184 results about "Control factor" patented technology

The invention relates to a reservoir porosity and permeability prediction method based on a dynamic committee integration model, and the method comprises the following steps: obtaining an original data set which comprises shale content, porosity, permeability, GR, AC, CNL, DEN, RT, RXO, SP, CALC, CALI, depth and lithologic labels; performing data enhancement on the original data set; determining main control factors influencing the porosity and the permeability; constructing a dynamic committee integration model; inputting the main control factors into a dynamic committee integration model; and utilizing the trained dynamic committee integration model to respectively predict the porosity and the permeability. According to the method, the logging data is processed by adopting a machine learning method, reservoir parameters can be efficiently and accurately predicted, and favorable support can be provided for oil-gas exploration and development; the dynamic committee integrated model constructed by the invention can dynamically adjust the weight of each model according to different geological conditions and data features, can more flexibly adapt to the geological condition of a research area compared with a single model, and improves the prediction precision and generalization of the model.

The invention discloses a dynamic efficiency optimization management and control method for a wind-light hydrogen storage system, which comprises the following steps of: acquiring operating parameters of an electrolytic bath based on a water electrolysis hydrogen production simulation framework of an alkali liquor medium, and analyzing joint probability distribution and correlation coefficients of historical wind-light data through a wind-light photovoltaic synergistic effect model; constructing a system load accommodating setting model; when the frequency or voltage fluctuation of the power grid is detected, starting a quasi-synchronous electric element regulation and control framework PSEERA, and adjusting the output power through a droop control equation; the comprehensive performance indexes are optimized by adopting a Ling-tuned chaos infinitesimal search (SACMESA) algorithm, and main control factors are extracted through a multi-element optimization evolution (BKEAMOEA) algorithm analyzed according to key elements to carry out multi-objective optimization; implementing a scattered point type cooperative control strategy including bottom-layer equipment control, middle-layer energy management and upper-layer system scheduling, and realizing cross-level dynamic optimization; the peak regulation and frequency modulation capability, the safety and the stability of the power grid are remarkably improved.

The invention discloses a shale gas well dessert prediction method and device based on integrated learning. The method comprises the steps of obtaining main control factors and feature data of a shale gas well to be predicted, and inputting the main control factors and the feature data into a trained dessert prediction model to obtain dessert prediction data; the model training process comprises the following steps: determining main control factors influencing the dessert according to the correlation between each parameter in the prediction data of the sampled shale gas well in the target area and the dessert; the prediction data comprises first data and second data, the first data comprises geological data, perforation data and oil and gas production data, and the second data comprises logging data and fracturing construction data; performing feature extraction on each parameter in the second data to obtain feature data; constructing a training data set according to the main control factors and the characteristic data of the shale gas well; and training the dessert prediction model based on the training data set. The accuracy of a prediction result can be improved, and fracturing design is effectively guided.

The invention discloses a warehouse capacity control method and device, equipment, a storage medium and a computer program product, and relates to the technical field of warehouse management, and the method comprises the steps: monitoring the warehouse capacity use condition; when the warehouse capacity use condition reaches the capacity expansion and contraction control condition, automatic capacity expansion and contraction of the warehouse are carried out according to a pre-designed warehouse automatic capacity expansion and contraction algorithm, and the warehouse automatic capacity expansion and contraction algorithm is determined based on warehouse capacity control factors. The capacity of the warehouse is expanded and shrunk through the automatic capacity expansion and shrinkage algorithm of the warehouse, the capacity management step of the warehouse can be simplified, and the management efficiency is improved.

The invention relates to the technical field of welding, and particularly discloses an anti-fatigue welding process for a long-distance pipeline supporting steel structure. The process comprises the steps that a font groove structure is determined, and pre-welding polishing pretreatment and layered welding are conducted; fatigue samples of weld toe areas with different arc radiuses are collected, crack feature coordinates and stress concentration coefficients are extracted, failure modes are divided based on clustering, the arc radiuses are verified as main control factors of fatigue failure through multiple linear regression, and a core control range is determined by combining process capability indexes; carrying out fatigue verification on the basis of core parameter extension radius gradient, carrying out process compatibility matching in combination with a controllable interval and a thermal deformation interval of equipment, and outputting a radius candidate value through a response surface method; on-site construction constraints are collected, laboratory path space compatibility is analyzed, a formed track is optimized in a segmented mode, and constraint compensation factors are embedded. The anti-fatigue performance of the weld toe area of the supporting steel structure can be improved, and quality guarantee is provided for welding of the long-distance pipeline supporting steel structure.

