478 results about "Iterative method" patented technology

The invention relates to the technical field of solid state disks, and discloses a load collaborative scheduling method and system for a solid state disk, and the method comprises the steps: carrying out the data collection of a main controller of the solid state disk, and obtaining the original feature data; a Kolmogorov-Arnold neural network is input to carry out nonlinear feature transformation and linear combination operation, and a load prediction result is obtained; performing hierarchical processing to obtain a hierarchical scheduling model; constructing a multi-objective optimization function and carrying out constraint setting to obtain a constraint optimization equation set; performing convex difference function decomposition and augmented Lagrange function construction on the constraint optimization equation set, and solving through an alternating direction iteration method to obtain a scheduling decision scheme; according to the scheduling decision scheme, load balancing control is carried out on data write-in physical address allocation, data read cache scheduling and multi-channel parallel transmission, a real-time performance monitoring index is obtained, and the method realizes load collaborative scheduling of the solid state disk.

A park-factory-coordinative optimized scheduling method based on a Jacobi iteration method, which belongs to the technical field of energy scheduling optimization. A park-factory hierarchical game model is established, and by means of coordination and optimization between energy scheduling under a complex production constraint and production management and control that takes profit optimization as the goal, an optimal price regulating strategy and an optimal production scheduling strategy are obtained, such that a lower industrial park energy consumption and a higher factory production profit are achieved. A coordinative optimized scheduling model for a park control center and a factory management and control center is a multi-variable multi-constraint complex optimization issue; the solution of a high-order partial differential equation set involved in the model is calculated, and a cyclic iterative optimization algorithm is designed on the basis of a Jacobi iteration matrix, thereby greatly reducing the operation complexity; moreover, such a cyclic iterative algorithm requires a smaller storage capacity of a computer, and is thus suitable to be applied in practice by an engineer.

Lowest cost usage scheduling of an energy system during a time interval of interest is achieved by utilizing two components of learning and optimization. First, a number of learning approaches including Linear Least Square Regression (LLSR), Auto Regressive Integrated Moving Average (ARIMA), and Multi-Layer Perceptron Deep Learning (MLPDL) are used to forecast energy production and storage of the energy producing components of a given group of energy components as a function of historical production data and weather data collected from weather and geo reports. Then, an optimization problem is formulated to create the optimal schedule of energy usage during time intervals of interests for the given group of energy components subject to scheduling and equipment constraints. Two alternative solutions, namely Simplex Branch and Bound (SBB) and Interior Point Branch and Bound (IPBB) are presented to solve the optimization problem. Accordingly, integrated iterative methods, programs, and systems are described aiming at minimizing the cost of energy consumption for the given group of energy components within time intervals of interest.

Embodiments of the present application provide a bidirectional iterative method for a pre-trained model and downstream sequence tasks, a device, and a medium. In the embodiments of the present application, a novel soft-prompt-based fine-tuning training approach is provided, and each round of fine-tuning training comprises both a feedback link from historical downstream tasks to a pre-trained model and an adaption link from the pre-trained model to a current downstream task. For each current round, on the basis of the feedback link, the pre-trained model undergoes a first fine-tuning by using historical downstream tasks that have appeared prior to the current round, so as to enhance the capability of the pre-trained model; and on the basis of the adaption link, the already fine-tuned pre-trained model undergoes a second fine-tuning by using the current downstream task of the current round, so as to train a task model more adapted to the downstream task. Thus, the pre-trained model can be practically applied to downstream tasks, and improved model performance can be achieved especially in few-shot scenarios.

The invention belongs to the technical field of networked multi-axis motion control, and discloses a multi-axis cooperative control method, system and device based on digital-analog linkage, and the method comprises the steps: outputting a tracking error prediction value corresponding to a reference trajectory through an offline single-axis tracking error prediction model, and compensating the tracking error prediction value to the reference trajectory to obtain a new reference trajectory; the feedback controller generates a control signal according to the new single-axis reference trajectory and the actual trajectory, and the disturbance observer estimates external disturbance in real time based on the control signal and the actual trajectory and outputs a disturbance estimation result; according to the reference trajectory and the actual trajectory, estimating a contour error by using a Newton iteration method, inputting the contour error into a generalized cross coupling controller, and calculating to obtain a contour error compensation amount for each single axis; and combining the single-axis control signal, the disturbance estimation result and the contour error compensation amount to serve as control input of the mechanism model, and obtaining an actual track output by the mechanism model. According to the invention, high-precision contour tracking control of networked multi-axis equipment is realized.

