108 results about "Qualitative property" patented technology

The invention relates to the technical field of energy management, in particular to a fuzzy logic-based multi-objective decision analysis method, which comprises the following steps of: firstly, dividing an evaluation criterion into quantitative and qualitative index sets; constructing an interval type-2 fuzzy set capable of describing data uncertainty according to quantitative indexes such as a full-life investment payback period; for qualitative indexes such as technology maturity, a spherical fuzzy set is introduced, and an intelligent operator for perceiving hesitance is used for aggregation; calculating a group utility value, an individual regret value and a comprehensive sorting index of each energy configuration scheme by applying a hybrid fuzzy VIKOR algorithm, outputting an optimal compromise sorting result, and identifying a reference optimal strategy and a risk avoidance strategy; according to the method, the explainable enhanced fuzzy rule is extracted, the robustness of the decision method is improved by analyzing different types of fuzzy logic, and the transparency, the credibility and the compliance of the energy configuration decision process are remarkably enhanced by the finally generated explainable decision basis, so that a feasible configuration decision reasoning model is provided for energy planning.

The invention provides a cogeneration unit peak regulation capability evaluation method, which comprises the following steps: firstly, constructing a thermodynamic system mathematical model, solving system coupling parameters under a deep peak regulation working condition through a multi-layer iterative loop architecture, and generating a multi-working-condition data set which covers a full working condition and meets physical consistency; secondly, deducing a linear qualitative relation equation of the power, the main steam flow and the heat supply steam extraction flow, preprocessing a data set, training a pure data driving model as a performance reference, introducing the linear qualitative relation equation as a physical constraint item into a loss function, and constructing and training a PINN; and finally, the rated boundary condition of the peak regulation capacity is determined, a thermal characteristic curve is obtained through PINN simulation, the peak regulation capacity range and the real-time peak regulation margin under different heat supply requirements are calculated, and the result is transmitted to a power system dispatching platform. According to the method, the all-working-condition peak regulation evaluation precision and reliability can be improved, and the flexibility and universality of the model are enhanced.

The invention relates to the technical field of computer-aided planning, and discloses a territorial space planning decision-making method and system based on multi-dimensional influence assessment, and the method sequentially comprises the steps: multi-source data fusion and problem diagnosis, multi-dimensional influence quantitative assessment, scheme collaborative optimization, and scheme comprehensive screening and decision-making. The system corresponds to the method. According to the method, through multi-source data fusion processing, the data reliability is improved, and a solid foundation is provided for subsequent problem identification; according to a quantitative index and a GIS spatial analysis technology, key problem region identification is more targeted, and the defect of generalization adjustment of a traditional qualitative method is avoided; through traffic, environment and municipal dimension parallel evaluation, the efficiency bottleneck of serial evaluation is avoided, and the evaluation period is shortened; a Pareto candidate scheme set generated through a multi-objective evolutionary algorithm is combined with a comprehensive screening mechanism to ensure that a final scheme is balanced between performance requirements and constraint conditions, and the feasibility of planning landing is enhanced.

The embodiment of the invention is suitable for the technical field of computers, and provides a risk qualitative method and device, electronic equipment and a storage medium. The method comprises the steps that API abnormal operation information of a user is received; obtaining abnormal context information, related to the API abnormal operation information, of the user; inputting the abnormal context information into a generative network model to obtain a qualitative result of the API abnormal operation information output by the generative network model, the qualitative result representing whether the API abnormal operation of the user is a malicious behavior; the generative network model is obtained by training a preset basic model based on abnormal context information related to preset API abnormal operation information and a corresponding qualitative result.

