10 results about "Projection pursuit" patented technology

The invention discloses a regional water environment bearing capacity change evaluation and prediction method and system, and the method comprises the steps: obtaining water resource data, water environment data and social economic data in a target region, and constructing a water environment bearing capacity index system; the index system comprises a plurality of subsystems; evaluating the subsystems through a projection pursuit model based on a sparrow algorithm to obtain subsystem evaluation results; obtaining a comprehensive evaluation result of the water environment bearing capacity through an entropy weight approximation ideal solution sorting algorithm according to the subsystem evaluation result; constructing a Markov transition probability matrix according to the comprehensive evaluation result; and predicting the change probability of the water environment bearing capacity according to the Markov transition probability matrix. The method can improve the evaluation and prediction accuracy of the water environment bearing capacity change, and can be widely applied to the technical field of water environment evaluation and prediction.

The invention discloses a water conservancy project service performance improvement effect evaluation method, device and equipment, relates to the technical field of water conservancy projects, and is beneficial to determining water conservancy project service performance improvement effect evaluation so as to determine the effectiveness of project reinforcement and maintenance measures. Comprising the steps of constructing an evaluation index of a water conservancy project service performance improvement effect; determining importance values of the evaluation indexes based on a projection pursuit method optimized by a genetic algorithm; and evaluating the service performance improvement effect of the water conservancy project according to the importance value and a multi-dimensional normal cloud model.

The invention relates to the technical field of emergency plugging of a embankment breach, discloses an optimization method of a embankment breach row pile plugging scheme, and aims to solve the problem of poor accuracy of an existing method. The scheme mainly comprises the following steps: judging a plugging difficulty level according to multi-dimensional parameters and a projection pursuit method based on a genetic algorithm; constructing a two-dimensional shallow water equation, and calculating breach water flow parameters through high-precision water flow simulation in the solving process; determining a dragging force coefficient and an inertia force coefficient through a least square method, and calculating the water flow impact force of the plugging structure of the embankment breach per unit length based on a Morison equation method; calculating an undrained shear strength standard value and a strain value when the maximum principal stress difference is half, and determining the ultimate bearing capacity of the row pile plugging structure based on the improved p-y curve; judging the bearing state of the row piles, optimizing the diameter and the pile distance of the steel pipe piles according to the bearing state of the row piles, and determining the pile point coordinates of the steel pipe piles. The accuracy of the row pile plugging scheme is improved.

The application discloses a seasonal river pollution control engineering effect evaluation and environmental protection technology popularization service system and relates to the technical field of environmental monitoring; the system comprises the following modules: a matter-element extension evaluation module, which determines the comprehensive evaluation grade of the pollution control engineering according to a matter-element correlation matrix; a projection pursuit weak link identification module, which generates an improvement priority sequence by sorting the projection values of each weak link index along the optimal projection direction vector from large to small; and a multi-objective optimization popularization module, which is used for setting candidate environmental protection technologies for each weak link index according to the improvement priority sequence and screening a final environmental protection technology popularization service scheme from a Pareto optimal solution set. The application realizes a complete decision link from quantitative evaluation to accurate positioning of weak links and then to multi-objective balanced optimization of a popularized technology scheme, and overcomes the limitation of traditional methods that can only output a comprehensive evaluation grade and cannot identify specific shortcomings and improvement priorities.

A method for evaluating the wear state of a transmission case, belonging to the technical field of wear state evaluation, includes the following steps: Step S01, collect wear particle data in the transmission case oil; Step S02, establish evaluation indexes for the wear particle data in Step S01; Step S03, use the improved parrot optimization algorithm IPO to optimize the penalty function in the projection pursuit model PPC to obtain the best objective function; Step S04, use the best objective function and evaluation indexes to construct a wear state evaluation model IPO-PPC, etc. The present invention improves the parrot optimization algorithm, so that its convergence speed and accuracy are greatly improved. The improved parrot optimization algorithm is used to optimize the penalty function in the projection pursuit method, establish a wear state evaluation model, and combine six evaluation indexes of oil abrasive particle data to realize the rapid and accurate identification of the wear state of the transmission case.

