111 results about "Fuzzy mathematics" patented technology

The invention discloses a mine ecological environment restoration evaluation method and system based on deep learning, and the method comprises the steps: obtaining related data and evaluation indexes of a mine ecological environment restoration effect, carrying out the fuzzification of the indexes through employing a fuzzy mathematical theory, and obtaining a fuzzy evaluation index set; constructing a fuzzy evaluation index system according to the fuzzy evaluation index set, and obtaining a fuzzy score matrix of each evaluation index and fuzzy information of the fuzzy score matrix; based on fuzzy information of the fuzzy scoring matrix, high-level features of the fuzzy information are extracted; determining different evaluation grades and standards according to the clustering result, and representing the matching degree between the evaluation object and each evaluation grade by adopting a fuzzy membership degree to obtain an evaluation result; establishing a fuzzy reasoning rule base by using a fuzzy reasoning technology; and performing information fusion on the fuzzy scores of the evaluation indexes by adopting a fuzzy integral method, and comprehensively considering the interaction influence and the importance degree difference between the evaluation indexes to obtain a final comprehensive evaluation result of the mine ecological restoration effect.

The invention discloses a reservoir multi-target optimization scheduling scheme optimization method and system based on multi-party coupling, and belongs to the field of reservoir scheduling. The system comprises the steps that firstly, boundary conditions of a simulation system are determined, and then a reservoir multi-target optimization scheduling model is constructed; and then solving the reservoir multi-objective optimization scheduling model by using a non-dominated sorting genetic algorithm of the reference points, verifying the effectiveness of the solving method by using a standard multi-objective test function, and evaluating and optimizing a reservoir scheduling scheme by using a method of combining a grey target theory, a cumulative foreground theory and a fuzzy mathematical method. According to the system, the multi-objective optimization problem among flood control, power generation and ecology of the reservoir is coordinated, decision support is provided for formulating a reservoir dispatching scheme of multi-objective optimization dispatching of the reservoir, the contradiction among flood control, power generation and downstream river ecology can be effectively coordinated, and the flood control and power generation benefits are increased on the basis of considering the downstream ecological flow demand as much as possible.

The invention relates to the technical field of network security management, in particular to a network security management system based on big data, which comprises a data acquisition and integration unit, a dynamic threshold setting unit, a fuzzy comprehensive evaluation unit, a machine learning optimization unit and a control unit. The acquisition process has intelligent characteristics and adopts a block chain to cache data, the dynamic threshold setting unit constructs a model to adjust a threshold by combining a hidden Markov model, kernel density estimation and a reinforcement learning algorithm for different network crime types, and the fuzzy comprehensive evaluation unit determines a membership function and distributes weights by applying a fuzzy mathematical algorithm. And the machine learning optimization unit uses historical data to train and update the model, assists in case-related account determination, effectively solves the problems of missed determination and misjudgment caused by a fixed threshold value in traditional account risk assessment, and improves the accuracy of network criminal account risk assessment.

The invention discloses a large transport vehicle bridge safety assessment method based on fuzzy comprehensive evaluation, which comprises the following steps: constructing a bridge bearing capacity reduction coefficient model, integrating four factors of material performance degradation, structural damage, environmental corrosion and load combination, and determining index weights by adopting an analytic hierarchy process; and a multi-stage evaluation system is established in combination with a fuzzy mathematics theory. A prestressed concrete continuous beam bridge in Jiangsu section of Jinghai highway is taken as an object, finite element simulation is used for analyzing the load effect of large vehicles under independent and mixed passing conditions, and verification shows that when the large vehicles pass at the mixing rate of 20%, the most unfavorable section safety coefficient of the bridge reaches 1.35, and the standard requirements are met. According to the method, fuzzy mathematics and structural mechanics analysis are creatively fused, a standardized process of parameter collection, model calculation and safety judgment is established, the efficiency is improved by 40% or above compared with a traditional static load test, the method is applied to transportation examination and approval of five bridges in Jiangsu province, a scientific basis is provided for selection of large transportation channels, and the risk of bridge damage is effectively prevented.