The invention discloses a mass spectrum data high-throughput alignment and parallel qualitative method based on deep characterization learning, and relates to the field of chromatography-mass spectrometry data processing and calculation mass spectrography. The method comprises the following steps: performing streaming, micro-batch and single traversal analysis on original mass spectrum data files of a plurality of samples to be detected; extracting metadata and main data by taking the fragmented spectrogram as a unit, inputting the metadata and the main data into a pre-trained depth representation learning model to generate a high-dimensional embedded vector, and incrementally writing the metadata and the main data into a column type storage database; constructing a sparse approximate nearest neighbor graph; executing a clustering algorithm on the graph to generate a consensus spectrogram set, and generating a consensus feature vector for each clustering cluster and a single example cluster; determining the nature of the consensus feature vector; and constructing a sample * feature matrix based on the cluster affiliation relationship and the qualitative result. According to the method, the technical problems of I / O bottleneck, memory overflow, combinatorial explosion, computing power waste and the like in large-scale mass spectrum data analysis are effectively solved.

The representation learning apparatus acquires M second-type mixed feature representations extracted from M first-type mixed feature representations. The apparatus acquires M mixed labels obtained by mixing N labels. The apparatus calculates the L similarities of L label combinations selected from the M mixed labels. Each of the L label combinations has K mixed labels selected from the M mixed labels, each of the L similarities represents the degree of similarity of the K mixed labels, and the L similarities are formulated based on a qualitative and quantitative constraint condition. The apparatus performs a computation of a loss function based on the M second-type mixed feature representations and the L similarities.

The application provides an intelligent processing method and device for auditing problem qualitative analysis and rectification tracking based on a large model and a medium. It belongs to the technical field of auditing. The system comprises a model construction module: an intelligent auditing knowledge cloud brain is constructed, and knowledge base data is generated; based on the knowledge base data, key auditing element extraction is performed on the auditing business scene, and auditing element extraction result data is generated; auditing problem matching model training is performed according to the auditing element extraction result data, and an auditing problem accurate matching model is constructed; relying on the powerful knowledge base and intelligent matching capability of the large language model, knowledge content closely related to the problem is rapidly and automatically filled in, covering key information such as problem name, manifestation form, problem qualitative analysis, qualitative analysis basis and treatment and punishment basis, which greatly saves the time of auditing personnel for manually searching and sorting data, more ensures the accuracy and integrity of the problem description, and lays a solid foundation for subsequent auditing analysis.

The invention relates to the technical field of information security, in particular to a penetration test effect evaluation method and system based on an attack mode framework, and the method comprises the steps: firstly, constructing an evaluation model comprising a target layer, a criterion layer and an index layer; the evaluation indexes under each criterion are weighted through a large language model, and the indexes are quantitatively scored by experts. And for each criterion, on the basis of a grey theory, calculating a comprehensive evaluation vector of the criterion by using index scores, weights, a preset comment set and a whitening weight function so as to obtain a quantitative score and a qualitative evaluation result. And finally, calculating a final comprehensive evaluation result of the target layer by integrating the quantitative score vectors and the criterion weights of all the criteria. During decision making, the final result needs to be combined with the qualitative evaluation conclusion of each criterion so as to formulate a comprehensive and targeted security reinforcement strategy. According to the invention, the accuracy of penetration test effect evaluation is improved.

The invention discloses a debris flow silt arrester disaster prevention benefit evaluation method, and the method comprises the steps: constructing a hierarchical evaluation system which faces a future operation state and can integrate landform shape constraints, reservoir capacity operation conditions and a safety risk state on the premise of not remarkably increasing the data acquisition cost; according to the invention, an integrated technology of AHP weighting, two-level fuzzy synthesis and maximum membership level judgment is provided; wherein a calculation framework based on threshold determination and piecewise linear membership functions, qualitative index feature vector assignment, penalty mapping of interval optimal indexes and two-stage fuzzy comprehensive evaluation jointly form core features of the method; the weight is determined based on the analytic hierarchy process, the consistency check is passed, the two-stage fuzzy comprehensive evaluation and the maximum membership principle are further adopted to output the levels of'excellent, good, medium and poor ', and a quantitative basis is provided for inspection and maintenance of the silt arrester, desilting modification and risk grading management and control.

