the load resources are promoted to be upgraded from one-way economic response to multi-dimensional collaborative response; the accuracy and credibility of potential evaluation are remarkably improved, the problem of deviation caused by extensive aggregation is solved, and a reliable data basis is provided for power grid demand response and marketization transaction; a key decision basis is provided for the park to participate in power grid interaction, the transformation of the building park to a flexible resource polymer is powerfully promoted on the premise of ensuring the safety and comfort of energy consumption, and a solid support is provided for the construction of a novel power system and the digital transformation of park energy.

The embodiment of the invention discloses a retail potential analysis method and device for retailers, equipment and a storage medium, and the method comprises the steps: obtaining retail attribute data and historical retail data corresponding to a plurality of to-be-analyzed retailers; clustering the plurality of to-be-analyzed retailers based on the retail attribute data to obtain a target clustering result corresponding to the to-be-analyzed retailers; classifying the to-be-analyzed retailer based on the historical retail data to obtain a target classification result corresponding to the to-be-analyzed retailer; and according to the target clustering result and the target classification result, determining a retail potential analysis result corresponding to the to-be-analyzed retailer. According to the technical scheme provided by the embodiment of the invention, the problem of poor retailer classification effect in the prior art is solved, the retailer can be comprehensively classified and analyzed based on various types of data, and the effectiveness and accuracy of retailer classification are improved.

The invention discloses a regional energy hosting collaborative management system and method based on a cloud platform, and relates to the technical field of data analysis. The system comprises a regional grid division and correlation analysis module, a data verification and feature extraction module, a load prediction and collaborative potential analysis module and a scheduling path optimization and instruction execution module. The regional grid division and association analysis module collects geographical and energy node information by means of a cloud platform, divides regional unit grids and constructs an energy flow association graph; the data verification and feature extraction module verifies and screens multi-energy historical data, calculates conversion efficiency and constructs a coupling feature matrix; the load prediction and collaborative potential analysis module predicts a multi-energy load, searches a surplus grid, evaluates collaborative potential and generates a supply and demand gap matrix; and the scheduling path optimization and instruction execution module screens an optimal scheduling path, sends an instruction to the energy equipment and updates the association diagram.

The present application relates to the technical field of multi-source information analysis, in particular to a niobium-tantalum metal mine mineralization evaluation system based on multi-source information analysis, which comprises a geological structure correlation module, a mineral distribution interpretation module, a mineralization environment adaptation module, a spatial feature analysis module and a potential area determination module. In the present application, the multi-source data analysis and fusion method is introduced to effectively improve the evaluation accuracy and comprehensive ability of resource exploration. The analysis after information fusion combines the correlation and spatial pattern of different data types to ensure that the mineralization potential evaluation is more accurate. The limitations of single data source and manual analysis are overcome to improve the identification accuracy and reliability of the mineralization regularity. The potential area can be more accurately identified. The adaptability of the mineralization environment is combined to optimize the resource potential analysis, significantly improve the efficiency and accuracy of the mineralization area determination, avoid the problems of information isolation and analysis deviation in the traditional method, and enhance the scientificity and practical application value of the exploration process.

The present application relates to the technical field of intelligent construction material management and wisdom logistics, in particular to a construction material intelligent demand management supply system based on predictive modeling; comprising data acquisition, trust quantification, entropy value analysis and strategy determination unit; the system compares the predicted data and the on-site reported data through the space-time graph neural network, and calculates the trust weight; the core is to calculate the scheduling entropy value according to the trust weight and the transport capacity resources, and compare it with the collapse threshold; when the entropy value triggers different states, the system adaptively generates cost priority or reverse saturation supply instructions; the present application establishes a dynamic credit potential analysis mechanism, effectively identifies malicious false reporting, and solves the problem of data distortion caused by interest game.

