74 results about "Global sensitivity analysis" patented technology

The invention discloses a method for estimating the yield of winter wheat by assimilating the characteristics of a leaf area index time-sequence curve. The method is implemented through the following steps: S1, performing global sensitivity analysis on a crop model and completing parameter regionalization of the crop model; S2, synthesizing the MODIS LAI (moderate resolution imaging spectroradiometer leaf area index) time-sequence curve; S3, performing filtering processing on the LAI time-sequence curve; S4, performing curve fitting and extracting key characteristic points; S5, operating the crop model in area coverage, performing curve fitting on the LAI time-sequence curve obtained by simulation and extracting the key characteristic points on the curve; and S6, establishing a cost function according to dates of three key characteristic points which are respectively obtained in S4 and S5, taking remote sensing observation error as weight for summating and further getting a total cost function, minimizing the total cost function to rapidly converge the cost function, and finally gathering according to an administrative boundary when convergence conditions are met and outputting a yield result. According to the method disclosed by the invention, the assimilation precision is improved, the affects caused by the situation that an MODIS LAI product system is lower are overcome and the method is further suitable for estimating the yield of the winter wheat at regional scale.

The invention provides a PCE (polynomial chaos expanse) based global sensitivity analysis method for time-variation reliability. The method comprises steps as follows: step one, performance PCE at each discrete moment of a product degradation process is calculated on the basis of a failure mechanism reliability and performance integrated module; step two, reliability PCE at each discrete moment of the product degradation process is calculated on the basis of an orthogonal experimental design scheme; step three, time-variation reliability PCE of the product degradation process is calculated according to the principle of moving least square; step four, coefficients of the time-variation reliability PCE are decomposed and recombined according to Sobol', and a global sensitivity Sobol' index is calculated. The method can be used for efficiently solving the problem about global sensitivity analysis for the reliability of a complex engineering model in a degradation process and has the characteristics of higher precision, wide application range and the like.

The invention provides an analysis method for influence factors of carbon dioxide concentration prediction at any time-space position. The method comprises the following steps of: on the basis of sparse and non-uniform satellite carbon dioxide column concentration observation data, corresponding environmental factors including a ground cover factor, a climate and weather factor and a combustion emission factor, and an XGBoost algorithm, constructing a model for simulating spatial and temporal distribution of carbon dioxide in a region, and extracting carbon dioxide temporal and spatial distribution trend variables; and realizing quantitative evaluation of environmental factor sensitivity by utilizing the constructed regional carbon dioxide spatial and temporal distribution model and a global sensitivity analysis algorithm, and quantitatively determining influence degrees and magnitudes of various environmental factors influencing regional carbon dioxide spatial and temporal distribution according to a sensitivity analysis result. Compared with a traditional method, the method can simulate regional carbon dioxide concentration distribution with high precision, and achieve quantitative evaluation of the importance degrees of the environmental variables.

The invention discloses a dynamic control method for a tunnel construction progress based on a global comprehensive sensitivity analysis. The dynamic control method comprises the steps of determining a sensitivity analysis input parameter based on a tunnel construction simulating model, and preprocessing the parameter; performing a multi-factor sensitivity analysis of a tunnel construction period; performing a global sensitivity analysis of the tunnel construction period; performing engineering language transformation on a sensitivity analysis result; and performing real-time dynamic monitoring and controlling on the tunnel construction period. The dynamic control method has functions of realizing dynamic control for the tunnel construction progress, finding unreasonable construction configurations and construction solutions, dynamically adjusting the construction solutions, improving engineering construction precision, performing sensitivity analysis and dynamic control on all parameters which may cause tunnel construction period change, realizing comprehensive understanding for the construction period influence by construction parameters and work procedure duration time, further acquiring more critical parameter in a parameter assembly, and effectively ensuring checking for a construction machinery configuration solution.

The invention relates to a field line coupling uncertainty quantification and global sensitivity calculation method. An adaptive hyperbolic truncation scheme is combined with a minimum angle regression method to carry out sparse processing on a generalized chaotic polynomial, an agent model is established to analyze the uncertainty problem of the radiation sensitivity of a multi-conductor transmission line, and the global sensitivity of an input variable is analyzed by a global sensitivity analysis method. According to the scheme, on the premise that the calculation precision is guaranteed, related statistical characteristic parameters and the like in the uncertainty problem of the radiation sensitivity of the multi-conductor transmission line can be rapidly and accurately calculated, andthe scheme is effective when the total sensitivity index and the first-order sensitivity index of the radiation sensitivity of the multi-conductor transmission line are calculated.