The invention relates to a quantitative collaborative evaluation method and system for power measurement differences and a storage medium. The method comprises the following steps: acquiring quantitative index data and qualitative index data of power measurement; performing normalization processing on the quantitative index data; respectively calculating subjective weights and objective weights of all indexes based on an analytic hierarchy process and an entropy weight method, and carrying out weighted fusion to obtain subjective and objective combined weights; processing the qualitative index data based on fuzzy comprehensive evaluation, and combining subjective and objective combination weights to obtain quantitative scores of qualitative indexes; calculating a correlation coefficient of the normalized quantitative index data and a corresponding reference sequence based on grey correlation analysis, and calculating a comprehensive correlation degree of the quantitative index; and integrating the comprehensive correlation degree of the quantitative indexes and the quantitative scores of the qualitative indexes, and calculating to obtain a comprehensive difference degree. Compared with the prior art, through subjective and objective combination and qualitative and quantitative collaborative evaluation process, accurate and consistent quantitative output of the power measurement difference is provided.

The present application relates to the field of oil and gas exploration, in particular to a kind of dual induction eight lateral logging curve semi-quantitative acceptance method, equipment and medium. Including according to the curve of adjacent well and acceptance area dual induction eight lateral logging experience, based on adjacent well comparison template obtains preliminary qualitative acceptance conclusion;Dual induction eight lateral original data is loaded by resistivity comparison template, whether the relative error of curve repeated measurement value meets acceptance standard is judged, and semi-quantitative acceptance conclusion is obtained;Comprehensive preliminary qualitative acceptance conclusion and semi-quantitative acceptance conclusion, obtain final conclusion.The present application combines the characteristics of dual induction eight lateral logging instrument and the curve law of the region, forms two templates, can quickly according to adjacent well, regional experience and resistivity curve carries out repeatability two-step inspection, obtains comprehensive analysis result, realizes the rapid and accurate acceptance of dual induction eight lateral logging curve.

This disclosure relates to method and system for determination of personality traits of agents in a contact center. The method includes retrieving textual data corresponding to a conversation between a first agent and a first customer. The method further includes generating a natural language justification corresponding to a set of personality traits of the first agent based on the textual data through a first Machine Learning (ML) model. The natural language justification may include one or more sentences. The one or more sentences may include a mapping of the textual data with the set of personality traits and a qualitative label associated with each of the set of personality traits. The method further includes determining a value corresponding to each of the set of personality traits of the first agent through the first ML model based on the natural language justification and the associated qualitative label.

This invention specifically relates to a performance testing method for laser cladding repair, encompassing the fields of laser additive manufacturing and non-destructive testing. The method includes: screening tracer particles based on three criteria: high physical field contrast, high-temperature thermal stability, and rheological compatibility; determining the tracer particle ratio; preparing uniform composite powder; verifying mixing uniformity; and standardizing powder pretreatment and storage. In this invention, tracer particles with high physical field contrast are introduced, and a direct mapping model between signal intensity and dilution rate is constructed using the law of conservation of solute mass. Normalization calculations eliminate interference from instrument response coefficient drift, enabling the method to penetrate the cladding layer surface and directly quantify the component mixing ratio within the molten pool. This not only achieves a leap from qualitative judgment to quantitative measurement but also replaces fuzzy empirical judgments with explicit physical laws, providing a non-destructive, high-confidence, and fully physically interpretable in-situ characterization method for laser repair quality.

The invention relates to the technical field of building heritage protection, and provides a railway building heritage protection method based on multi-source data fusion in order to solve the problems of data splitting, significant subjective deviation and decision staticization in the building heritage protection process. The method comprises the following steps: constructing a multi-dimensional digital file by comprehensively collecting a BIM model, an Internet of Things sensor network, a historical literature database and a geographic information system; establishing a hierarchical evaluation index system, setting an objective reference value, and determining the weight of a corresponding index by adopting a collaborative process integrating an analytic hierarchy process and a Delphi method; carrying out quantitative scoring through an expert team, and carrying out weighted calculation on a total score of a comprehensive value to determine a protection grade; and performing section division according to the spatial position, identifying regional dominant value features through clustering analysis, and generating a hierarchical protection strategy in combination with a protection rule base. According to the method, normal form conversion from subjective qualitative to objective quantitative in the evaluation process is realized, subjective deviation is remarkably reduced, and the accuracy and operability of protection decision making are improved.

