456 results about "Potential evaluation" patented technology

The invention relates to the technical field of anti-cracking performance testing, in particular to an ultra-high performance concrete anti-cracking performance testing system and a dynamic monitoring method thereof.The system comprises a dynamic stress field simulation feedback module used for sensing three-dimensional distribution of a micro stress field in concrete in real time by constructing a flexible loading array to obtain dynamic stress field data; the multi-scale damage evolution tracking module is used for deploying a high-resolution acoustic emission network and a distributed optical fiber sensing layer based on dynamic stress field data of the flexible loading array to form a full-scale evolution graph from microdefects to macroscopic cracks; and the intelligent healing efficiency evaluation module obtains stress redistribution data and a full-scale evolution graph, and a repairing medium containing a tracer agent is injected into a preset crack path. According to the method, the whole process of crack resistance of the material from defect initiation to repair and regeneration can be quantitatively evaluated; and finally, outputting a dynamic evolution rule of the crack resistance and enhancing potential evaluation.

The invention discloses an interdisciplinary scientific research potential assessment method based on a dynamic multi-modal knowledge graph, relates to the technical field of scientific research management and intelligence analysis, and aims at the dynamic requirements of college scientific research ecology by relying on an incremental assessment framework. Comprising the steps of multi-source data acquisition and incremental knowledge graph construction, time sequence trend identification, online and transfer learning optimization, scene simulation and multi-scene strategy verification and multi-modal data fusion. The map structure is updated in real time through concept drift detection and ontology extension, and emerging hotspots are identified by combining time sequence difference indexes such as citation acceleration and a cooperative network; and the accuracy and continuous iteration capability of the evaluation model are kept in multiple environments by means of online learning and a cross-domain migration strategy. Finally, potential evolution is quantified through scene simulation, strategy suggestions are output, the sensitivity to the cross domain is further enhanced with the assistance of multi-mode embedding, a closed-loop evaluation system from data to decision is formed, and college subject cross layout and resource allocation are assisted.

The invention relates to the technical field of ecological restoration evaluation, in particular to a surface mine ecological restoration effect evaluation method and system.The surface mine ecological restoration effect evaluation method comprises the following steps that based on ecological restoration targets and standards, a decision tree algorithm is adopted, potential evaluation indexes are analyzed and screened, data in the aspects of biological diversity and soil quality are processed, and the evaluation result is obtained; and classifying the data to generate a refined evaluation index system. According to the method, through application of the decision tree algorithm, screening and classification of evaluation indexes are more scientific and systematic, comprehensiveness and pertinence of an evaluation system are ensured, the genetic algorithm and the simulated annealing algorithm are applied, the global optimization capability is introduced in the weight adjustment process, and the evaluation accuracy is improved. The accuracy of weight configuration and the adaptability of an evaluation system are remarkably improved, the long-term and short-term memory network model and the support vector machine are combined, the long-term dependency relationship in ecological restoration effect time sequence data is captured, and the accuracy of future trend prediction and the reliability of a classification result are improved.

The invention relates to the technical field of database construction, in particular to a construction method and system for a reproductive medicine database. The method comprises the following steps: acquiring a biological tissue sample of a patient; acquiring reproductive endocrine hormone data, embryo morphological parameter data, immune cell function data and genome variation data from the biological tissue sample of the patient; performing time sequence analysis processing on the hormone fluctuation mode according to the reproductive endocrine hormone data to obtain endocrine dynamic characteristic data; performing image recognition processing based on coherent superposition characteristics of light on the embryo morphological parameter data, and performing embryo development potential evaluation to obtain embryo development potential data; and performing hierarchical clustering processing on the individual heterogeneity of the patient according to the immune cell function data and the genome variation data to obtain immune-genetic typing data of the patient. By means of the quantum dot sensing technology and the multi-channel micro-fluidic chip, standardization of data acquisition is achieved, and the heterogeneity problem of a data source is solved.