The invention discloses an information recommendation method and device, equipment, a medium and a program product. The method comprises the steps of obtaining a multi-source data set; performing multi-dimensional association on the equipment performance data, the cloud platform resource data and the security equipment data according to a target identifier to obtain a global data link diagram corresponding to the target identifier; performing risk detection based on the security equipment data to obtain a risk detection result; performing information analysis based on the equipment performance data, the cloud platform resource data and the security equipment data to obtain an information analysis result; safety potential and performance potential analysis is carried out according to the global data link diagram, the risk detection result and the information analysis result, an information list is obtained, and the information list comprises a target risk customer and a corresponding product deployment list and / or product optimization list. According to the embodiment of the invention, data can be comprehensively collected, information recommendation is performed by integrating multiple dimensions, and information can be flexibly and accurately recommended.

The invention relates to the technical field of intelligent management of cabinet air conditioners, in particular to a healthy and energy-saving management method for a cabinet air conditioner based on digital twinning. Comprising the following steps: constructing a high-fidelity digital twinborn model of a cabinet and a cabinet air conditioner; the method comprises the following steps: acquiring operation data and environment data in real time through a sensor group deployed on a physical cabinet and a cabinet air conditioner, and synchronizing the data to a digital twinborn model; based on the synchronized digital twinborn model, health state evaluation and fault prediction are carried out; based on the health state evaluation result and the real-time operation data, energy-saving potential analysis and optimization strategy simulation are carried out through a digital twin model, and an optimal control instruction is dynamically generated and executed to the physical cabinet air conditioner; and feeding back execution result data of the physical cabinet air conditioner to the digital twin model to realize self-learning and dynamic correction of the model. The invention provides a novel intelligent management method which can deeply couple the health state and energy-saving operation and has prediction and optimization capabilities.

The invention belongs to the crossing field of shipbuilding and electrical engineering, and discloses a shipbuilding process flexible scheduling method based on adjustable potential analysis and a related device, and the method comprises the steps: responding to dynamic disturbance information, and updating a state task network diagram and a scheduling diagram of a shipbuilding process; according to the updated state task network graph and the scheduling graph of the shipbuilding process, dynamic adjustable potential of each task of the shipbuilding process is obtained by combining the dynamic adjustable potential model of each task of the shipbuilding process; and based on the scheduling constraint optimization model, according to the updated state task network diagram and scheduling diagram of the shipbuilding process and the dynamic adjustable potential of each task, generating a flexible scheduling result of the shipbuilding process. An optimal scheduling path can be selected in a disturbance scene to dynamically generate an adjustment strategy, so that the toughness of a production system is remarkably improved; meanwhile, based on dynamic adjustable potential analysis, the adjustment level and the flexible boundary of each task can be accurately identified, and real-time scheduling optimization and intelligent configuration of the flexible manufacturing system are supported.

This invention belongs to the field of carbon asset assessment technology, specifically relating to a method and system for carbon asset potential analysis and assessment based on multi-indicator comprehensive evaluation. The method includes the following steps: generating correction factors based on historical emission data of carbon assets; correcting historical emission data using the correction factors to obtain corrected emission values; and determining the assessment level of the carbon asset based on the corrected emission values. This invention identifies peak and trough points in time series data to define peak and trough periods, compares the average emission value within a period with the global average emission value to determine whether it belongs to positive or negative fluctuations, and sets corresponding adjustment parameters. This qualitatively classifies and quantitatively characterizes historical fluctuations, identifying their existence and revealing their specific nature, providing dynamic characteristic basis for subsequent carbon asset potential analysis and assessment, thereby improving the accuracy of the assessment results.

The invention relates to the technical field of data processing, in particular to a post capability analysis system based on learning condition information, and the system comprises a score quantification unit which is used for collecting subject scores and subject credits of a user, and carrying out the calculation to obtain a comprehensive skill value and a professional skill value; the modeling unit is used for constructing a learning detection model; the score detection unit is used for collecting detection parameters of the learning detection model completed by the user; the potential analysis unit is used for calculating and generating a comprehensive potential value and calculating and generating a professional potential value; the concentration analysis unit is used for calculating a concentration degree value; the ability analysis unit is used for calculating a generation ability value based on the comprehensive potential value, the professional potential value and the concentration degree value, and generating a learning situation ability model; according to the invention, the above units cooperate with each other, so that the accuracy of the post capability analysis system based on the learning condition information is further improved while the learning state of the student is effectively evaluated.