The invention discloses a function handling method, device and equipment based on a life cycle and a medium, and relates to the technical field of artificial intelligence. The method comprises the steps of obtaining a confidence factor set corresponding to a to-be-selected evaluation function in a current function evaluation service; performing quantitative judgment on the confidence factor set based on the target low-efficiency affirmation model to obtain a quantitative judgment result, and determining a corresponding intermediate evaluation function based on a preset function category field and the quantitative judgment result; generating a qualitative affirmation starting instruction based on the intermediate evaluation function, and determining a qualitative affirmation result corresponding to the current function evaluation service based on the qualitative affirmation starting instruction and a preset qualitative affirmation rule; and performing function disposal on the intermediate evaluation function based on the qualitative affirmation result, and generating a function disposal result corresponding to the to-be-selected evaluation function. According to the technical scheme of the invention, the method can achieve the accurate recognition and disposal of the low-efficiency function, improves the recognition efficiency and accuracy of the low-efficiency function, and reduces the maintenance and operation cost of a system.

The invention relates to the technical field of data processing, in particular to a method for evaluating the uniformity of qualitative characteristic values of a standard sample based on a quantitative result. The invention provides an evaluation and expression method for defining the qualitative characteristic uniformity of the standard sample by using the definite probability, so that reasonable quantitative expression of the qualitative characteristic uniformity of the standard sample is realized, and the problem of reasonable evaluation and explanation of the qualitative characteristic uniformity of the standard sample is solved.

This invention relates to the field of power plant data processing, and discloses a natural language processing-based operation and maintenance data processing system and method to address the problems of existing technologies relying on big data, lacking interpretability, and being unable to quantitatively integrate textual experience with physical laws. The system includes parsing operation and maintenance text into structured semantic units; quantifying these units into continuous influencing factors driving the physical model; using a non-machine learning theoretical physical model for state inference and prediction; comparing the prediction results with historical real states to generate difference data; and finally, optimizing the semantic quantification rules based on the difference data. This system achieves interpretable prediction and continuous self-evolution under small sample conditions, effectively transforming qualitative operation and maintenance experience into quantitative decision-making basis, and improving the reliability of operation and maintenance decisions and the ability to accumulate knowledge.

This application relates to the field of detection technology for the degree of voiding at the steel-concrete interface, and provides a method and system for evaluating the degree of voiding at the steel-concrete interface. By establishing an acoustic cross-correlation mapping system between a dense benchmark sample and a preset voiding model, the traditional qualitative judgment relying on human hearing is transformed into a mathematical representation based on waveform similarity. A quantitative relationship between the degree of voiding and the detuning degree of the acoustic signal is constructed through a normalized voiding cross-correlation coefficient, fundamentally eliminating the subjective error of human experience. The acoustic autocorrelation coefficient of the dense steel pipe is introduced as a benchmark, achieving decoupling mapping between the degree of voiding and signal characteristics. A four-level evaluation mechanism of "unqualified - qualified - good - excellent" is established based on the preset voiding model, with the grading threshold derived from the correlation between the actual voiding size and acoustic distortion.

The invention provides a project evaluation method and system and a computer readable storage medium, and belongs to the technical field of project evaluation. The method aims at solving the technical problem that an existing single review mode causes one-sided and biased review results. The method comprises the following steps: grouping bidding items according to a preset classification standard; independently reviewing the project by a plurality of first reviewing experts, and outputting a qualitative reviewing result containing a recommendation level; converting the recommendation level into a quantitative score according to a preset score assignment rule to obtain a first-stage review total score; at least one second review expert carries out centralized discussion type common review on at least part of the bidding items, and a unified review opinion is formed; and finally, determining a final project approval project based on the first-stage review total score and the unified review opinions. According to the project review method and device, independent quantitative initial review and centralized discussion review are combined, the defect of a single review mode is effectively overcome, and the fairness, scientificity and efficiency of project review are improved.

