700results about How to "Improve evaluation efficiency" patented technology

The invention discloses a data-driven cross-domain intelligent asset knowledge reasoning and value evaluation method and system, and relates to the technical field of intelligent assets, and the method comprises the steps: extracting multi-domain data features of intelligent assets based on a deep learning model, and constructing a cross-domain intelligent asset knowledge graph; analyzing a user evaluation target based on a pre-trained language model, retrieving related assets in a knowledge graph, and performing knowledge reasoning by using an attention mechanism and a graph reasoning algorithm; and on the basis of the value evaluation model of reinforcement learning training, a final evaluation value and an evaluation report containing a confidence interval are generated in combination with a time sequence prediction algorithm. According to the method, multi-source heterogeneous data can be effectively fused, knowledge reasoning and value evaluation of cross-domain intelligent assets are realized, and the evaluation efficiency and accuracy are improved.

The invention provides a power transmission and transformation project ecological influence space-time boundary determination method and system based on multi-source remote sensing information deep fusion interpretation, and belongs to the technical field of power transmission and transformation project management. The method comprises the steps of data acquisition, data preprocessing and multi-source data integration, multi-scale space-time analysis, ecological influence index construction, remote sensing ecological index model construction, ecological influence space-time boundary determination, dynamic monitoring and early warning system platform establishment and long-term monitoring and evaluation. By integrating satellite remote sensing, unmanned aerial vehicle aerial photography and ground monitoring data and combining an image fusion algorithm, a principal component analysis method and a random forest algorithm technology, the method is beneficial to promoting accurate evaluation of the influence of the power transmission and transformation project on the ecological environment, visualizes the space-time boundary of the ecological influence, breaks through the limitation of a traditional evaluation method on time and space coverage, and improves the evaluation efficiency of the power transmission and transformation project. And a scientific method system for analyzing and evaluating the ecological influence of the power transmission and transformation project is further improved.

The invention discloses a chronic disease patient information management system and method based on intelligent AI, and relates to the technical field of information management. The information management system comprises a patient information management module, a data acquisition module, a data management module, a data analysis and evaluation module, a risk early warning module, a health management module and a remote medical service module. According to the chronic disease patient information management system and method based on the intelligent AI, learning and analysis are carried out based on comprehensive health data of the patient, so that accurate assessment of the health risk of the patient is realized, the current health data of the patient is integrated, and multi-dimensional information of medical history and living habits of the patient is combined, so that the assessment result is more comprehensive and accurate, and meanwhile, the assessment efficiency is improved. The health risk possibly faced by the patient in the future is predicted, early warning is given out in advance, sufficient time is provided for medical institutions to formulate intervention measures, potential health problems can be found and handled in time, and disease deterioration is prevented.

The invention provides an intelligent mineral resource exploration and evaluation system, and relates to the technical field of data processing, and the system comprises a data preprocessing module which is used for preprocessing data to obtain preprocessed data; the stress analysis module is used for analyzing the rock physical property and the geological structure stress state of the exploration area according to the preprocessed data so as to obtain the relevance between the rock physical property and the geological structure stress state; calculating a dynamic adjustment coefficient according to the relevance between the rock physical property and the geological structure stress state; the resource reserve estimation module is used for estimating mineral resource reserves according to the dynamic adjustment coefficient; and the resource evaluation module is used for evaluating the mineral resource reserves to obtain a final evaluation result. According to the method, accurate analysis of the rock physical property and the geological structure stress state is realized, so that the accuracy and the reliability of exploration and evaluation of mineral resources are greatly improved.

The invention provides a limb nerve rehabilitation state evaluation method based on multi-modal sensor data fusion. Motion inertia data, electromyographic signal data and text data of a corresponding limb nerve rehabilitation action manual of a patient during rehabilitation actions are obtained in real time; inputting the data into a designed and trained multi-modal data feature extraction network to obtain motion inertial data features, electromyographic signal data features and text semantic features; inputting the motion inertia data features, the electromyographic signal data features and the text semantic features into a designed and trained multi-modal data feature fusion network to obtain multi-modal fusion features; and inputting the multi-modal fusion features into a trained prediction output network to obtain a limb nerve rehabilitation state prediction value of the patient. Through multi-modal data fusion and time-dependent feature extraction, the limb nerve rehabilitation state of the patient is evaluated more accurately, and a more reliable diagnosis basis is provided for doctors. Meanwhile, the labor cost is reduced and the evaluation efficiency is improved.