The invention relates to the technical field of information security, in particular to a network security risk assessment method and system based on fuzzy mathematics, and the method comprises the following steps: based on dynamic monitoring data of node data in a network environment, extracting multiple risk factor parameters, dividing a parameter value range, comparing risk level intervals, and carrying out the statistics of a differentiation interval distribution proportion. And generating a network risk factor membership distribution table. According to the method, network node data are dynamically monitored, multiple risk factors are accurately analyzed, attribution range division is refined, the distribution relation between parameters and risk levels is defined, the distribution proportion and weight influence are analyzed, an interactive risk distribution model is formed, factor relevance is revealed, a significant characteristic group is screened, and the time dimension change rule is combined, so that the risk level of the network is determined. And key risk feature data is extracted, the dynamic monitoring capability is enhanced, the accuracy, comprehensiveness and dynamic adaptability of risk assessment are improved, the conversion from static analysis to real-time response is realized, and complex network threats are effectively dealt with.

The invention discloses an improved food sensory quality evaluation method and system based on a fuzzy mathematical method, and relates to the technical field of food inspection and detection. Performing a single-factor test on the improved food sample, and performing a response surface test on the basis of the single-factor test; performing comprehensive sensory evaluation on each sample in the response surface test by adopting a fuzzy mathematical analysis method; and physical and chemical indexes of the improved food under the optimal process are determined. According to the invention, the technology of the improved food is optimized, and the physicochemical indexes of the improved food with the optimized response surface are measured; a single-factor test and a response surface test are carried out in sequence, sensory scores are taken as evaluation standards, and factors influencing the quality of the improved food are determined; the optimal formula of the improved food is finally determined through a verification experiment; a fuzzy mathematics comprehensive sensory evaluation model is established for the improved food, and the obtained sensory evaluation result is used for response surface optimization evaluation.

The invention relates to the technical field of agricultural data dynamic perception, in particular to an agricultural data dynamic perception scheduling method based on the Internet of Things, and the method is realized based on an Internet of Things sensor, an edge computing platform and an edge server. Comprising the following steps: deploying Internet of Things sensors including a meteorological station, a soil humidity monitor and an unmanned aerial vehicle inspection system, and deploying a real-time data processing module on an edge server through an edge computing platform. According to the method, a dynamic cost-benefit analysis model is constructed, various factors and dynamic changes in agricultural production are comprehensively considered, a multi-objective optimization algorithm and a dynamic planning technology are applied, optimization of resource allocation and maximization of long-term benefits are achieved, in addition, uncertainty factors are processed by introducing a fuzzy mathematical method, and the method is suitable for large-scale popularization and application. The method improves the robustness and reliability of analysis, and solves the problems of lack of dynamics, incomplete consideration factors and limited optimization means in a traditional scheme.

The invention provides an ion adsorption type medium and heavy rare earth ore mineralization prediction method which comprises the following steps: (1) screening ion adsorption medium and heavy rare earth mineralization prediction indexes according to mineralization theory understanding; (2) calculating the weight of each prediction index by using an analytic hierarchy process; (3) on the basis of a group decision-making method, calculating an expert weight coefficient, and solving a comprehensive index weight; (4) constructing a membership function of each prediction index by adopting a fuzzy mathematics method, and carrying out membership calculation; and (5) integrating the weight and the membership degree of each prediction index, fitting and constructing an ion adsorption type medium and heavy rare earth mineralization prediction model, and performing mineralization prediction. According to the method, expert cognition is effectively simulated, errors caused by subjective judgment can be remarkably reduced, the reliability of a metallogenic prediction result is improved, compared with a traditional method, the success rate of finding ion adsorption type medium and heavy rare earth ore is greatly increased, and then the prospecting exploration efficiency can be effectively improved.