The invention discloses an intelligent question answering method and system based on multi-strategy response, a medium and a product, and relates to the technical field of artificial intelligence. The method comprises the following steps: carrying out semantic splitting on a multi-modal input request of a user; based on a preset intention recognition feature system, the user intention is accurately qualitative as a knowledge query intention or a task execution intention; and selecting a special knowledge response path or task processing path according to a qualitative result. In a task processing path, the system not only extracts structured parameters, but also actively retrieves task knowledge which is adaptive to tasks and contains business rules or constraint conditions, and finally calls an interface to execute operation in combination with the parameters and the task knowledge. According to the method and the device, through a core framework of first qualitative and second shunt, task knowledge is deeply fused in a task path, so that execution path errors caused by intention qualitative errors are avoided from the source, task instructions containing complex constraints can be precisely processed, and the question answering success rate of the intelligent question answering system is remarkably improved.

The present invention is a computer system for creating fractal spider graphs which display data in a nested structure. The present invention includes a data store, a data analytics engines, and a computer platform for data visualization. The present invention analyzes both qualitative and quantitative data to determine a pattern of behavior based on the data. The data is then broken down into key performance indicator (KPI) units using NLP and machine learning. These KPI units are then used as the atomic unit for constructing the fractal spider graphs. The fractal spider graphs of the present invention are hierarchical, nested spider graphs which simultaneously display information and analysis from multiple levels of an organizational hierarchy. Further, the present invention is operable to generate inferences (i.e., decision outputs) based on the data, wherein the inferences are displayed as prioritized action lists, weighted confidence scores, risk-impact indices, and / or narrative recommendations.

The invention discloses a forest litter prediction method based on multi-modal fusion and automatic machine learning, belongs to the field of cross technologies of ecological system simulation and prediction forest ecology and computer science, and relates to an innovative data fusion framework integrating standard environment numerical data and unstructured qualitative text information. Ecological descriptive knowledge is converted into quantifiable prediction features, an automatic machine learning (AutoML) technology is utilized, through full-process automation steps from data processing, model selection to integrated optimization, a modeling threshold is reduced, a high-precision and high-robustness prediction model is constructed, and prediction of forest litters is completed.

This invention provides a fault prediction method, apparatus, electronic device, and storage medium. The method includes: performing fault prediction based on component attribute data of the product under test (BUT) during the design phase; applying a fault hierarchy model to infer the root cause of faults based on the predicted fault probability distribution; and obtaining the fault propagation path corresponding to the fault modes involved in the BUT. The fault hierarchy model is configured with a multi-layer topology from the product component level to the product whole-machine level, and the transmission relationship of faults in the multi-layer topology from the product component level to the product whole-machine level. This not only realizes the leap from qualitative experience analysis to quantitative data prediction, but also transforms isolated component risks into visualized fault propagation paths. This allows designers to clearly see the specific impact chain of underlying design defects on the reliability of the whole machine, thereby enabling targeted optimization before product manufacturing and greatly improving R&D efficiency and the final quality of the product.

The invention relates to the field of hydrogen energy power ship design, in particular to a hydrogen energy ship power system-oriented suitability evaluation method, which comprises the following steps of: carrying out disassembly analysis on a hydrogen energy ship power system to determine key equipment of a ship; establishing a key equipment suitability evaluation standard based on ship navigation requirements; performing preliminary suitability screening and qualitative grading on different types of key equipment; establishing a mixed evaluation model combining an analytic hierarchy process and a fuzzy evaluation method, and constructing an evaluation method system; carrying out adaptability analysis and index weight distribution on each key device; establishing a system topological structure, and determining core elements of the evaluation weight decision tree; and constructing a multi-level evaluation weight decision tree, quantitatively evaluating the implementation process, and outputting equipment type selection suggestions and a short board optimization scheme. The method for evaluating the suitability of the hydrogen energy power system and the ship is beneficial to realizing objective and accurate design of the hydrogen energy power ship, and has remarkable technical and industrial values.