The invention provides a water quality comprehensive evaluation method based on a projection pursuit theory, and belongs to the technical field of water quality evaluation. The method comprises the following steps: firstly, preprocessing original water quality data by adopting a range standardization method, and eliminating index dimension differences; secondly, constructing a projection index function based on an information entropy theory, and effectively representing nonlinear correlation characteristics among water quality parameters; and finally, designing a particle swarm optimization algorithm with a dynamic adjustment mechanism, and remarkably improving the convergence speed and optimization precision of the model through an inertia weight linear decline strategy and a learning factor self-adaptive updating mechanism. According to the method, the multi-dimensional water quality indexes are creatively projected to the low-dimensional feature space, and the projection direction is optimized by introducing the improved particle swarm optimization of the dynamic inertia weight and the self-adaptive learning factor, so that the comprehensive water quality evaluation method with strong generalization ability is constructed; the water quality comprehensive evaluation method shows excellent engineering applicability in arid region drainage basin water quality monitoring and evaluation, provides intelligent technical support for water environment management decision, and has good practicability.

The invention discloses an industrial talent big data analysis method based on retrieval enhancement generation, and relates to the field of talent data processing, and the method comprises the steps: building an industrial talent information graph based on industrial talent data and in combination with a retrieval enhancement generation technology, and enabling the industrial talent information graph to be used for quantifying talent flow data and cooperation density data; according to the industrial talent intelligence map and the constructed nonlinear diffusion equation, the influence of talent loss and cooperative interruption on the employer is quantified; evaluating the centrality of talent nodes in the industrial talent intelligence graph by using an evaluation algorithm; on the basis of a multi-objective optimization framework, an optimal talent management strategy is searched in combination with an influence quantification result of talent loss and cooperative interruption on an employer and a talent node centrality evaluation result; and predicting the effectiveness and potential risk of the optimal talent management strategy by using a projection tracking forest algorithm and influence factor data. By analyzing industrial talent data, scientific and effective talent management strategy suggestions are provided.

The invention discloses a carbon lock evaluation method based on multi-source data projection pursuit and frequent item set identification. The method comprises the following steps: S1, constructing a household energy consumption factor database comprising a plurality of dimensions; s2, performing nonlinear dimension reduction processing on the data by using a projection pursuit model, and optimizing a projection direction in combination with a real number coding acceleration genetic algorithm; s3, based on the factor vector after dimension reduction, extracting a frequent item set, setting support degree and credibility thresholds, and identifying a carbon locking behavior path; and S4, in combination with a DNAS behavior mechanism theory, identifying a causal path and mechanism of carbon locking. The method can integrate multi-source data, has nonlinear dimension reduction and efficient factor extraction capabilities, and realizes accurate and effective evaluation of carbon locking.

The invention discloses a reserve industrial land development time sequence decision-making method and system considering a space perspective, and the method comprises the steps: S1, constructing a development potential index system, and obtaining the data of a research city reserve industrial land; s2, constructing a particle swarm optimization projection pursuit model, wherein the particle swarm optimization projection pursuit model uses all normalized index data as high-dimensional data, uses a particle swarm algorithm to iteratively adjust particle positions and finally projects the particle positions into one-dimensional data; and S3, constructing an SOFM neural network, carrying out spatial clustering on the development potentials of all spatial positions in the research city to obtain N spaces, and sorting the N spaces in sequence according to the development potentials to serve as a time sequence decision result. According to the method, the particle swarm optimization projection pursuit model projects high-dimensional data of a multi-dimensional index into one-dimensional data to represent the development potential of each spatial position, and the SOFM neural network adopts a combination of a spatial domain and an attribute domain to carry out mixed distance clustering processing, so that development potential evaluation and development time sequence decision technical support is provided for reserve industrial land.

The invention belongs to the field of electric power, and discloses a power distribution network bearing capacity index weight determination method and device, and the method comprises the steps: obtaining index data corresponding to each index for evaluating the bearing capacity of a power distribution network; calculating an objective weight vector corresponding to each index based on a grey correlation analysis method, and calculating a subjective weight vector corresponding to each index based on an analytic hierarchy process; synthesizing and calculating the objective weight vector and the subjective weight vector into a basic combination weight corresponding to each index according to a multiplication synthesis method, and substituting the basic combination weight vector into a projection pursuit algorithm; solving according to a genetic algorithm, and generating a target weight corresponding to each index according to a solving result; wherein the genetic algorithm takes the basic combination weight as an initial guiding direction, and an objective function is a projection value function for maximizing the basic combination weight.