The invention discloses an industrial park demand response potential assessment method and system. The method comprises the following steps: collecting basic data of each user in an industrial park; load characteristic key indexes are determined, and a typical daily load curve of each user is extracted through clustering analysis; the production characteristics of the user equipment are analyzed, and an interactive response model capable of translating, transferable and reducing loads is established; a multi-target optimization model with the minimum park load peak-valley difference and the minimum operation cost as targets is constructed; and carrying out statistics on the variable quantity of each user load in an optimization result, and evaluating the peak clipping and valley filling potential of the industrial park in different time periods. The method effectively improves the accuracy of industrial park demand response potential evaluation, can accurately describe the power regulation characteristics and time translation characteristics of the flexible load resources of industrial users in different periods of time within the day, fits the actual power consumption behaviors of the users, can accurately obtain the upper and lower adjustable potentials of the industrial park, and improves the evaluation accuracy of the industrial park demand response potential. And a powerful basis is provided for formulating a reasonable load interaction strategy for the industrial park.

The invention discloses a deep coal rock in-situ gas content and adsorption / free gas proportion calculation method and device, and relates to the field of reservoir resource potential evaluation.The deep coal rock in-situ gas content and adsorption / free gas proportion calculation method comprises the steps that an isotope fractionation model coupled with a double-dispersion pore structure (matrix pores and kerogen pores) and a multi-gas transmission mechanism (viscous flow, Knudsen diffusion and surface diffusion) is constructed; the accumulated analytic gas quantity and the apparent isotope value of the produced gas obtained through solving are fitted with the actually measured accumulated analytic gas quantity and the apparent isotope value of the produced gas, and key parameters corresponding to the optimal fitting result are obtained; and determining the in-situ gas content, the in-situ adsorption gas proportion and the in-situ free gas proportion according to the productivity evaluation parameters at the initial moment corresponding to the optimal key parameters. According to the method, the in-situ gas content, the in-situ adsorbed gas proportion and the in-situ free gas proportion of the deep coal rock are calculated on the basis of an isotope fractionation model coupled with a double-dispersion pore structure and a multi-gas transmission mechanism, so that the gas resource content of the deep coal rock is predicted.

The invention belongs to the technical field of oil and gas reservoir energy development, and discloses a three-dimensional injection and production well pattern construction method based on a multi-objective algorithm. The problem that the delimited potential area is difficult to effectively use due to the fact that existing potential evaluation is only based on a single index is effectively solved. Comprising the steps that a fault inner core, a fault outer core, a fracture development dense zone and a secondary fracture zone are proposed; carrying out inter-well connectivity analysis on the oil reservoir units by utilizing an oil reservoir engineering method and a numerical simulation streamline method; based on the embedded discrete fracture model, analyzing a remaining oil distribution mode under the control of the nuclear band structure; a multi-parameter comprehensive evaluation system is constructed by combining the remaining oil utilization potential, the displacement power, the flow capacity, the connectivity relation and the reserve abundance; a three-dimensional injection-production well pattern construction technology is formed for an oil reservoir with or without bottom water; based on a multi-objective optimization algorithm, three-dimensional collaborative optimization of the recovery ratio, the well control reserves and the net present value is taken as a core, and a high-efficiency well location deployment technology for different fault zones is constructed.

The invention discloses an electric power system real-time simulation optimization scheduling method based on edge computing, and particularly relates to the technical field of edge computing management, and the method comprises the following steps: dividing an electric power system into a plurality of regional power grids according to a preset strategy, collecting the load information of each region, and carrying out the load analysis, activating a distributed computing potential evaluation mechanism after identifying abnormal load fluctuation; according to the method, resource utilization difference and task allocation imbalance analysis is carried out by obtaining regional power grid simulation cooperative task allocation information, and efficient and low-efficiency cooperative operation power grids are identified; for a low-efficiency collaborative power grid, task allocation of edge nodes and a center node is optimized, optimal scheduling of analogue simulation tasks is achieved, finally, a regional power grid is adjusted to be a high-efficiency collaborative operation power grid, and the power grid operation efficiency is improved; according to the method, tasks can be reasonably allocated according to the load and computing power of each node, overload or idle of some nodes is avoided, computing resources of edge and center nodes are fully utilized, and the simulation real-time performance and efficiency are improved.