The invention relates to a mine water depth sealing layer site selection evaluation method and system based on multi-parameter coupling. The method comprises the following steps: acquiring geological, hydrological and engineering parameters through geological exploration equipment and the like, and carrying out wavelet transform noise reduction and Kriging interpolation processing; determining a key parameter set and weight by using an analytic hierarchy process, constructing a comprehensive evaluation model coupling the analytic hierarchy process and fuzzy mathematics, and generating a membership matrix and a multi-field coupling numerical model; and calculating a fitness index through spatial overlay analysis, generating a sealing suitability partition map, outputting an evaluation report containing risk early warning, and generating an interactive three-dimensional site selection decision interface. The system comprises a data acquisition and preprocessing module, a parameter processing module, a weight distribution module and the like. The simulation precision and the risk positioning efficiency are improved, and a comprehensive evaluation scheme is provided for site selection of the sealing layer of the water depth of the mine.

The invention provides an unmanned aerial vehicle distribution center site selection method based on a fuzzy mathematical programming particle swarm algorithm, aims to complete position selection of a park distribution center under multi-target and complex constraint conditions under the background of low-altitude economy, intelligent logistics and unmanned distribution, and comprises the following steps: carrying out detailed modeling characterization on a park multi-unmanned aerial vehicle distribution center site selection problem; delivery time and operation cost targets are subjected to target reduction through fuzzy mathematical programming, solving under complex constraint conditions is facilitated, the particle swarm optimization optimizes the search process through an elitism strategy, a limited number of Pareto solutions are obtained through an epsilon-constraint method, convergence is gradually carried out to an optimal solution, and the optimal solution is obtained. The method is suitable for multi-unmanned-aerial-vehicle distribution in an unattended park, the load and cruising ability of the unmanned aerial vehicles, energy consumption, no-fly zone distribution and other scenes with complex constraint conditions are considered, and an efficient and accurate unmanned aerial vehicle distribution center site selection scheme can be provided.

The invention relates to the technical field of bridge construction, in particular to a multi-span continuous rigid frame bridge closure jacking force optimization method and system.The method comprises the steps that firstly, construction steps corresponding to a closure sequence scheme are determined according to the closure sequence scheme; secondly, performing soil constraint degradation simulation according to a closure sequence scheme and the corresponding construction steps, and establishing a finite element model of a full bridge; then, parameters corresponding to the unit jacking force applied to each closure gap and parameters corresponding to the unit jacking force not applied to each closure gap are calculated based on the finite element model, and a to-be-solved function is constructed based on the first parameters and the second parameters; finally, a fuzzy mathematical solution is adopted, the multi-target optimization problem corresponding to the to-be-solved function is converted into a single-target linear programming problem, and the optimal solution of the jacking force is obtained.According to the scheme, the soil constraint degradation effect is comprehensively simulated, meanwhile, the multi-target problem in the deepwater environment is converted into the single-target linear programming problem, and the optimal solution of the jacking force is obtained. The solving process is simplified, and the optimal solution of the jacking force can be accurately solved.

The invention discloses a comprehensive evaluation method for the health state of concrete filled steel tubes. According to the method, a multilevel evaluation index system for the health state of the concrete-filled steel tube structure is constructed, and factors influencing the health of the structure are divided into a plurality of key indexes including the ultimate bearing capacity, the overall stability performance, the anti-seismic performance and the like. The method comprises the following steps: firstly, quantifying each index by using a membership function in fuzzy mathematics, and constructing a membership matrix; secondly, determining the weight of each index according to the influence of each index on the whole bridge; then, the health state of the concrete filled steel tube is evaluated through the fuzzy comprehensive evaluation model, the structure health level is generated, an accurate health state evaluation result is provided, and the method is suitable for health monitoring and evaluation of complex concrete filled steel tube structures such as bridges, tunnels and high-rise buildings. The method has the advantages of being high in evaluation precision, wide in application range and easy and convenient to operate, and a scientific basis is provided for safety management and maintenance decision making of the concrete-filled steel tube structure.