The invention relates to an ultra-deep well perforation test combined operation tubular column safety evaluation method. The method comprises the following steps that S1, a packer lower portion perforation detonation annulus pressure evolution finite element model and a dynamic negative pressure evolution numerical model after perforation detonation are established; s2, establishing a perforation instant tubular column coupling impact vibration evolution model, and determining main control factors; s3, establishing a dynamic evolution numerical model of the shock absorber at the moment of perforation, and obtaining a dynamic evolution model of the lower oil pipe of the packer, the shock absorber and the perforating gun at the moment of perforation; and S4, evaluating the safety of the pipe column at the lower part of the packer by taking the Mises yield criterion as an evaluation standard. The influence of perforation detonation transient wellbore pressure and dynamic negative pressure on a lower tubular column system of the packer is fully considered, the dynamic response rule of the tubular column is disclosed through numerical simulation and theoretical analysis, risk control measures are put forward, and the safety of the packer is improved. Theoretical basis and technical support are provided for optimal design of an ultra-deep well perforation test combined operation scheme and safety of an oil testing process.

The invention discloses an anti-icing testing method, device and equipment for a super-hydrophobic surface structure of energy equipment and a storage medium, and relates to the technical field of super-hydrophobic surface testing. Designing a super-hydrophobic surface structure based on the environmental main control factor to obtain a structure parameter set; simulating the super-hydrophobic surface structure by using an environment load condition determined based on the environment working condition matrix and a structure parameter set to obtain an equipment critical vibration frequency, and determining a current surface structure morphology based on the structure parameter set and the equipment critical vibration frequency; and determining a morphology simulation error based on the current surface structure morphology and the actual surface structure morphology of the super-hydrophobic surface structure, and monitoring the super-hydrophobic surface structure based on the morphology simulation error, the structure parameter set, the equipment critical vibration frequency and the preset control mechanical excitation frequency to obtain the ice growth rate and the ice adhesion work. The efficiency of anti-icing testing of the super-hydrophobic surface structure is improved.

The invention relates to the technical field of railway earthquake safety, in particular to a rail-bridge system earthquake resistance evaluation method, a medium and equipment. The method comprises the following steps: establishing a finite element model of a track-bridge system; carrying out nonlinear time-history analysis on the track-bridge system under different working conditions; analyzing control factors of earthquake response of the track-bridge system; establishing a mapping relation between the seismic response of the track structure and the seismic response of the main beam; calculating the earthquake response of the main beam, and evaluating the earthquake displacement response of the track structure; and the anti-seismic evaluation of the track-bridge system is realized. Through the method, the method can be used for all high-speed railway bridge types and rails at present, the anti-seismic evaluation of the rail-bridge system based on the driving performance can be indirectly and quickly realized based on the mapping relation, a large amount of time-consuming and labor-consuming train-rail-bridge system finite element simulation calculation does not need to be carried out, and the calculation efficiency is improved. The efficiency is effectively improved, the cost is reduced, the calculation is simple and convenient, and the calculation result is accurate.

The invention provides a borehole trajectory anti-collision scanning method and device, electronic equipment and a storage medium, and belongs to the technical field of borehole detection.The method comprises the steps that first inclinometry data and first borehole trajectory calculation data of a reference well and second inclinometry data and second borehole trajectory calculation data of a comparison well are obtained; inputting the first inclinometry data, the second inclinometry data, the first borehole trajectory calculation data and the second borehole trajectory calculation data into an improved cuckoo algorithm by taking the nearest spatial distance between the trajectory points of the reference well and the comparison well as an objective function to obtain the trajectory point with the smallest spatial distance between the reference well and the comparison well; wherein the improved cuckoo algorithm comprises the following steps: on the basis of an original cuckoo algorithm, adjusting an inertia weight and a step size control factor based on the number of iterations, and dynamically adjusting a parasitic nest elimination probability based on a fitness variance of a population. The technical problems that time and labor are wasted and convergence is poor in the prior art are effectively solved.