The invention discloses a contract evaluation method, system and device based on a large model and a medium, and the method comprises the steps: obtaining a target contract, carrying out the data preprocessing, obtaining the preprocessed contract data, and inputting the preprocessed contract data into a preset contract large language model; the preset contract large language model stores a vector knowledge base including coastal bulk cargo transportation knowledge, legal clauses and industry regulations; in a preset contract big language model, performing contract classification and contract summary extraction on the current preprocessed contract data by using a first model agent to obtain contract summary information; performing contract risk assessment on the current preprocessed contract data to obtain risk assessment information and / or risk avoidance suggestion information; performing benefit measurement and calculation on the current preprocessed contract by using a third model agent to obtain benefit measurement and calculation information; according to the method, the examination and evaluation of the large model in the coastal bulk cargo transportation contract are realized, and the purposes of saving the labor cost and improving the business turnover rate are achieved.

The invention provides a senile dementia clock drawing experiment automatic evaluation method and system based on non-rigid registration, and belongs to the technical field of artificial intelligence, and the method comprises the steps: S1, obtaining clock drawing experiment data of a testee, and carrying out the preprocessing of the obtained clock drawing experiment data, and obtaining a first point cloud image; s2, performing non-rigid registration on the first point cloud image and a preset standard template to obtain a second point cloud image after non-rigid registration; s3, performing clock drawing experiment analysis on the second point cloud image to obtain an analysis result; and S4, scoring the analysis result according to a preset scoring standard to obtain a total score of the senile dementia scale of the testee. The non-rigid registration method based on machine vision has the advantages that automatic and intelligent evaluation of the senile dementia scale clock drawing experiment is achieved, evaluation efficiency and accuracy are improved, a more effective auxiliary means is provided for diagnosis and treatment of senile dementia patients, and the non-rigid registration method based on machine vision has wide application prospects.

The invention discloses a multi-language translation method and system, and relates to the field of electrical digital data process.The method comprises the steps that cultural feature information and semantic structure information are obtained; splitting the source language text into a plurality of semantic units based on the semantic structure information; retrieving cultural connotation information of which the association degree with the semantic unit is greater than a preset threshold value; determining that the semantic unit is a culture sensitive semantic unit; extracting a target language expression mode based on the cultural connotation information; performing semantic combination on the target language expression mode and standard translation results of other semantic units except the culture sensitive semantic unit in the source language text to obtain a translation result; judging whether the semantic coherence of the translation result meets a preset condition or not; if the preset condition is met, outputting a translation result; and if the preset condition is not met, re-executing the step of semantic combination. The accuracy of the cultural connotation and the emotional color contained in the transmission source language is improved, and then the cultural adaptability of the translation result is improved.

The invention discloses a big language model evaluation system and method, and belongs to the technical field of big language model evaluation. The system comprises a data preparation module, a basic performance evaluation module, an efficiency evaluation module, a robustness and multi-mode evaluation module, a distributed task scheduling module and a feedback optimization module. Through the system, the technical effect of multi-dimensionally, efficiently and automatically evaluating the large language model is achieved.

The invention discloses an ecological product carbon sink value accounting method, belongs to the technical field of resource evaluation, and solves the problem that a regional carbon sink estimation result has deviation due to the fact that the existing method is insufficient in single remote sensing data coverage range and resolution and is difficult to adapt to spatial heterogeneity of a region to which a product belongs. The method comprises the following steps: acquiring multi-source heterogeneous carbon sink monitoring data associated with a sub-monitoring area in real time according to a preset acquisition period, preprocessing the multi-source heterogeneous carbon sink monitoring data, and performing data enhancement on a normalized data set based on a Mosaic-Mixup mixing method; executing the carbon sink value accounting model, wherein the carbon sink value accounting model outputs a carbon sink value accounting result; according to the method, a method of preprocessing the multi-source heterogeneous carbon sink monitoring data and performing data enhancement on the normalized data set is adopted, so that accurate and scientific data support can be provided for the carbon sink value accounting of the ecological product, and the carbon sink capacity of the regional ecological product can be accurately evaluated by the carbon sink value accounting model.