The invention discloses a roof photovoltaic identification and potential evaluation method based on improved TransUNet semantic segmentation. The method comprises the following steps: obtaining a building roof satellite image data set; cleaning and classifying the images in the data set according to whether roof features exist or not, and dividing out images with roofs; according to the roof image, roof features are extracted through the constructed and trained TransUNet semantic segmentation model, and a building roof area is identified and area division is carried out; and matching the processed image with the subject name, and positioning the subject to which the building belongs. According to the method, an innovative solution of a remote sensing technology and a machine learning method is integrated, the generalization ability of roof recognition semantic segmentation can be effectively improved, the roofs are accurately recognized and divided, and the method aims at achieving rapid and accurate evaluation of large-scale urban building roofs.

The invention discloses a single air conditioner load regulation potential evaluation method based on transfer learning and multi-task learning, and relates to the technical field of air conditioner management.The method comprises the steps that a regional association model is built based on air conditioner operation data in a general scene, and the regional association model is analyzed to obtain a cooperative regulation relation between air conditioner equipment; constructing an air conditioner load regulation potential evaluation model by using a deep residual neural network; a multi-task learning framework is formulated according to the cooperative adjustment relation between the air conditioning equipment, and the air conditioning load adjustment potential evaluation model in the general scene is optimized by using the multi-task learning framework; and adjusting the weight of the optimized air conditioner load regulation potential evaluation model in combination with a transfer learning technology to obtain an air conditioner load regulation potential evaluation model in a specific scene. According to the method, the adaptability and generalization ability of the air conditioner load regulation potential evaluation model are remarkably improved by constructing the regional correlation model and introducing self-supervised learning and adversarial training.

The invention discloses an extreme low water change attribution and low water resource potential evaluation method, which belongs to the technical field of water resource calculation, and comprises the following steps of: obtaining raster data of runoff and driving factors of the runoff in a research area, performing data preprocessing, deducing the frequency distribution of runoff depth of each grid unit by adopting a non-parametric kernel density estimation method, and calculating the runoff depth of each grid unit; and counting the proportion of the grids meeting the guarantee rate runoff depth threshold in each year in the total grid, and further determining a low water typical year under each guarantee rate. A nonlinear regression simulation model of coupling optimization deep learning is adopted to carry out extreme low-water runoff depth regression simulation research under different driving factor combinations, and a key driving factor combination influencing low-water runoff depth change is mined based on a regression simulation precision result; and analyzing the constraint effect of each key driving factor on the extreme low water and a possible threshold value by adopting a constraint line deduction technology, and evaluating the low water resource potential of a typical year of the extreme low water.

The invention discloses an intelligent and automatic transformer substation information acquisition system, which relates to the technical field of information acquisition, and is characterized in that an information change coefficient and an information priority coefficient are acquired and substituted into a logistic regression model to obtain an information potential evaluation coefficient, the information potential evaluation coefficient is analyzed with a preset potential threshold to obtain a comparison result, and the transformer substation information is acquired according to the comparison result. Dividing to obtain a real-time acquisition potential information set and a non-real-time acquisition potential information set, substituting into a default score combination mechanism, determining an actual classification acquisition result of each piece of information, obtaining a network state when each piece of information is uploaded, obtaining a network delay degree and a bandwidth utilization rate from the network state, and substituting into fuzzy logic for fuzzy reasoning to obtain a real-time acquisition potential information set and a non-real-time acquisition potential information set; according to the method, the reasonability result of the default score combination mechanism is determined, then the network delay degree and the bandwidth utilization rate when each piece of information is uploaded are substituted into set parameters in the default score combination mechanism, the score combination mechanism is determined and adjusted, and the information redundancy and the system burden are reduced.