The method comprises the following steps: comprehensively monitoring and analyzing energy efficiency and carbon efficiency data of the operation stage of the public building to obtain energy efficiency and carbon efficiency analysis data of the operation stage of the public building and an energy efficiency and carbon efficiency improvement potential analysis and diagnosis report; calculating budgeting management data according to the energy efficiency and carbon efficiency analysis data in the operation stage of the public building; and formulating an energy efficiency and carbon efficiency management and control strategy according to the budgeted management data and the energy efficiency and carbon efficiency improvement potential analysis and diagnosis report. By generating the energy efficiency and carbon efficiency improvement potential analysis report, performing public building energy budget management calculation and dividing the public building energy use space structure, and formulating different subdivided space energy use control strategies, the problems of unclear energy supply and use characteristics, unscientific energy use planning, extensive energy use management and control modes, low energy efficiency and high energy efficiency in the operation stage of the public building are effectively solved. And the public building is assisted to efficiently realize energy conservation and carbon reduction.

The invention discloses a power distribution network demand response capability dynamic prediction and potential analysis method based on deep learning, and belongs to the field of intelligent power distribution network optimization, the method adopts a CNN-BiLSTM-Transform double-layer model for demand response capability dynamic prediction, and compared with a single traditional model, the method has the advantages that the dynamic prediction efficiency is improved, and the power distribution network demand response capability dynamic prediction and potential analysis efficiency is improved. The complex coupling relationship among the load, the weather and the excitation signal can be described more accurately; multi-dimensional demand response potential calculation is carried out, and a demand response potential source is systematically analyzed from the perspective of a distribution network side and a development trend according to response characteristics of different user types, so that comprehensive identification of adjustable resources is facilitated, and the management precision of a demand side is improved; a long-term and short-term demand response potential quantification mode based on a space envelope domain is provided, the space envelope domain is introduced to quantify the potential, a potential expectation value is obtained, potential changes under different time scales and influence factors can be represented in a unified form, and the defect that a traditional method only carries out qualitative analysis and lacks unified quantitative indexes is overcome.

The invention relates to the technical field of cloud particle measurement and analysis, in particular to an airborne cloud particle measurement data analysis system based on multi-source data fusion, and the system can analyze the cloud particle measurement data according to a vector real-time key index which is calculated in real time through a dynamic adjustment mechanism of dynamic reasoning key vectors. The most critical vectors for judging the playable area in different scenes are adaptively screened out, and the limitation of traditional fixed vector input is broken through, so that the model can accurately adapt to complex changes of diversified cloud scenes; through mutual cooperation of the core key vector and the dynamic reasoning key vector, on the premise that the core key vector guarantees the basic precision of playable area analysis, the dynamic reasoning key vector only brings the key vector in a real-time scene into calculation, redundant vectors do not need to be processed, the analysis precision is guaranteed, the efficiency of playable potential analysis is improved, and the accuracy of playable area analysis is improved. And good balance between precision and efficiency is realized.

1. The name of the design product: the potential analysis of the energy storage device of the electronic equipment graphical user interface. 2. The use of the design product: the design product is used for an electronic device. 3. The design points of the design product: the content of the graphical user interface. 4. The picture or photo that best indicates the design points: the front view. 5. The use of the graphical user interface: the graphical user interface of the product is the energy storage device running and potential analysis system software interface; the front view shows the first interface of the software; the interface change state diagram is the interface displayed after clicking the "potential analysis" option in the front view interface; the interface change state reference diagram 1 is the reference diagram of the front view, and the interface change state reference diagram 2 is the reference diagram of the interface change state diagram.