The invention discloses an LLM-based graduation design thesis intelligent evaluation system. The system comprises a data input module, a preprocessing module, an LLM evaluation module and an evaluation result output module. Text data of graduation papers are input into the data input module, the data input module is connected with the preprocessing module, the text data, processed by the preprocessing module, of the graduation papers are input into the LLM evaluation module, and the evaluation result output module is connected with the LLM evaluation module. According to the system, a large language model is utilized to perform multi-dimensional evaluation on graduation theses submitted by students, including but not limited to content quality, logic structure, language expression, innovation, academic specification and the like. According to the LLM-based undergraduate thesis evaluation system, the LLM can adapt to thesis evaluation requirements in different subject fields through a fine adjustment mode.

The invention discloses a tongue picture characteristic change rule analysis method based on the rehabilitation process of a chronic disease patient, and relates to the technical field of health big data analysis, and the method comprises the steps of tongue picture data standardized collection, tongue picture data recording system establishment, tongue picture characteristic data analysis, result visualization and report generation. According to the invention, through a standardized tongue picture data acquisition mechanism, the quality and consistency of the tongue picture data are ensured, and through controlling illumination conditions, background colors, diet restrictions and posture requirements, the influence of external factors on the tongue picture data is reduced, and the accuracy and reliability of the data are improved. By comprehensively evaluating definition, noisy points, contrast ratio and color accuracy verification parameters, it is ensured that collected tongue picture data reaches a preset quality standard, and a high-quality data basis is provided for subsequent analysis; meanwhile, a comprehensive tongue picture data recording system is established, and tongue picture data are effectively stored and managed.

The invention discloses a liquid nitrogen preservation effect evaluation method and system based on big data. The method comprises the steps of data acquisition, data preprocessing, establishment of a liquid nitrogen preservation effect evaluation model and liquid nitrogen preservation effect evaluation. The invention belongs to the field of effect evaluation, and particularly relates to a liquid nitrogen preservation effect evaluation method and system based on big data, according to the scheme, a dynamic activation function is designed by introducing learnable parameters, and the prediction stability is improved; a regularization item is constructed based on the module weight so as to design a loss function, and the prediction accuracy of liquid nitrogen preservation effect evaluation is improved; through gradual updating module by module, the capability of capturing subtle changes of liquid nitrogen preservation effect evaluation data is enhanced; and the liquid nitrogen preservation effect evaluation efficiency is improved based on secondary dynamic optimization correction parameters.

The invention relates to an urban park physical examination evaluation system construction method based on a machine learning algorithm. The method comprises the following steps: S1) selecting an evaluation index set; s2) taking a park system, an urban comprehensive park, an urban community park and an urban micro-greenbelt collaborative group as evaluation scales, and selecting evaluation indexes from the evaluation index set; s3) acquiring specific data of evaluation indexes to form an index data set; s4) screening repeated indexes with complex collinear features in all index data sets by using a variance expansion coefficient; s5) clustering by using a K-medoids clustering algorithm, and S6) based on an SHAP machine learning algorithm, performing full sample analysis and outputting the importance degree of the index factors, and constructing an urban park physical examination assessment system based on the importance degree of the index factors.According to the method, subjectivity and uncertainty of a traditional assessment method can be avoided, the assessment efficiency is improved, and rapid updating can be performed.

The invention discloses a tunnel construction quality evaluation system and method. The evaluation system comprises a data acquisition module, a quality evaluation standard system, an early warning and notification module and a data management module. Wherein the data acquisition module is used for acquiring construction vehicle data, construction site sensors and site photographing; the quality evaluation standard system comprises drilling quality evaluation, back break evaluation, primary support thickness evaluation, anchor rod construction quality evaluation, waterproof and drainage pipe quality evaluation, steel bar binding quality evaluation, secondary lining quality evaluation and primary support flatness evaluation; the early warning and notification module integrates early warning signals from all the evaluation modules; and the data management module is responsible for storing data generated by each independent module and executing cross-module data analysis. According to the tunnel construction quality evaluation system, by integrating advanced monitoring equipment, an automatic algorithm and comprehensive data analysis, the quality control effect in the tunnel construction process is remarkably improved.