An iterative method for monitoring a computing device characterized by metric data to be monitored, including, for each iteration, of collecting metric data over a predetermined interval of time, detecting a seasonality pattern of said metric data over said predetermined interval of time, determining an interval-specific model representing the detected seasonality pattern, calculating modelled data using said determined model and the collected metric data, comparing the calculated modelled data with the collected metric data to calculate a score characterizing the difference between the calculated modelled data and the collected metric data, calculating an anomaly likelihood for each data of the collected metric data using the calculated score, detecting an anomaly on a data when probability that the value of said data is an anomaly is greater than a predetermined threshold.

The invention provides a numerical simulation method and system based on rock mass fracture extension and seepage coupling, and belongs to the field of rock mechanics. Rock is regarded as a set composed of particles and mechanical contact between the particles, and a triangulation network is constructed based on the circle center of each particle; according to the geometrical characteristics of the triangulation network, a seepage pipeline network containing the interior and the periphery is built, and network nodes and boundary nodes are determined; calculating the permeability coefficient according to the particle positions on the two sides of the pipeline, and forming a penetrating seepage channel and fracture network by taking the pipeline which is not 0 and penetrates through and is connected with boundary nodes as a passage pipeline; and constructing a flow conservation equation set based on network nodes, solving pore pressure by using a Jacobian iteration method, calculating fracture pressure, and applying the fracture pressure to the model to realize coupling of a stress field and a seepage field. According to the method, the advantages of particle discrete elements in calculation of rock mass fracture extension and the advantages of a pipeline network method in calculation of fracture seepage are fully exerted, and accurate simulation of rock mass fracture initiation extension, seepage channel recognition and seepage field calculation is achieved.

The invention discloses a collaborative optimization method for a power system containing multiple virtual power plants based on a feasible region equivalent projection theory. The method comprises the following steps: establishing a main network operation model; modeling wind and light uncertainty by adopting an opportunity constraint optimization method and establishing a virtual power plant operation model; the chance constraint is converted into a deterministic constraint through quantiles; giving an objective function of virtual power plant-main network collaborative optimization, and establishing an integrated dispatching model of a power system containing multiple virtual power plants; eliminating internal variables of the virtual power plant in the target function by using an upper mirror graph theory; describing a multi-period power-cost feasible region projection of the virtual power plant at the common coupling point based on a feasible region equivalent projection theory and a vertex projection convex hull search method; and establishing a VPP-major network collaborative optimization model based on feasible region equivalent projection, and calling a GUROBI solver for solving in a Matlab2021a environment. According to the method, the virtual power plant-main network collaborative optimization model in multiple periods is solved in a non-iterative mode, the solving time is greatly shortened compared with a traditional iterative method, and the method has the same optimality as the traditional method.

The invention provides a large model parameter fine adjustment method and device, equipment, a medium and a product, and belongs to the technical field of artificial intelligence. The method comprises the steps that a data set of a target task is acquired, and a training set is obtained according to the data set; performing parameter fine tuning on the large model according to the training set, a preset fine tuning strategy and an optimization algorithm; wherein the fine tuning strategy comprises performing low-dimensional projection on the gradient of the large model based on a random subspace iteration method. According to the method, low-dimensional projection is carried out on the gradient of the large model through the random subspace iteration method, parameter updating is carried out in the low-dimensional projection space, and compared with a full-parameter fine adjustment method, the needed video memory is reduced, and the fine adjustment time is shortened.

The invention discloses a hydrogeological parameter space-time heterogeneity geostatistics inversion method. The method comprises the following steps: constructing a to-be-solved hydrogeological parameter column vector based on a geologic model and a'space-time equivalence 'principle; a priori covariance matrix of partition parameters in a time domain is assembled in a blocking mode; carrying out dimension reduction on the covariance matrix based on a principal component analysis method; carrying out parameter sensitivity matrix approximate calculation, solving a collaborative Kriging equation, and calculating an estimated value of a to-be-solved parameter by utilizing an iteration mode; and determining a target function, and performing iterative updating according to the target function to obtain a to-be-solved parameter column vector. The invention designs a partition geological statistics dimension reduction inversion method for describing the spatial-temporal heterogeneity of the hydrogeological parameters, and provides an efficient and accurate solution for describing the spatial-temporal heterogeneity of the parameters in a complex spatial-temporal process.