The application relates to a building demand response potential determination method and device, computer equipment and medium. The method comprises the following steps: determining the respective index values of each building relative to each demand response evaluation index according to the building power load information of each type of building and the regional power load information; performing subjective and objective weighting processing on each demand response evaluation index based on the respective index values of each building relative to each demand response evaluation index, to obtain the subjective weight and the objective weight of each demand response evaluation index; performing weight comprehensive analysis on the demand response evaluation index according to the subjective weight and the objective weight, to obtain the comprehensive weight of the demand response evaluation index; and performing demand response potential analysis on the building based on the comprehensive weight, to obtain the demand response potential result of the building. The method can improve the accuracy and reliability of the determination of the demand response potential of the building.

The invention relates to the technical field of land resource management, and discloses a global land comprehensive renovation plot potential analysis method and system, and the method comprises the steps: obtaining land utilization current situation data and multi-temporal remote sensing image data of a project area to be renovated; extracting cultivated land resource pattern spots based on land utilization current situation data to form an initial evaluation object set; identifying and rejecting the initial evaluation object set based on the multi-temporal remote sensing image data to obtain a to-be-verified pattern spot set; removing the pattern spot set to be verified through field verification to obtain a primary potential pattern spot set; constructing an evaluation index system to carry out quantitative comprehensive evaluation, and determining a target area; performing laboratory analysis on the soil of the target area to obtain key soil quality parameters; and grading the soil quality based on the parameters, and outputting an evaluation result. The system corresponds to the method. According to the method, accurate screening and scientific evaluation of the potential land parcels are realized, and the accuracy, comprehensiveness and engineering guidance of evaluation work are improved.

The present invention provides a multi-perspective fusion-driven summary generation method based on LLM, belonging to the field of data processing technology. The method specifically includes the following steps: Step 1: After obtaining a target document uploaded by a user, multiple potential analysis perspectives are generated based on the document content; Step 2: Using a clustering algorithm to group and cluster the potential analysis perspectives to obtain a final analysis perspective; Step 3: Generating an emotional perspective based on user needs; Step 4: Inputting the final analysis perspective and the emotional perspective into a fuzzy inference system for fuzzification, calculating the membership of the fuzzified perspective combination, and selecting the optimal perspective combination accordingly; Step 5: Designing a fusion perspective prompt template based on the optimal perspective combination; Step 6: Generating a summary corresponding to the target document based on the fusion perspective prompt template and a pre-trained language model. The present invention improves the efficiency, accuracy, and adaptability of summary generation.

The invention relates to the technical field of reservoir deposit resource evaluation, and particularly discloses a reservoir deposit resource utilization potential analysis method based on machine learning, and the method comprises the steps: constructing a three-dimensional geological entity model comprising a plane and a vertical boundary, and dividing the three-dimensional geological entity model into multiple layers of grid units; siltation low-risk grids with the heavy metal content meeting a low-risk threshold value are screened, and a siltation aggregation grid group is constructed through clustering; recognizing resource potential boundaries through correlation analysis of heavy metals and nutrient elements and gradient mutation points, and combining coincidence boundaries to recognize resource potential domains; a deposition prediction model is constructed, a deposition-migration rule is dynamically output to identify a sustainable boundary, and model parameters are adjusted based on prediction errors. According to the method, the whole process analysis from low-risk area screening to resource potential dynamic evaluation is realized, the accuracy and timeliness of resource potential evaluation are improved, and a scientific basis is provided for safe resource utilization of reservoir deposits.

This invention discloses a waste heat boiler energy-saving potential analysis system and method based on big data, belonging to the field of industrial automation and intelligent control technology. The system includes the following steps: S1, collecting real-time operating data and predictive fuel chemical composition data of the waste heat boiler; S2, calculating the expected corrosion rate, cumulative wall thickness loss, and potential heat recovery efficiency based on the real-time operating data and predictive fuel chemical composition data; S3, constructing an optimization objective function that correlates the operating benefits determined by the potential heat recovery efficiency with the equipment loss costs determined by the expected corrosion rate; S4, performing rolling optimization on the optimization objective function to determine the optimal boiler operation control strategy; S5, generating control commands based on the optimal boiler operation control strategy and sending them to the boiler control system to complete closed-loop adaptive control of the boiler operation. This invention maximizes the total operating benefits of the boiler, demonstrating significant technological advancement and economic value.