The invention relates to the technical field of aluminum template optimization, and discloses an aluminum template parameter optimization method based on variable control. The method comprises the following steps: acquiring an initial parameter set and an optimization target parameter of an aluminum template assembly; executing a multi-stage control optimization process, the process including a plurality of control stages, each control stage processing only a portion of the parameters of the initial set of parameters while generating control factors for passing to the next control stage and feedback factors for optimizing the current control stage; and adjusting the initial parameter set based on data interaction of the control factor and the feedback factor so as to enable the initial parameter set to meet the optimized target parameter. According to the method, the parameters are processed stage by stage, mutual interference of multiple parameters is avoided, dynamic optimization is achieved by means of interaction of a control factor and a feedback factor, pertinence, controllability and efficiency of parameter optimization are improved, material waste and cost increase are reduced, the performance of the aluminum formwork is guaranteed, and the requirements of modern building engineering for the aluminum formwork are met.

The invention provides an adaptive cruise system adjusting method, a vehicle and a storage medium, the method is applied to the field of automatic driving, and the method comprises the following steps: determining a target control factor of an adaptive cruise system based on an attention parameter of a driver of the vehicle and an initial control factor of the adaptive cruise system of the vehicle, the target control factor is used for adjusting a control parameter of the adaptive cruise system, and the attention parameter is used for evaluating the concentration degree of the driver driving the vehicle; determining a target control parameter of the adaptive cruise system based on the target control factor and an initial control parameter of the adaptive cruise system; and driving control is conducted on the vehicle through the self-adaptive cruise control system according to the target control parameters. According to the method, the control factor of the self-adaptive cruise system can be dynamically adjusted according to the real-time state of the driver, and the vehicle is controlled in real time according to the control factor, so that the vehicle is controlled to run safely under the condition that the driver is in a distraction state, and the probability of accidents of the vehicle is reduced.

The invention discloses a natural gas hydrate productivity main control factor analysis method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining sample data of various variable factors of natural gas hydrate productivity, and carrying out the preprocessing of the sample data; constructing a preliminary causal structure between variable factors based on a physical mechanism, and performing direct causal relationship evaluation based on the preliminary causal structure and the preprocessed sample data to obtain a target causal graph; and performing causal inference analysis based on the target causal diagram to obtain main control factors of the natural gas hydrate productivity. According to the natural gas hydrate productivity main control factor analysis method based on causal inference, the causal relationship of productivity influence is accurately identified, the scientificity and reliability of main control factor screening are improved based on the causal relationship, and more powerful technical support is provided for natural gas hydrate development. The method can be widely applied to the technical field of data processing.

The invention relates to the technical field of digital control, in particular to an automatic control system and method for producing lithium carbonate. The method comprises the following steps: acquiring sensing data of a lithium carbonate production line, and binding the sensing data to obtain a process section field state factor set; performing fine-tuning embedding time state transition according to the process section field state factor set to obtain a multi-dimensional control characterization flow; performing control instruction coding based on the multi-dimensional control representation flow to obtain a multi-channel control factor set; carrying out field load parameter re-calculation and micro-cycle feedback modulation by combining the obtained real-time lithium carbonate production line sensing data to obtain a control modulation response matrix; based on the control modulation response matrix, reverse adjustment is carried out on the process diagram structure, and a process anomaly feedback body is obtained; the real-time response capability of the lithium carbonate production line to raw liquid fluctuation, equipment state change and working condition abnormity is enhanced, and the product purity, the yield and the production line operation stability are effectively improved.

The invention belongs to the technical field of data processing, particularly relates to a fault processing method and system for an anti-icing simulation system, and aims to solve the problems that the early warning accuracy is not high and processing instructions are easy to mismatch in the prior art. The method provided by the invention comprises the following steps: acquiring multi-source simulation data of an anti-icing simulation system; determining a temperature drop rate and a humidity change rate according to the environment simulation data, and determining a dynamic regulation and control factor in combination with the system characteristic data; valve time sequence data of the anti-icing simulation system are obtained, the valve time sequence data and the dynamic regulation and control factors are input into a pre-trained time sequence prediction model for fault prediction, and a fault prediction probability is obtained; taking the fault prediction probability as a query vector, retrieving a plan node in a pre-constructed knowledge graph, and generating a predictive instruction; and when the fault prediction probability reaches a preset threshold value, executing the predictive instruction. Based on the method, the early warning accuracy and the instruction adaptability in the fault processing stage are effectively improved.