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 belongs to the technical field of three-dimensional modeling systems, and particularly relates to an urban geological complex geologic body three-dimensional modeling system which comprises urban geological database construction, three-dimensional model construction and underground space resource development potential evaluation. The urban geology database construction comprises the steps that the database construction target is to establish an urban geology and underground space database; the system is positioned as a basic data center on which urban geology and underground space depend, a convergence place of various data required by accident emergency processing, an information management and control center of various geology and underground space built in the whole life cycle of a city, a data exchange hub and an auxiliary support data center. In the aspect of database construction, efficient management and comprehensive application of urban geological data are realized through standard architecture, classified storage, safety measures and a reasonable updating mechanism.

The invention relates to the technical field of power dispatching, in particular to a comprehensive evaluation method and system considering industrial load participation in power grid regulation and control, and the method comprises the steps: constructing an evaluation index system of industrial load participation in power grid regulation and control, which comprises a potential evaluation index and an effect evaluation index; collecting power grid data, calculating each index score of the evaluation index system in which the industrial load participates in power grid regulation and control, and performing normalization processing; calculating the weight of each index in the evaluation index system in which the industrial load participates in power grid regulation and control; and calculating a total score of industrial load regulation and control performance according to the normalized score of each index and the weight thereof, and evaluating the participation of the industrial load in power grid regulation and control. According to the method, the interaction enthusiasm of the industrial load and the power grid can be improved, a reliable basis is provided for potential prediction before the industrial load participates in power grid regulation and control and establishment of a reward revenue mechanism after regulation and control, and an important reference is provided for power grid dispatching and marketing departments to specify corresponding regulation and control strategies.

The invention relates to the technical field of forest wetland carbon sink monitoring and evaluation, and particularly discloses a forest wetland carbon sink intelligent monitoring and evaluation system and method. According to the method, a vegetation carbon sequestration potential evaluation result is obtained by analyzing vegetation structure feature data of forest, water and soil composite ecology of the forest wetland, a water-soil-carbon cooperative evaluation result is obtained by analyzing specific hydrological-soil carbon cycle key elements of the forest wetland, and environmental disturbance response factors are obtained by combining various environmental disturbance factors. Through multi-source data fusion and intelligent modeling, a carbon sink quantitative evaluation value is output, and abnormal feedback is triggered; the problems that in the prior art, adaptability to a forest wetland compound ecological system is insufficient, evaluation refinement is insufficient, and dynamic response is lacked are solved. According to the method, accurate and dynamic monitoring and evaluation of forest wetland carbon sink are realized, carbon sink short plates can be accurately positioned, optimization support is provided, and technical support is provided for protection, restoration and optimization management of forest wetland carbon sink resources.

The invention discloses a multi-energy collaborative complementary power grid access capability assessment method, and relates to the technical field of electric power. The multi-energy collaborative complementary power grid access capability assessment method comprises the three steps of S1 data collection and preprocessing, S2 characteristic analysis module analysis and S3 access capability comprehensive assessment, and by constructing a renewable energy power generation facility characteristic library, collecting output sample information, load sample information and the like, the output characteristics and load characteristics of different renewable energy power supplies are analyzed, and the access capability of the power grid is assessed. The transmission capability, the operation characteristics and the like of the power grid are analyzed, development potential evaluation, access capability evaluation, future output and load prediction, equipment bearing upper limit determination and power grid weak link identification are finally carried out, and development potential evaluation comprises illumination resource endowment evaluation, geographic attribute constraint evaluation and economic cost constraint evaluation. The multi-energy collaborative complementary power grid access capability assessment method has the beneficial effects of multiple functions, accurate assessment and high practicability.