The invention discloses an industrial park groundwater pollutant screening and identification method, which comprises the following steps: firstly, scoring the source strength, toxicity and path of pollutants through a comprehensive scoring method, and carrying out preliminary screening according to the scoring result to determine preliminarily concerned pollutants, thereby being beneficial to narrowing the screening range and reducing unnecessary evaluation work; the evaluation efficiency is improved. Meanwhile, the ITD index model constructed based on the three dimensions of source intensity, toxicity and path can more comprehensively consider the potential risk of the pollutants, and a scientific basis is provided for an evaluation result. The toxicity test result is introduced, so that the evaluation result is more accurate, and experimental data support is provided for the evaluation result. The method can provide scientific basis and technical support for underground water pollution prevention and control in industrial parks. According to the comprehensive evaluation result, corresponding risk prevention and control measures are provided for the optimal control pollutants in the list, the underground water pollution risk of the industrial park is reduced, and the environment and human health are protected.

The invention discloses a traditional Chinese medicine planting site selection evaluation method, system and device based on big data and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring a traditional Chinese medicine category of to-be-planted traditional Chinese medicine and soil data and meteorological data of a plurality of candidate planting areas; based on the plant growth parameters corresponding to the traditional Chinese medicine categories, establishing a planting area evaluation standard; performing evaluation processing on the soil data and the meteorological data of each candidate planting area according to a planting area evaluation standard to obtain an environmental adaptability index; receiving the multispectral image of each candidate planting area, determining the vegetation coverage and water and soil loss rate of each candidate planting area, and calculating an environmental risk index; and determining corresponding site selection priorities in combination with the environmental adaptability indexes and the environmental risk indexes, and taking the candidate planting area with the highest site selection priority as a target site selection area of the to-be-planted traditional Chinese medicine. By implementing the technical scheme provided by the invention, the accuracy of traditional Chinese medicine planting site selection evaluation can be improved.

The invention belongs to the field of artificial intelligence, finance and medical treatment, and relates to an algorithm model verification and precision evaluation method, which comprises the steps of calling a pre-constructed original algorithm model to process an original sample file set to obtain a to-be-evaluated model result, and associating an original sample file with the to-be-evaluated model result to obtain a to-be-evaluated model result; performing annotation task allocation according to the generated annotation task allocation scheme, receiving a truth value result submitted by the annotation personnel, comparing a to-be-evaluated model result with the corresponding truth value result to obtain an initial model precision evaluation result, optimizing the model according to the initial model precision evaluation result, and evaluating the optimization algorithm model to obtain an evaluation result. And generating a model performance comparison report. The invention further provides an algorithm model verification and precision evaluation device, equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the original sample file can be stored in a block chain. According to the method, the model iteration efficiency can be greatly improved, and the precision and performance of the model are improved.

The invention discloses a software testing method and system based on a large model, and relates to the technical field of software testing, and the method comprises the following steps: step 1: describing a code review rule, and expanding specifications required to be checked: firstly, listing the check specifications required to be satisfied by a code, and according to a thinking chain and a zero- / feed-shot example, establishing a list of the check specifications required to be satisfied by the code; the check rules in the list are described as reasoning instructions of the model according to the check key points and the check steps through combination of one or more technologies of context learning; 2, code slicing: performing structure analysis and dependency analysis on the tested software project: firstly, slicing the code according to a function by utilizing a code analysis tool; according to the software testing method and system based on the large model, convenient project management, user-defined configuration and high-automation-degree test execution can be implemented on a software evaluation task, and the evaluation efficiency is effectively improved.

The invention belongs to the field of photovoltaic technology, and discloses a method and system for evaluating different types of roof photovoltaic installation potentials in different climate regions, and the method comprises the steps: shooting different types of aerial images, including orthographic top views and horizontal side views, of buildings with installed roof photovoltaic in different climate regions by using an unmanned aerial vehicle, and combining a roof / photovoltaic identification model to identify the installation potential of different types of roof photovoltaic in different climate regions; and the roof area and the photovoltaic area of each building in the image are counted, and the quotient of the photovoltaic area and the roof area is a roof available coefficient, so that the roof available coefficients of different types of buildings in different climate regions are summarized. The coefficient is closer to an actual value and is more comprehensive and practical compared with 100% utilization or 3D shadow analysis, and in an existing simple coefficient multiplication method, the value of the coefficient is not perfect and scientific. Recognizing the building roof area in the region by combining a roof recognition model; and determining functional attributes of the house building according to the POI data.