The invention discloses a three-level ANPC converter model prediction control method and device based on Newton iteration method vector optimization, and belongs to the technical field of converter control, and the method comprises the steps: building a mathematical model of a three-level ANPC converter under a three-phase static coordinate system based on the Kirchhoff theorem; performing forward Euler discretization on the mathematical model of the three-level ANPC converter to obtain a current prediction equation model; establishing a cost function according to the control target; performing online search on the optimal voltage vector according to a cost function; voltage vector synthesis is carried out, voltage vectors selected when the optimal voltage vector falls in 36 different small sectors, a voltage vector action sequence and action time distribution are obtained through calculation, and then the action time of a pair of redundant positive and negative small vectors in the voltage vectors is adjusted to carry out neutral point potential balance control. According to the invention, rapid optimal voltage vector search and three-level ANPC converter output current and neutral point potential control are realized.

The invention relates to the technical field of railway reconstruction, and discloses a line reconstruction optimization method for a local strong constraint section, a medium and equipment, and the method comprises the steps: S1, importing an initial plane scheme; s2, performing constraint detection and generating a strong constraint section; s3, optimizing the initial plane scheme; and S4, respectively carrying out point-line consistency and constraint condition detection on the plane scheme subjected to primary reconstruction by adopting a strong constraint oscillation iteration method. According to measuring point coordinates, a dynamic threshold method and an MADS algorithm are utilized to generate an optimal initial scheme for plane line position reconstruction of the existing railway, and a line default quantitative evaluation model is provided to respectively formulate evaluation standards and methods for two constraint conditions with different properties, so that the default condition can be accurately and comprehensively measured. Plane linear reconstruction is realized through a'difficult-first-easy-later 'fitting strategy, and finally, a strong constraint oscillation iteration method is proposed to optimize linear parameters, so that the accuracy of local optimization is ensured.

The invention discloses a circular foundation pit diaphragm wall deformation calculation method and system based on a vertical elastic foundation beam. The method comprises the steps that S100, a design scheme and design parameters of a circular foundation pit are collected; s200, establishing a vertical elastic foundation beam calculation model of the circular foundation pit supporting structure, and inputting the design scheme of the circular foundation pit into the model; s300, dispersing the beam into a plurality of calculation points, dividing the excavation step into a plurality of load increment steps, and calculating each load increment step of the beam; and S400, based on the load increment step of the beam, calculating an accumulated deformation amount, and outputting the accumulated deformation amount. A bending equation of a vertical elastic foundation beam is adopted to establish a calculation model of a circular foundation pit supporting structure, an inner supporting structure is introduced into the bending equation of the beam, the excavation process is decomposed into a plurality of excavation steps and increment steps, an iteration method is adopted for calculation, and the soil pressure distribution and deformation process of each stage in the excavation process is accurately simulated. Therefore, the accuracy of deformation calculation of the circular foundation pit diaphragm wall is improved.

The invention discloses a fast scanning seismic travel time calculation method based on a process function equation, and relates to the field of seismic travel time calculation, and the method comprises the steps: firstly, reading a speed model and related parameter information; then carrying out seismic source initialization, setting a slowness fixed item, calculating a travel time fixed item, and setting a travel time disturbance item according to the position of a seismic source point; next, Gauss-Seidel iterative calculation is carried out, in four alternating directions, a Gauss-Seidel type iterative method is used for solving an eikonal equation of factorization, a proper travel time disturbance term is selected through a causal condition, and finally, a travel time calculation result meeting a termination condition is output. According to the high-precision seismic travel time calculation method based on the factorization eikonal equation, the problem of seismic source singularity is well solved, high precision is guaranteed, meanwhile, the algorithm has high calculation efficiency, and the accuracy of subsequent seismic exploration data processing is improved.

The invention discloses an inner-layer process dynamic optimization method based on an RBF coherent method. The inner-layer process dynamic optimization method comprises the following steps: giving a control variable initial value u0, a state variable initial value x0, optimization time t0 and te and boundary constraints of all variables; performing variable discretization; simulation of a DAE model equation is carried out once in each optimization iteration, and model calculation is carried out on a discrete nonlinear algebraic equation set in a simulation layer by adopting a Newton iteration method to obtain a value of a state variable; during model calculation, obtaining a sensitivity information matrix of a state variable to a control variable and a time variable; and in each optimization iteration process, the previous steps are repeated, and an NLP solver is utilized to solve the nonlinear programming problem processed by the simulation layer until the convergence precision of optimization iteration is achieved, and an optimal solution is found. According to the method, optimal scheduling of the fast climbing ability of the CHP unit is considered, wind power consumption can be promoted on the premise of ensuring the feasibility of a CEHS scheduling scheme, and the operation cost is saved.