The invention discloses a multi-dimensional comprehensive evaluation method for permeability resistance of overlying strata of a working face, and belongs to the technical field of mine engineering and geological safety evaluation. 12 types of core factors such as rock strength, rock core quality, physical and mechanical properties of rock mass, hydrological properties and mining influence characteristics are integrated; a full-process evaluation framework of data acquisition, index system construction, weight distribution, comprehensive modeling and verification optimization is constructed, an analytic hierarchy process and an entropy evaluation method are coupled to determine index weights, a dynamic evaluation model is constructed in combination with a fuzzy mathematics theory, and accurate classification and risk early warning of the permeability resistance of the overlying strata are realized. According to the method, through comprehensive analysis of a plurality of factors, the accuracy of overlying strata permeability resistance evaluation can be improved, so that the underground water permeation path and the permeation amount are predicted more accurately, the uncertainty is reduced, the comprehensiveness and the accuracy of evaluation are remarkably improved, and a scientific basis can be provided for mine water disaster prevention and control and safe mining.

The invention relates to the technical field of power distribution and utilization, and provides a community-level electric vehicle-household energy storage collaborative scheduling method and system. The method comprises the following steps: dividing real-time electricity price, battery SOC and external temperature into a plurality of fuzzy subsets, and determining a membership function of each fuzzy subset based on a TSK fuzzy mathematical model; introducing a price sensitivity parameter, a battery state parameter and a temperature sensitivity parameter, formulating a fuzzy rule of each fuzzy subset in three dimensions, and quantitatively evaluating the response willingness of the electric vehicle through fuzzy reasoning of all membership functions; an SAC algorithm is adopted, a state space and an action space are respectively designed according to the community environment, and an overall reward function is constructed by combining power grid benefit rewards, user comfort rewards and electric vehicle demand response rewards; and inputting a quantitative evaluation result into an SAC algorithm to obtain an optimal scheduling strategy of the energy storage resources. According to the invention, collaborative scheduling optimization of the electric vehicle cluster and the household energy storage device is realized.

The invention relates to the technical field of risk level assessment, and discloses a chemical enterprise electric power operation safety risk early warning method and system. According to a power operation site of a chemical enterprise, accident types are summarized, causes are analyzed, and a risk identification table is designed based on a fault mode and influence analysis method and a Hall three-dimensional model. Based on the risk identification table, constructing a fault tree model by using a fault tree analysis method, constructing an accident tree model by using an accident tree analysis method, performing risk reason logic relation analysis through the fault tree model, making prevention and control measures through the event tree model, and performing qualitative analysis on the fault tree model. And performing assignment and feedback by utilizing a Delphi method, performing fuzzy processing on data by utilizing a fuzzy mathematics theory so as to reduce evaluation deviation generated by subjective factors, and finally solving the risk probability of a fault tree top event and a middle event. And the operating personnel comprehensively evaluate the risk according to the risk probability, so that field personnel can take management and control measures in time, and accidents are prevented.

The invention relates to the technical field of agricultural information, in particular to a product supplier and consumer matching method and system based on information axiom, and the method comprises the steps: recognizing the attributes of agricultural products; defining a system range and a design range for each attribute; for each matching scheme between the consumer and the supplier, checking whether all hard attributes are met or not, and if not, filtering out the matching scheme; for the soft attributes, calculating the information amount from the perspective of consumers and the perspective of suppliers: for the quantitative soft attributes, calculating the information amount according to the types of the quantitative soft attributes; for qualitative soft attributes, applying a fuzzy mathematical method, and then calculating information amount; respectively calculating the total information amount of the consumer perspective and the total information amount of the supplier perspective; establishing a multi-objective optimization model; for all possible matching schemes, calculating the total information amount of consumers and suppliers, and determining respective maximum values and minimum values; for each matching scheme, calculating a normalized membership function value by comparing the total information amount with the maximum value and the minimum value of all the matching schemes; the matching scheme enabling the weighted comprehensive score of the membership function to be the highest is selected. The invention provides an intelligent matching method which can comprehensively consider unique attributes, dynamic transaction demands and fuzzy language features of agricultural products, so as to optimize supply and demand matching and promote agricultural product sales and sustainable economic development.