The invention provides a multi-modal spoken language pronunciation evaluation method based on a large language model, and belongs to the technical field of spoken language evaluation, and the method comprises the steps: obtaining the audio data of a spoken language tester; performing feature coding processing on the audio data through an acoustic encoder to obtain audio representation information, and mapping the obtained audio representation information into a public space through a modal adaptation layer; setting an audio evaluation instruction, separating the audio evaluation instruction into a plurality of phrases through a word segmentation device, converting the phrases into high-dimensional text features through a word embedding module, and mapping the high-dimensional text features into a public space; splicing the audio representation information in the public space with the high-dimensional text features, carrying out multi-modal feature combination, and constructing an evaluation sequence; and the big language model carries out evaluation prediction on the evaluation sequence to obtain a corresponding pronunciation accuracy evaluation result and a fluency evaluation result. The method does not need to depend on an automatic voice recognition system, and the evaluation efficiency of the audio data is greatly improved while the evaluation process is simplified.

A large model agent generation content quality evaluation method based on double baselines comprises the steps that data generated by human beings is acquired, preprocessing and semantic segmentation are carried out, and data samples after semantic segmentation are formed; performing theme extraction on the data samples after data segmentation to form a theme list; the content of the data forming the theme list is generated through an intelligent agent workflow and the content of the data forming the theme list is directly generated through a large model, and an evaluated sample and a contrast sample are obtained; comparing and scoring the data sample after semantic segmentation, the evaluated sample and the contrast sample; selecting a sorting algorithm to carry out score conversion on the graded and compared samples; and performing statistical verification and result analysis. According to the method, a comprehensive, reliable and efficient solution is provided for quality evaluation of the generation content of the large model agent. The method not only can accurately evaluate the content quality, but also provides powerful support for continuous optimization of an intelligent agent system.

The invention relates to the technical field of cement-based composite cementing material preparation, in particular to a low-carbon environment-friendly cement-based composite cementing material and a preparation method thereof.The preparation method comprises the steps that an initial forming object is subjected to regional division according to position characteristics so as to obtain real-time monitoring results of all target monitoring regions, determining the actual state of each target monitoring area according to the real-time monitoring result; analyzing the actual state to determine a single mixing amount set of each target monitoring area; integrating the single mixing amount sets to obtain a target mixing amount set, and sequentially performing stirring and pouring molding according to the target mixing amount set to obtain a target molded object; in the stirring process, the initial stirring parameters are adjusted according to the actual stirring degree in combination with the overall analysis result, so that actual stirring parameters are determined; and in the pouring forming process, the initial pouring parameters are adjusted according to the bubble generation rate in combination with the overall analysis result, so that the actual pouring parameters are determined.

The invention relates to the technical field of monitoring intelligent management, and discloses a monitoring video intelligent inspection management method and system based on artificial intelligence. The method comprises the following steps: collecting historical video monitoring data, establishing a sample set, preprocessing the historical video monitoring data in the sample set, and extracting abnormal behavior characteristics and spatial-temporal characteristics in the historical video monitoring data through a machine learning mode based on the preprocessed historical video monitoring data; meanwhile, monitoring camera reminding frequency is set based on extraction of spatio-temporal characteristics in historical video monitoring data, and a video monitoring event is set, so that after an administrator selects a frame of video monitoring data in a corresponding time period, a selected video picture is identified and an inspection record is generated based on a machine learning mode and a data matching mode; and finally, by setting an inspection evaluation management standard and evaluating and optimizing an inspection record generated by an administrator, the precision of intelligent inspection of the monitoring video is improved.

The invention relates to the technical field of speech recognition effect evaluation, in particular to a speech recognition evaluation method based on artificial intelligence. The method comprises the following steps: acquiring to-be-evaluated voice data, analyzing the to-be-evaluated voice data to obtain a voice fluency index, a voice clarity index and a voice accuracy index, and calculating to obtain a first voice quality index of the to-be-evaluated voice data based on the voice fluency index, the voice clarity index and the voice accuracy index; inputting the to-be-evaluated voice data into the voice content recognition model, outputting a prediction text of the to-be-evaluated voice data, and performing comparative analysis on the prediction text and the labeled text to obtain a second voice quality index of the to-be-evaluated voice data; and obtaining a voice recognition evaluation result corresponding to the to-be-evaluated voice data based on the first voice quality index and the second voice quality index. According to the invention, the evaluation efficiency and accuracy of the speech recognition effect can be improved.