The present invention is a computer system for creating fractal spider graphs which display data in a nested structure. The present invention includes a data store, a data analytics engines, and a computer platform for data visualization. The present invention analyzes both qualitative and quantitative data to determine a pattern of behavior based on the data. The data is then broken down into key performance indicator (KPI) units using NLP and machine learning. These KPI units are then used as the atomic unit for constructing the fractal spider graphs. The fractal spider graphs of the present invention are hierarchical, nested spider graphs which simultaneously display information and analysis from multiple levels of an organizational hierarchy.

The invention discloses an ancient and famous tree health assessment method and system. The method comprises the steps of collecting multi-dimensional health index data of a target ancient and famous tree; performing cleaning, normalization and missing value processing on the index data to form a standardized data set, and extracting feature vectors; inputting to a pre-trained gradient boosting decision tree model, and outputting a health level prediction result of the target ancient and famous tree; the model takes a minimization objective function as a training objective to carry out iterative training; the objective function is composed of a loss function and a regularization term and comprises a weighted cross entropy loss term and a time sequence smoothing regularization term; the system is used for implementing the method. According to the method, health assessment of ancient and famous trees is converted from qualitative judgment depending on subjective experience into objective diagnosis based on multi-dimensional quantitative data and an algorithm, and the scientificity and decision support value of an assessment result are remarkably improved.

The invention provides a motor attribute evaluation method, device and equipment for a gravity energy storage system, and the method comprises the steps: obtaining the index data of a candidate motor, and the index data comprises quantitative data and qualitative data; model calculation is carried out on the quantitative data, quantitative calculation is carried out on the qualitative data, an index data matrix is obtained, and the index data matrix comprises first index data and second index data; standardizing the index data matrix and calculating to obtain a combination weight; and processing the combined weight by an approximate ideal exclusion method to obtain evaluation data. According to the method, the index data of the candidate motors are obtained and calculated to obtain the index data matrix, the combined weight is obtained through standardization processing and weight coefficient allocation, and the close degree of the index under the combined weight and the target data is calculated; therefore, the defects that actual requirements cannot be comprehensively considered in manual model selection and manual experience lacks repetitive basis are overcome, and the reliability of the motor of the gravity energy storage equipment is ensured.

A method for facilitating qualitative assessment of natural language data via artificial intelligence is disclosed. The method includes receiving, via an application programming interface, an input from a source, the input including the natural language data; determining, by using a model, a confidence score for the input, the confidence score relating to a clarity level of the natural language data; determining, by using the model, whether the confidence score exceeds a predetermined threshold; generating, by using the model, a request for additional information when the confidence score is below the predetermined threshold, the request including a prompt in a natural language format; and transmitting, via the application programming interface, the request back to the source.

The application discloses a mass spectrum combined characterization qualitative and quantitative method and system of unified hidden state, relates to the cross field of analytical chemistry, bioinformatics and artificial intelligence data processing, the method obtains original data and instrument / method metadata containing LC-MS / MS, encodes to form a condition vector and is used for conditional modulation, constructs wave encoder and particle encoder, respectively Tokenizes continuous chromatographic signal and discrete fragment peak set into wave encoder and particle encoder to obtain wave representation and particle representation, realizes cross-modal interaction through wave-particle fusion module, forms unified hidden state or object-level unified hidden state set, adopts two-stage training of self-supervised pre-training and task fine-tuning, and applies conditional quantitative operator and qualitative operator to unified hidden state or object-level unified hidden state set in the inference stage, and parallelly outputs quantitative results and identification score / probability, and is suitable for end-to-end qualitative and quantitative analysis in DDA / DIA scene.