The invention discloses a typical adjustable resource optimization method and system for a power grid adjustment scene, and the method comprises the steps: carrying out the step extraction of operation data for the historical operation data of different adjustable resources; setting typical scene response characteristics by considering response characteristic differences of the adjustable resources in different power grid adjustment scenes, constructing an adjustable resource response potential evaluation index system oriented to the power grid adjustment scenes, and calculating various evaluation indexes; the matching degree difference between the multi-type adjustable resource response characteristics and the power grid adjustment demand is considered, an adjustable resource comprehensive evaluation model is constructed, and adjustable resource response potential comprehensive evaluation in a specific scene is achieved; in combination with an adjustable resource response feature combination and a comprehensive evaluation model, rapid grouping and optimization are carried out on adjustable resources by adopting a combination evaluation and affinity propagation algorithm, and classification and optimization of adjustable resource groups with different response potentials are realized; and in combination with classification and optimization results, analyzing user demand response potential, and optimizing energy management and demand response strategies.

The invention discloses a method for constructing a large mineralization potential evaluation model based on LLM, and relates to the field of models.The method for constructing the large mineralization potential evaluation model based on LLM comprises the following steps that 1, a mineral geological map file is converted into a structured JSON format data set; step 2, constructing cue words, wherein the cue words at least comprise geological information extraction cue words, function task cue words and entity, relation and attribute extraction cue words; compared with the prior art, the method has the beneficial effects that the large mineralization potential evaluation model constructed by the method realizes text and map multi-mode mineral product geological map information identification and analysis, automatic mineralization geological feature analysis, mineralization feature information extraction and mineralization potential evaluation; the problems that in the prior art, man-made subjective influence exists, professional knowledge dependence is high, the geological information recognition accuracy rate in the recognition process is low, and information is lost during knowledge retrieval are solved.

The invention discloses an electric vehicle V2G regulation potential evaluation method based on electricity price regulation, particularly relates to the technical field of electric energy storage cooperative control, and is used for solving the problems of power grid resonance risk and battery life loss caused by power synchronism in existing V2G centralized scheduling. Through real-time fusion of a dynamic electricity price time period division signal and a power grid frequency deviation value, carrying out dual constraint on a charging and discharging power range in combination with a battery health state attenuation coefficient, and generating an initial instruction set; a power grid resonant frequency distribution interval is further extracted based on a frequency sweep test, an asymmetric phase disturbance rule is generated for a dominant resonant frequency point, and a harmonic superposition effect of power output is destroyed through differential time sequence offset; in the instruction execution stage, the phase disturbance amplitude is dynamically adjusted to adapt to the power grid frequency fluctuation and the battery aging degree, a closed-loop control mechanism is formed, collaborative optimization of the power grid stability and the equipment service life is achieved, and the safety of the electric vehicle cluster participating in power grid adjustment is improved.

The invention discloses a virtual power plant adjustable potential comprehensive evaluation method, system and equipment giving consideration to communication and action time delay. According to the method, a communication system time delay model, an equipment action time model and a communication reliability model are constructed by constructing a cloud edge collaborative network system framework for regulating and controlling a virtual power plant. And then, establishing a virtual power plant maximum adjustable potential evaluation model based on timing delay step length search by using a k-shortest path algorithm. And finally, providing a method based on a near-end strategy optimization algorithm to solve the optimization model. According to the method, comprehensive evaluation of the adjustable potential of the virtual power plant considering the influence of the communication system and the resource action time is accurately described, a decision basis is provided for the virtual power plant to participate in primary and secondary frequency modulation and peak regulation of the power system, and frequency stability and power and electric quantity balance of the power system can be supported.

The invention provides an electricity-hydrogen coupling energy hub peak regulation potential evaluation method and system. The method comprises the following steps: obtaining new energy output of an energy hub and equipment parameters of each electricity-hydrogen coupling energy hub; on the basis of the new energy output and the parameters of the electricity-hydrogen coupling equipment, combining with a pre-constructed energy hub peak load regulation power model, and obtaining actual peak load regulation participation power of the electricity-hydrogen coupling equipment; on the basis of actual participation power of peak regulation of the electric-hydrogen coupling equipment, the new energy output and the equipment parameters in combination with a pre-constructed energy hub peak regulation target model, obtaining an optimal target value of peak regulation participated by the electric-hydrogen coupling equipment; according to the net load value and the total scheduling time of the energy hub corresponding to the optimal target value, evaluating the grid-connected peak regulation potential of the electricity-hydrogen coupling energy hub; according to the invention, the potential of the electro-hydrogen fusion energy hub in the peak regulation of the power grid is fully exerted through potential evaluation; the adjusting capability of the power grid is improved, and the stability and safety of power grid operation are improved.