The invention provides a magnet power supply control system, and relates to the technical field of data processing, and the system is used for obtaining a parameter setting instruction input by a control terminal, determining control input parameters of each time point according to a set current value and an actual voltage value, constructing a second data matrix according to a historical operation sequence index value, the first data matrix and the second data matrix are superposed to obtain a fusion data tensor, gradient features are extracted according to the fusion data tensor, response fitting degrees between the gradient features and all control paths are calculated, a mode fitting index set is obtained, the maximum response fitting degree is extracted, the state conversion direction is determined, and a state conversion index is obtained; and calling a control parameter mapping path, mapping the logic condition of the physical circuit change into a digital control sequence to obtain a control factor matrix, generating an execution instruction, and sending the execution instruction to a power output execution layer. Hardware control can be replaced by data driving, and stable operation of the magnet power supply is ensured.

The invention discloses an intelligent bonding silver wire equipment control method and system based on the Internet of Things, and relates to the technical field of equipment control. An intelligent bonding silver wire equipment control system based on the Internet of Things comprises an equipment data acquisition module, an equipment abnormity judgment module and an equipment linkage control module. According to the method, the bonding external environment data, the bonding production process data and the bonding equipment state data are collected in real time, and the silver wire surface data are combined, so that the precise control on the bonding silver wire equipment can be realized, the production parameters can be optimized, and the bonding quality can be improved; in combination with dynamic equipment control analysis and dynamic silver wire state analysis, an environment control factor, a production process control factor, an equipment state control factor and a silver wire bonding process influence factor can be adjusted in real time, so that equipment can adapt to different production conditions, and the production flexibility is improved.

The invention discloses an intelligent ship power control system which comprises a data collection module, a power control strategy adjustment trigger module, a ship navigation state recognition model construction module, a ship power strategy generation module and a power intelligent control module. The invention relates to the technical field of ship power control, in particular to an intelligent ship power control system, which innovatively introduces a power control strategy adjustment triggering method of a dual judgment logic mechanism, and effectively realizes intelligent updating of a ship power control strategy. The stability of an identification result is improved through identification model construction of a dynamic hyperbox expansion mechanism of overlapping risk avoidance and a membership function construction method of boundary dynamic regulation and control; a multi-stage strategy generation method is designed, an improved optimization algorithm which introduces a population search direction control factor and a self-adaptive reverse guidance mechanism is adopted, the global optimization ability of the control strategy is improved, and fine control over the ship power strategy in the complex navigation environment is achieved.

The invention provides a main control factor analysis method and system influencing oil and gas reservoir single well yield and a medium, and relates to the technical field of oil yield prediction, and the method specifically comprises the steps: collecting the oil reservoir single well yield and influence factors; processing the yield and each influence factor, calculating a Pearson's correlation coefficient, and determining a main control factor; according to the yield of the ith single well and the initial value of the yield of the ith single well, the sensitivity coefficient of the bth main control factor of the m single wells is obtained; and combining the Pearson's correlation coefficient with the sensitivity coefficient to generate a comprehensive evaluation coefficient, and evaluating the influence of each main control factor on the single well yield. According to the method, the influence degree of each factor on the yield can be quantified, the main control factor of the oil and gas reservoir single well yield can be determined, the comprehensive influence of each main control factor on the single well yield can be comprehensively reflected through the comprehensive evaluation coefficient, related factors can be identified, and the factor is prevented from generating significant influence on the yield under specific conditions.

The invention discloses an acceleration and deceleration control method for a servo motor of a press machine, and relates to the technical field of servo motor control, and the method comprises the following steps: obtaining a historical acceleration and deceleration control scheme of the servo motor of the press machine in a historical work period; performing corresponding correlation coefficient analysis on the influence factors after the implementation of the sub-control factor set in the historical pressure acceleration and deceleration control scheme and the control factor set for each historical acceleration and deceleration control scheme to obtain a preprocessing coefficient set; acquiring a current acceleration and deceleration control scheme implemented by the press machine in the current working period, and counting correlation coefficients among influence factors generated by the current acceleration and deceleration control scheme according to the preprocessing coefficient set to obtain a target preprocessing coefficient set; the effect is that the acceleration and deceleration control of the servo motor is more adaptive to the production requirements of the press.