The invention discloses a large-model intelligent question setting system and method based on fuzzy mathematics fine tuning, and belongs to the technical field of intelligent question setting. Comprising a fuzzification processing module, a multi-dimensional reward feedback module, a rule-driven attribute reasoning module, an attribute accurate quantification module, a self-adaptive membership degree adjustment module, a strategy optimization and intra-cluster standardization module and a question generation and structured output module. According to objective fields such as post specifications, post levels, technical stack depth and team scales, hard indexes are converted into soft boundary semantics through five membership functions, and then quantitative attributes of surface test questions on difficulty, openness, prejudice and distinction are reasoned by using N rules without subjective wording. And the business result data is used for driving rewards to be updated online, and finally, daily automatic fine tuning is realized on the 32B large model, so that each subjective surface test question generated by the AI not only meets the objective requirements of posts, but also has explainable, auditory and iterable closed-loop capabilities.

The invention discloses a machine vision-based annona squamosa cultivating and picking integrated method, which comprises the following steps of: firstly, acquiring image data of annona squamosa through an unmanned aerial vehicle, constructing a three-dimensional environment model of the annona squamosa by combining a multi-view three-dimensional reconstruction algorithm, and extracting spatial data of the annona squamosa; then, the annona squamosa is clustered according to spatial distribution of the planting area, and a robot carrying a mechanical arm is dispatched for each cluster to conduct cultivation and picking operation; then the unmanned aerial vehicle is controlled to count the number of annona squamosa in each cluster, and path planning is conducted on the robot in each cluster; and finally, generating a mechanical arm force control scheme, a moving speed control scheme and a light supplementing quantity control scheme of each cluster of robots based on fuzzy mathematics, and cultivating and picking the annona squamosa by each cluster of robots according to the generated schemes. The machine vision and fuzzy control technology is combined, the annona squamosa cultivation and picking integrated service is achieved, the annona squamosa cultivation and picking efficiency and yield are improved, and the bad fruit rate and the damage rate are reduced.

The embodiment of the invention provides an intelligent power optimization and control method for an all-vanadium redox flow energy storage system, which comprises the following steps: establishing a mathematical model of the all-vanadium redox flow energy storage system, the mathematical model comprising a galvanic pile model, an electrolyte circulation model and a pump model, and setting a state variable, an input variable and an output variable; based on historical day illumination, temperature and wind speed data, photovoltaic and wind power generation and power grid load demands are predicted by using a machine learning method, and the total power demand of an energy storage system is calculated; inputting the total power demand signal to the energy storage system, and generating a power distribution and control instruction; constructing a multi-objective optimization model for the operation of the all-vanadium redox flow battery energy storage system, wherein the multi-objective optimization model comprises a multi-objective function, a constraint condition and a power distribution evaluation index; adopting a fuzzy mathematics theory to carry out membership degree unification processing on the multi-objective function; distributing power based on a two-step method strategy; and executing a power instruction based on the segmented quantized cerebellum model neural network-proportional integral differential composite control strategy.

The invention discloses a software quality evaluation method based on a fuzzy theory. The method comprises the following steps: obtaining a quality factor set according to a Meiger software quality model; determining an evaluation grade set, and dividing the evaluation grade set into five evaluation grades; constructing a membership function by adopting a kernel density estimation method; constructing a judgment matrix through the triangular fuzzy number and calculating a defuzzification weight; and converting the score into a fuzzy synthesis value through fuzzy synthesis operation, and generating a fuzzy comprehensive evaluation score through weighted average and normalization processing. According to the method, the fuzzy theory and the Meicole model are combined innovatively, and uncertainty in subjective and objective evaluation is processed by applying fuzzy mathematics. The objectivity, scientificity and repeatability of an evaluation result are effectively improved through a membership function and a weight set constructed based on historical data of similar software. The method is suitable for quality evaluation and optimization decision making of various complex software systems.