The invention provides a recruitment interview evaluation system based on artificial intelligence. The recruitment interview evaluation system comprises an information acquisition module which acquires enterprise recruitment information and corresponding applicant resume information and applicant interview information; the skill evaluation module extracts position skill features and applicant skill features, performs skill learning path analysis based on the established industry skill knowledge graph, and further obtains skill potential evaluation results of the applicants; the culture adaptation evaluation module extracts enterprise culture characteristics and applicant culture characteristics, and performs culture adaptation analysis based on the enterprise culture characteristics and the applicant culture characteristics to obtain a culture adaptation evaluation result of an applicant; the interview evaluation module analyzes the interview performance of the applicant according to the interview video record data of the applicant to obtain an interview evaluation result; and the report module is used for obtaining a comprehensive evaluation result of the applicant for the enterprise position. According to the invention, an enterprise can be helped to improve the intelligent level of evaluation of an applicant for a specific position.

The invention discloses a new energy power grid hybrid energy storage system multi-dimensional regulation and control capability quantitative evaluation method and system, and mainly relates to the technical field of new energy power grid hybrid energy storage system regulation and control. Comprising the following steps: respectively constructing layered evaluation index systems of the hybrid energy storage unit in frequency modulation and peak regulation based on short, medium and long time scales; determining the weight of each level index in the index system; based on the hierarchical evaluation index system and the weight of each hierarchical index, performing comprehensive potential evaluation on the hybrid energy storage unit; and according to an evaluation result, the regulation and control capability of the hybrid energy storage system under different time scales is comprehensively evaluated, and an optimization and scheduling strategy of the energy storage unit is formulated according to the evaluation result. The method has the beneficial effects that the frequency modulation, voltage regulation and peak regulation potentials of the hybrid energy storage system can be quantified under different time scales, and the optimal energy storage configuration and operation strategy can be formulated according to the frequency modulation, voltage regulation and peak regulation potentials.

The invention discloses a distribution network reactive power support capability evaluation method and system considering uncertainty new energy output, and belongs to the technical field of power grid power generation dispatching, and the method comprises the steps: constructing a distribution network reactive power deviation index considering active and reactive power coupling, and fusing the index into a distribution network reactive power support capability evaluation calculation process; constructing reactive power reserve models of various traditional energy sources and uncertain new energy sources, wherein the reactive power reserve models comprise a generator set, a capacitor bank, wind power generation, photovoltaic power generation, energy storage, a flexible load and an electric vehicle; constructing a typical scene set which comprehensively considers the output of all the models; constructing a distribution network reactive power support capability calculation model considering the uncertainty new energy output; and solving by adopting a genetic algorithm to obtain the reactive power support capability of the distribution network. According to the method, multiple types of reactive power resources on the power distribution side are fully transferred, the reactive power reserve potential evaluation model for the active power distribution network individuals is established, and quantitative evaluation of the reactive power voltage supporting capacity of the power distribution network is achieved.

The invention discloses a controllable load adjustable potential evaluation method considering user response willingness, and the method comprises the steps: carrying out the quantitative aggregation of the user response willingness according to different power utilization characteristics of a flexible load, and constructing a flexible load influence factor membership function through a TSK fuzzy model; the relation between the up-regulation and down-regulation response willingness of the flexible load cluster and other influence factors is quantified, the upper and lower limits of the adjustable potential of the flexible load cluster are calculated according to the determined response willingness threshold value to serve as one of consideration of the reliability of the adjusting quantity, richer information is provided for optimized operation of the power distribution network, and the reliability of the power distribution network is improved. And a real-time electricity price scheme is combined to guide the electricity consumption behavior of the user, thereby reducing the power grid load peak and filling up the power grid load valley.