This application provides a control method for an energy storage system, comprising: determining the state parameters corresponding to each individual battery cell; determining a multi-dimensional control factor corresponding to each individual battery cell based on different state dimensions indicated by the state parameters at preset calculation cycles; sorting multiple individual batteries cells according to the charge / discharge state of the energy storage system and the multi-dimensional control factor; determining the output demand voltage corresponding to the energy storage system based on the peak reference voltage and AC frequency corresponding to the energy storage system; and controlling the access state of each individual battery cell in the next AC cycle by applying the nearest level approximation method based on the sorting result, the output demand voltage, and the maximum supply voltage corresponding to each individual battery cell in the next AC cycle. This application controls the energy storage units connected to the charge / discharge circuit of the energy storage system and their access time through multi-dimensional control factors calculated from multiple dimensions, thereby achieving full utilization of the energy of the energy storage units.

The application discloses a control method and a cooling water tower based on a dry-wet dual-purpose closed cooling water tower, relates to the technical field of energy-saving refrigeration, and comprises the following steps: calling a pre-established heat exchange digital model; acquiring real-time operation data, extracting different control factors of each working condition area according to the characteristics of each working condition area; calling a scaling and corrosion evolution model and a switching mechanism loss model, correcting the static heat exchange model on line according to the real-time operation data and a historical 72h load curve to obtain a dynamic heat exchange model; performing multi-dimensional coupling analysis based on the real-time operation data and the different control factors, inputting the coupling analysis results into a pre-trained operation mode decision model to obtain a dynamic operation mode decision result of the cooling water tower; and generating an operation parameter adjustment strategy of each working condition area and each stage according to the dynamic operation mode decision result. The application improves the performance of the cooling water tower in terms of full-season adaptability, heat exchange efficiency and energy saving.

This invention relates to the field of computer peripheral control, and more particularly to a method and system for monitoring and controlling the status of computer peripherals. The method includes the following steps: acquiring an internal load sequence and an external current sequence; calculating a first-order difference term using a sliding window; accumulating and weighting the products of the first-order difference term, the external current sequence, and a preset reference voltage to obtain a transient power supply deficit gradient; acquiring a retransmission count sequence; and weighting and accumulating the cross product of the transient power supply deficit gradient and the retransmission count sequence, along with their first-order moment statistical characteristics, to obtain a latent current outage risk index; acquiring service priority weights; and mapping the latent current outage risk index to the service priority weights to obtain a stability degradation diagnostic signal; and calculating a frequency reduction control factor and adjusting the operating state when the stability degradation diagnostic signal exceeds a preset threshold. This invention effectively identifies latent current outage faults, achieving accurate diagnosis and adaptive control.

The invention provides a gas well productivity and EUR optimization method in the middle and later periods of dense low-permeability gas reservoir development, and relates to the technical field of gas reservoir engineering, and the method comprises the steps: collecting historical dynamic and static data of a dense low-permeability gas reservoir, and constructing index system data; based on the index system data, static and dynamic main control factor analysis influencing open flow capacity and recoverable reserves is carried out, and a main control factor set is obtained; according to the main control factor set, using a machine learning algorithm to construct a prediction model used for predicting open flow capacity and recoverable reserves; taking open flow capacity or recoverable reserve maximization as a target, and constructing a control optimization model for optimizing production control variables; and for the target well, using the prediction model to predict open flow capacity and recoverable reserves, and using the control optimization model to optimize production control variables. Compared with a traditional productivity analysis method, the method has the advantages that subjective factor interference is effectively reduced, the analysis process is more objective and efficient, and productivity and EUR evaluation under the interaction of different factors is achieved at the same time.

The invention discloses a flow control method for intelligent voice outbound, and the method comprises the steps: introducing a statistical classification algorithm in the aspect of an outbound flow control algorithm, taking various outbound flow control factors as events, and calculating the probability that the outbound flow reaches a certain level under a certain condition; flow upper limit calculation and flow adjustment dynamic decision are introduced for flow control of intelligent voice outbound; and an outbound traffic controller based on an outbound traffic control algorithm is introduced to complete a full-intelligent outbound system. According to the method, accurate prediction and intelligent adjustment of the flow of the intelligent outbound system are realized, dynamic balance between the outbound task flow and available resources of the outbound voice platform is realized, the resource utilization rate of the outbound voice platform is maximized, and the capacity of the intelligent outbound system is further released, the cost is reduced and the efficiency is improved on the premise that the outbound resources are kept unchanged.