A method of identifying most influential design variables in a multi-objective engineering design optimization of a product is disclosed. According to one aspect of the present invention, a product is optimized with a set of design variables and a set of response functions as objectives and constraints. Representative product design alternatives (samples) are chosen from the design space and evaluated for responses. Metamodels are then used for fitting the sample responses to facilitate a global sensitivity analysis of all design variables versus the response functions. A graphical presentation tool is configured for allowing the user to conduct 'what-if' scenarios by interactively applying respective weight factors to response functions to facilitate identification of most influential design variables. Engineering design optimization is then conducted in a reduced design space defined by the most influential design variables.

The invention discloses a fatigue performance prediction method based on machine learning. The method comprises the steps: firstly collecting material data to form initial sample data, employing a Sobol global sensitivity analysis method to evaluate the contribution degree of each feature variable to an output variable variance, carrying out the sorting of the importance of the feature variables,screening out key feature variables, and forming training sample data; dividing the training sample data into a training set, a verification set and a test set for training the model; performing modeltraining learning based on the training set and verification set data, obtaining corresponding model parameters, outputting a model trained based on existing training set / verification set learning, quantitatively evaluating model prediction performance by adopting a determination coefficient R2, completing establishment of the model, and performing fatigue performance prediction by utilizing thetrained model. According to the method, the nonlinear corresponding relation between the material information and the fatigue performance is established by utilizing the more comprehensive material information, and the method is applied to fatigue performance prediction of a higher-precision and generalized environment.

The invention discloses a method for estimating the yield of winter wheat by assimilating the characteristics of a leaf area index time-sequence curve. The method is implemented through the following steps: S1, performing global sensitivity analysis on a crop model and completing parameter regionalization of the crop model; S2, synthesizing the MODIS LAI (moderate resolution imaging spectroradiometer leaf area index) time-sequence curve; S3, performing filtering processing on the LAI time-sequence curve; S4, performing curve fitting and extracting key characteristic points; S5, operating the crop model in area coverage, performing curve fitting on the LAI time-sequence curve obtained by simulation and extracting the key characteristic points on the curve; and S6, establishing a cost function according to dates of three key characteristic points which are respectively obtained in S4 and S5, taking remote sensing observation error as weight for summating and further getting a total cost function, minimizing the total cost function to rapidly converge the cost function, and finally gathering according to an administrative boundary when convergence conditions are met and outputting a yield result. According to the method disclosed by the invention, the assimilation precision is improved, the affects caused by the situation that an MODIS LAI product system is lower are overcome and the method is further suitable for estimating the yield of the winter wheat at regional scale.

The invention relates to the field of power system data analysis methods, and provides a power distribution network reliability influence factor analysis method and system, and the method comprises the steps of constructing a Kriging model, obtaining a series of to-be-tested influence factors, and generating a series of prediction reliability indexes for the series of to-be-tested influence factors through the Kriging model; using a Sobol index method for carrying out global sensitivity analysis on a series of influence factors to be measured and a series of prediction reliability indexes corresponding to the series of influence factors to be measured, obtaining the sensitivity index of any influence factor and the sensitivity indexes of all the influence factors, the sensitivity indexes reflecting the importance degree of the influence factors to the reliability of the power distribution network. The invention overcomes the defect that an entropy weight method and a grey correlation analysis method cannot quantify the importance degree of the influence factors on the reliability of the power distribution network, and realizes the quantification of the importance degree of the influence factors on the reliability of the power distribution network.

The invention relates to a global sensitivity analysis method of a single-stage thermoelectric refrigeration system based on moment independence. For the global sensitivity analysis method, on the basis of considering a single-stage thermoelectric refrigeration system physical model under the influence of external heat transfer, a moment independent global sensitivity analysis model is established; an improved Monte Carlo simulation method is adopted to study independent torque sensitivity indexes of design variables for the refrigerating capacity and the refrigerating coefficient; and a single-stage thermoelectric refrigerating system is designed and improved according to a calculation result, so that the reliability of the system can be effectively improved, and important research significance and application value are achieved.