The invention provides an aircraft load bridge monitoring method and monitoring system based on a microwave radar, and the method employs the microwave radar to monitor the dynamic displacement of an aircraft load bridge in real time, employs a video recognition technology to recognize an aircraft passing through the bridge, and carries out the comparison with flight information in an airport data system. The model, the quality and the speed of the airplane passing through the bridge are automatically confirmed; then, endowing an airplane model with the obtained airplane mass and speed, establishing an airplane-bridge coupling vibration model considering the bridge deck irregularity, and obtaining the dynamic displacement of the bridge midspan when the airplane passes through the airplane load bridge through nonlinear numerical calculation; and comparing the actually measured dynamic displacement with the theoretically calculated dynamic displacement, and judging whether the aircraft load bridge has a safety problem or not. According to the invention, automation and intellectualization of aircraft load bridge health monitoring can be realized, the efficiency of aircraft load bridge monitoring and evaluation is greatly improved, the cost is saved, and the accuracy of monitoring and evaluation is improved.

The invention discloses a circuit breaker contact wear degree intelligent evaluation system, and belongs to the technical field of circuit breaker contact wear evaluation, the circuit breaker contact wear degree intelligent evaluation system comprises a camera, a data collector, a server and a display, the server comprises a circuit breaker type analysis module, a signal processing module, a wear evaluation module, a wear prediction module and a health monitoring module, the circuit breaker type analysis module, the signal processing module, the wear evaluation module, the wear prediction module and the health monitoring module are in communication connection in sequence; the display comprises a data display module; according to the invention, the wear degree of the contact head of the circuit breaker can be intelligently evaluated, and meanwhile, the system also has the functions of wear degree prediction, residual use frequency calculation and wear frequency early warning, so that the maintenance and management efficiency of the circuit breaker can be greatly improved, and the equipment fault risk is reduced.

The invention relates to the technical field of clustering analysis, and particularly discloses a fruit growth monitoring system, which comprises an acquisition module for acquiring a target value at a time point, acquiring target data based on the target value, and generating a target point; the clustering analysis module is used for setting a clustering radius and clustering the target points according to the density of the target points in the clustering radius; the clustering optimization module is used for adjusting a clustering cluster according to the theoretical gravity center and the maximum distance when the density of the target points in the overlapping region meets the condition; and the result module obtains the standard points and judges the growth state of the fruits based on the standard points. According to the invention, the efficiency of monitoring the growth state of the fruits can be improved.

The invention discloses a supplier quality evaluation method, and relates to the technical field of data quality analysis, and the method comprises the steps: obtaining a data initial quality evaluation label of each supplier; counting an uploaded information quality processing comprehensive data quality evaluation value of each type of suppliers; determining an initial quality detection constraint period of each type of suppliers and performing quality tracking detection; obtaining quality tracking detection data, and analyzing and processing to obtain a quality tracking monitoring result; according to the method, the data quality of the data uploaded by the suppliers is analyzed, the availability of the quality evaluation data is ensured, the suppliers whose initial quality evaluation is unqualified are screened, and the quality of the suppliers is evaluated to be qualified. Quality evaluation resources are concentrated on suppliers whose initial quality evaluation is qualified, customized quality tracking detection is carried out on each type of suppliers, the quality tracking detection efficiency and result are improved, and the quality detection constraint period is dynamically adjusted in time.

The invention relates to the technical field of sewage treatment, in particular to a sewage treatment effect assessment method and system based on data analysis, which improve the quality of sewage treatment effect assessment and realize accurate assessment of sewage treatment effect. The method comprises the following steps: acquiring biochemical data information of a water quality sample before and after sewage treatment and microscopic image information of the water quality sample after sewage treatment; performing water quality biochemical feature extraction on the water quality sample biochemical data information before and after sewage treatment, and calculating to obtain water quality biochemical feature change vectors before and after sewage treatment; inputting the water quality biochemical characteristic change vector into a water quality treatment biochemical effect evaluation model to obtain a first-order sewage treatment effect evaluation result; performing water quality image feature extraction on the water quality sample microscopic image information after sewage treatment to obtain a water quality image feature set; and aiming at each water quality image feature in the water quality image feature set, respectively comparing with a corresponding preset image feature.