The invention relates to the technical field of data communication, in particular to a data communication system for multi-level linkage agent deduction, which is characterized in that in a data acquisition end, basic data of an agent is acquired and verified, and the data is subjected to multi-node processing to obtain deduction data; in the data transmission end, the deduction data is encrypted to obtain encrypted data, the block chain technology is adopted to transmit the encrypted data through multiple industrial control communication protocols, and the encrypted data is verified and monitored in the transmission process; in the data receiving end, decrypting the encrypted data, and performing error correction on the decoded data according to verification and monitoring results in the data acquisition end and the data transmission end; and synchronizing the verified data to a corresponding agent for data updating by adopting a distributed cache technology, performing deduction analysis on the synchronized updated data by adopting a deep learning algorithm, and performing defuzzification on a deduction analysis result by utilizing a fuzzy mathematical algorithm to obtain a deduction decision of the agent.

The invention discloses a post-evaluation method for a road maintenance project. The post-evaluation method comprises the following steps: S1, establishing a post-evaluation index system of an ordered hierarchical structure related to the road maintenance project; s2, calculating a correlation degree between indexes of each level in the post-evaluation index system; s3, on the basis of the association degree between the indexes of each level, constructing the weight of the index of each level; s4, constructing a fuzzy membership matrix of each level index; and S5, performing fuzzy comprehensive evaluation on the maintenance engineering project according to the weight and the fuzzy membership matrix of each hierarchy index, establishing a post-evaluation index system of three structural hierarchies, and adopting a comprehensive evaluation method based on an association degree-AHP-fuzzy mathematics theory to evaluate the maintenance engineering project. The method has the advantages of clear process, strong operability, subjective and objective combination and practical evaluation results.

The present invention relates to the technical field of network security management. Specifically, it relates to a network security management system based on big data, which includes a data collection and integration unit, a dynamic threshold setting unit, a fuzzy comprehensive evaluation unit, a machine learning optimization unit, and a control unit. In the present invention, the data collection and integration unit collects multi-source data and cleans it. The collection process has intelligent features and uses blockchain to cache data. The dynamic threshold setting unit constructs a model to adjust the threshold for different types of network crimes by combining the hidden Markov model, kernel density estimation, and reinforcement learning algorithm. The fuzzy comprehensive evaluation unit uses the fuzzy mathematics algorithm to determine the membership function, allocate weights, and calculate the comprehensive risk score of the account. The machine learning optimization unit uses historical data to train and update the model to assist in the determination of the involved accounts, effectively solving the problems of missed and misjudged cases caused by fixed thresholds in traditional account risk assessment, and improving the accuracy of network crime account risk assessment.

The invention belongs to the technical field of oil and gas exploration and development, and relates to an accident early warning method and system for an FPSO mooring system under an extreme weather condition, and the method comprises the steps: building an accident scene library according to extreme weather data; grading accidents in the accident scene library according to expert opinions; fusing the expert opinions through a fuzzy mathematical method to obtain the weight of each expert opinion; combining expert opinions with the weights to obtain an accident prediction result of the key nodes of the FPSO mooring system; and inputting the time-varying extreme weather condition data and the key node accident prediction result into a dynamic Bayesian network model to obtain an accident early warning result of the FPSO mooring system. Accident occurrence probability calculation and accident early warning of the whole mooring system, subsystems and equipment units under the extreme weather condition are achieved, and data support is provided for field emergency protection.

The invention relates to the technical field of intelligent traffic management, in particular to a 5S-based road congestion evaluation method, which comprises the following steps of: determining multi-dimensional indexes from five aspects of fluid property, structural property, spatiality, scenario property and social property elements, collecting the corresponding multi-dimensional indexes, and preprocessing; a fuzzy comprehensive evaluation model is constructed by using the combination of an analytic hierarchy process and fuzzy mathematics, the evaluation precision is improved through weight distribution and a membership function, contrastive analysis is performed in combination with examples, and finally, according to real-time traffic data, each index weight is dynamically adjusted, and the model adaptability of the fuzzy comprehensive evaluation model is improved. The dynamic evaluation method suitable for the complex scene supports real-time data input and multi-road parallel calculation, and the problem that a traditional evaluation method mainly depends on a single index is solved.