The invention relates to the technical field of geothermal resource development, and discloses a geothermal resource prediction method and system based on multi-source data fusion, and the method comprises the steps: obtaining a multi-source geothermal basic data set, carrying out the weighted fusion analysis of the multi-source geothermal basic data set, and extracting a comprehensive geothermal feature vector meeting a resource enrichment condition; carrying out potential evaluation and weight fusion according to the feature vector, generating an earth heat flux density distribution potential map and determining a high potential area; on this basis, potential development point locations are identified, and a candidate well location preliminary set is formed; performing comprehensive evaluation and sorting on the candidate well positions to obtain an optimized well position set; performing combined influence evaluation and interference judgment by combining well location distance constraint conditions, and constructing a constraint relation matrix; and through multi-round combination screening and optimization, an optimal well position combination scheme is determined, and a complete implementation scheme is generated and used for small-scale geothermal development and implementation. According to the method, high-precision well position selection and development scheme optimization can be realized.

The invention discloses a load regulation potential evaluation method and system for a power system and a medium, mainly relates to the technical field of load regulation, and is used for solving the problems that an existing method is difficult to accurately describe complex power consumption behaviors of power loads and is difficult to popularize and apply under the condition of insufficient data or strict privacy protection. Comprising the steps that a trained nonlinear autoregressive neural network is utilized, and based on historical data of a preset time period and external environment data of the day, a predicted load curve of the day is obtained through fitting; on the basis of Euclidean distances between key features in the prediction load curve and the typical daily clustering centers, determining the class with the closest distance from H * T typical daily clustering centers as the typical daily clustering center corresponding to the prediction load curve on the current day; and calculating to obtain the valley filling capability and the peak clipping capability of the evaluation subject.

The invention relates to the technical field of data classification prediction, and discloses a sandy soil earthquake liquefaction potential rapid evaluation method, which comprises the following steps: S1, selecting data from a data set commonly used in the field of sandy soil liquefaction as a first data set; s2, constructing a sandy soil earthquake liquefaction potential evaluation model; s3, inputting the data of the first data set into the model, performing domain adaptive training by using the maximum mean value difference, correcting the model, and performing data prediction on the second data set by using the corrected model; and S4, comparing the predicted sandy soil liquefaction condition with the actual sandy soil liquefaction condition, and carrying out validity verification on the sandy soil seismic liquefaction potential. The scheme improves the adaptability of the model on different data sets, solves the problems of low prediction efficiency, easy occurrence of an overfitting phenomenon of the model and the like in an existing scheme, and improves the prediction accuracy of the sandy soil seismic liquefaction potential. And the method shows higher accuracy and reliability in sandy soil earthquake liquefaction potential evaluation, so that the method has better interpretability and applicability.

The invention discloses a geological carbon sequestration potential evaluation method, device and equipment, a medium and a program product. The method comprises the following steps: preprocessing an initial geological carbon sequestration training data set to obtain a target geological carbon sequestration training data set; constructing a migration optimization model according to the target geological carbon sequestration training data set; inputting the target geological carbon sequestration reasoning data set of the sea area depleted oil and gas field research area into the migration optimization model for multi-field coupling simulation to obtain target geological carbon sequestration evolution data; calculating an initial geological carbon sequestration total amount according to the target geological carbon sequestration evolution data; performing sea area correction on the initial geological carbon sequestration amount to obtain a target geological carbon sequestration amount; the target total geological carbon sequestration amount is used for representing the geological carbon sequestration potential of the sea area depleted oil and gas field research area. The method can improve the reuse rate of the oil and gas data, greatly reduces the training data to reduce the cost of evaluating the geological carbon sequestration potential of the exhausted oil and gas field, and can be widely applied to the technical field of intelligent geological carbon sequestration.