This invention relates to an optimized control method for total nitrogen removal and anaerobic ammonia-oxidizing bacteria enrichment in constructed wetlands, comprising: S1, selecting control factors for the constructed wetland, forming an experimental system using a central coincidence design method, introducing wastewater to be treated into the constructed wetland, monitoring the operation of the constructed wetland, and collecting data on total nitrogen removal and relative abundance of bacteria; S2, using analysis of variance to determine a suitable model method for data fitting, and then constructing prediction models for total nitrogen removal efficiency and relative abundance of anaerobic ammonia-oxidizing bacteria based on the model method; S3, predicting the total nitrogen removal efficiency and relative abundance of anaerobic ammonia-oxidizing bacteria in the constructed wetland, thereby achieving optimized control of the operation and maintenance management of the constructed wetland. The optimized control method provided by this invention can predict the relative abundance of anaerobic ammonia-oxidizing bacteria and the total nitrogen removal efficiency of constructed wetlands, guiding the operation and maintenance management of constructed wetlands.

The invention relates to the technical field of engineering data processing, in particular to a fusion processing method, system and device for multi-source heterogeneous engineering data and a storage medium. The method comprises the steps of obtaining original engineering data, and performing structural unit division on an engineering project; performing basic feature extraction on the structural unit, and generating cost information energy of the structural unit; semantic perturbation is introduced to update the cost information energy of the structural unit to obtain perturbed structural energy; based on the disturbed structural energy, a multi-channel control flow feedback mechanism is introduced to obtain a control factor of the structural unit, and further, the disturbed structural energy is combined to obtain cost information energy of the structural unit after fusion processing; and introducing a structural information entropy feedback mechanism, and integrating the cost information energy after fusion processing of the structural units to obtain the total cost. The problems that in the prior art, efficient fusion processing of multi-source heterogeneous engineering data is difficult, feature expression is not uniform, and calculation efficiency is low are solved.

The invention discloses a method for evaluating compressibility of a deep ultra-low permeability rock reservoir, which comprises the following steps of: analyzing a relationship between a main control factor of the compressibility of the reservoir and the fracturing difficulty of the reservoir, and determining a relational expression for representing the influence degree of the main control factor on the compressibility of the reservoir; quantitatively representing the influence degree of the main control factors on the reservoir compressibility based on the relational expression of the influence degree of each main control factor on the reservoir compressibility; and based on the influence degrees of different main control factors, evaluating the reservoir compressibility by adopting an analytic hierarchy process. According to the method disclosed by the invention, more accurate reservoir compressibility evaluation is realized by quantitatively representing the influence degree of the elastic modulus, the Poisson's ratio, the fracture toughness, the crustal stress and the natural fracture on the reservoir compressibility.

The present invention discloses an intelligent ship power control system, comprising a data collection module, a power control strategy adjustment trigger module, a ship navigation status identification model construction module, a ship power strategy generation module, and a power intelligent control module. The present invention relates to the field of ship power control technology, and specifically refers to an intelligent ship power control system. This solution innovatively introduces a power control strategy adjustment trigger method with a dual judgment logic mechanism, effectively realizing the intelligent update of the ship power control strategy; combines the dynamic hyperbox expansion mechanism for overlapping risk avoidance with the membership function construction method for boundary dynamic regulation to construct an identification model, thereby improving the stability of the identification result; designs a multi-stage strategy generation method, and adopts an improved optimization algorithm that introduces a population search direction control factor and an adaptive reverse guidance mechanism to enhance the global optimization capability of the control strategy, thereby realizing refined control of the ship power strategy in a complex navigation environment.

The application discloses an irrigation oasis regulation and control potential power and targeted intervention strategy generation method and system, the method comprises the following steps: dividing a target irrigation oasis region into a plurality of management units, obtaining multi-source data of all the management units, and calculating the coupling coordination degree of each management unit; taking the management unit with a coupling coordination degree less than the regulation lower limit as a regulation unit, and taking the difference between the coupling coordination degree of the regulation unit and the regulation lower limit or the regulation upper limit as the regulation potential; constructing and training a Bayesian causal network, and according to the coupling coordination degree and the index of the regulation unit, using the probability output by the trained Bayesian causal network, calculating the mutual information or belief variance of each driving node of the regulation unit to the target node; taking the driving node with the highest mutual information or belief variance as the main control factor of the corresponding regulation unit, and searching for the targeted intervention strategy of the regulation unit in the factor-strategy knowledge base by using the main control factor.

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.