The invention provides an intelligent linkage control method for a flood discharge gate of an avionics hub, and the method comprises the steps: collecting and preprocessing hydrological, meteorological and shipping multi-source data through a sensor, and eliminating data noise and scale difference. And constructing a multi-factor evaluation model by utilizing machine learning or fuzzy mathematics, and calculating a flood discharge risk and shipping influence evaluation value by taking the preprocessed data as input. A control strategy is made according to the evaluation value and a preset rule, the gates are grouped and sorted, and the opening sequence, height and time are determined through an intelligent linkage algorithm. In flood discharge, key parameters are monitored in real time, actual and expected targets are compared, control strategies and parameters are adjusted, and historical data are collected regularly to optimize a model and an algorithm. According to the method, the flood discharge efficiency and accuracy are improved, the operation safety is enhanced, the shipping demand is considered, and the system adaptability and stability are improved.

The invention discloses a pipe-jacking tunneling machine type selection evaluation system and method based on fuzzy mathematics. The method comprises the steps that firstly, a multi-dimensional key evaluation index system covering planning and design requirements, hydrogeological conditions, surrounding environment factors and cutterhead configuration characteristics is constructed; secondly, establishing each index membership function aiming at different jacking pipe types and cutterhead configuration combinations by applying a fuzzy mathematics theory, and generating a membership matrix of jacking pipe adaptive type selection; and thirdly, determining a comprehensive index weight by adopting a subjective and objective weighting method fusion strategy, and finally constructing a fuzzy comprehensive evaluation model based on the membership matrix and the comprehensive weight, thereby realizing the adaptability quantitative evaluation of the pipe-jacking tunneling machines with different types and cutterheads. According to the method, the defect that traditional model selection depends on subjective experience is overcome, quantitative evaluation of pipe-jacking model selection under the complex stratum condition is achieved, the model selection accuracy and efficiency are improved, a reliable solution is provided for scientific model selection of the pipe-jacking tunneling machine, and the method has outstanding practicability and wide application prospects.

This invention discloses an optimization method for a glycerol refining process, comprising the following steps: Based on the adopted glycerol refining process, determining the control factors, and conducting single-factor experiments with each control factor as a variable to obtain the optimized first control factor. The control factor is selected from at least one of the following: the ratio of silica gel to zeolite powder, the amount of decolorizing agent added, and the decolorization temperature; then conducting an orthogonal experimental design; setting an evaluation subset and a comment set; setting a weight set; determining a fuzzy relation comprehensive evaluation set; establishing and analyzing a quadratic response surface regression model; using software to analyze the fitted equation to obtain the optimal process parameters for glycerol refining, and using a fuzzy mathematical sensory evaluation model to verify and determine the optimal process parameters for glycerol refining. This invention uses fuzzy mathematical evaluation combined with response surface methodology to examine the effects of the ratio of silica gel to zeolite powder, the amount of decolorizing agent added, and the decolorization temperature on the glycerol content, thus obtaining the optimal refining process.

The application relates to the technical field of drilling exploration, and discloses a method, device, equipment and medium for predicting the broken degree of the well wall surrounding rock of a to-be-drilled formation based on well-seismic fusion, which comprises the following steps: obtaining the single-channel seismic attribute data of a drilled well, the hole enlargement rate, the logging data and the seismic attribute data of an un-drilled formation; performing correlation analysis based on the single-channel seismic attribute data and the hole enlargement rate to obtain target seismic attribute data; performing multi-attribute fusion based on the target seismic attribute data and a hierarchical analysis fuzzy mathematics method to obtain a formation broken seismic attribute index; obtaining an evaluation index of the broken degree of the well wall surrounding rock of the formation based on the formation broken seismic attribute index, the logging data and an evaluation index formula of the broken degree of the well wall surrounding rock of the formation; and obtaining the broken degree of the well wall surrounding rock of the un-drilled formation based on the evaluation index and the seismic attribute data of the un-drilled formation. The broken degree of the well wall surrounding rock of the un-drilled formation is effectively predicted.