The invention discloses a high-resolution particle image velocity measurement method based on a lightweight model. The method comprises the following steps: S1, acquiring a data set; s2, an RFPA-PIV model is constructed, the RFPA-PIV model is trained based on the data set, and the RFPA-PIV model comprises a feature encoder, a 4D correlator establishment module, a decoder and an up-sampling module; and S3, obtaining an optimized RFPA-PIV model so as to predict a velocity field from the particle image. According to the method, the resolution feature map of the particle image is extracted through the feature encoder in the RFPA-PIV model, so that the calculation complexity of the RFPA-PIV model can be reduced, and meanwhile, the performance of the RFPA-PIV model is kept; the decoder iteratively updates the set initial optical flow according to the correlation pyramid established by the 4D correlation body establishment module and the resolution feature map extracted by the feature encoder, and generates an accurate velocity field through an iteration mode, thereby reducing the parameter quantity and the video memory consumption of the RFPA-PIV model in the training and reasoning process, and improving the calculation efficiency.

The invention relates to a method for controlling physical quantity of underwater explosion near a naval vessel based on a multiphase flow model, and belongs to an anti-impact technology of underwater explosion near the naval vessel. According to the method, an additional correction equation related to total mixed energy is created, and a model is expanded into seven equation models. A mixed energy correction equation is introduced, and a more accurate gas state equation is combined, so that the difference between the predicted thermodynamic states under the shock wave condition is solved; an algorithm program of an improved six-equation model is provided on an unstructured grid system, a homogeneous hyperbolic equation is solved by using a second-order MUSCL-Hancock format based on least square reconstruction and a Barth-Jespersen limiter and a two-phase flow HLLC Riemann solver, and then an instantaneous pressure relaxation equation is solved by using a Newton-Raphson iteration method. By improving the six-equation model in the diffusion interface method, the interface capture precision and the numerical algorithm stability are improved.

The invention discloses a water level prediction method based on an improved intelligent algorithm, a readable storage medium and a device, and belongs to the technical field of water level prediction.The method comprises the steps that normalization preprocessing is conducted on original hydrological data of multi-source information, and an original water level sequence is obtained; performing VMD decomposition on the original water level sequence to decompose the original water level sequence into modal components; inputting the modal component into an LSTM model to construct a prediction model; and inputting an original water level sequence of recent multiple days into the prediction model, generating a predicted value of a future date based on an iteration mode, and restoring to obtain real water level data through reverse normalization processing. A computer program is stored in the readable storage medium, and the method is carried out when the computer program is executed. The apparatus includes a memory, a processor, and a terminal program stored in the memory and operable in the processor. Water level influence factors can be comprehensively considered, multiple variables are fused, the water level condition closer to the reality is obtained through analysis, and the water level prediction precision is improved.

The invention provides a multiphase multicomponent seepage numerical simulation method based on a discrete fracture model. The method comprises the following steps: step 1, establishing a multi-phase multi-component seepage mathematical model, and solving; step 2, mesh generation of the discrete fracture model; step 3, discretization of a mass conservation equation; step 4, calculating the conductivity between the matrix and the crack; and 5, establishing a nonlinear equation set, and completing solution by adopting an automatic differential technology and a Newton iteration method. According to the method, a complex fracture network is represented through a discrete fracture model, reservoir stress sensitivity and nonlinear seepage characteristics are considered, adsorption and diffusion effects of a surfactant and salt and mechanisms such as capillary pressure, relative permeability curve and osmotic pressure change under the action of the surfactant and the salt are coupled, and a multi-phase multi-component seepage mathematical model is established. According to the method, fracture explicit representation is achieved through a self-adaptive mesh generation method, a finite volume method is adopted for solving, the model is established, and therefore ultra-low permeability-tight oil reservoir development simulation under the influence of a complex fracture network is achieved.

The invention discloses a multi-algorithm collaborative three-dimensional positioning method based on UWB and IMU, and the method comprises the steps: constructing a three-dimensional space rectangular coordinate system based on a plurality of UWB base stations, measuring the distance between a label and the UWB base stations through bilateral bidirectional distance measurement, and obtaining a corresponding distance variable; establishing a nonlinear equation set through a trilateral positioning algorithm, substituting a distance variable, converting the nonlinear equation set into a linear error equation set, and obtaining a group of three-dimensional coordinates of the label through a Newton iteration method; obtaining a nonlinear equation set through the time difference of arrival, obtaining a linear error equation set based on Taylor expansion approximation, and obtaining another group of three-dimensional coordinates of the label through a least square method; performing weighted average on the two groups of three-dimensional coordinates to obtain an initial three-dimensional coordinate; and constructing a state transition model based on the initial three-dimensional coordinate, the velocity component and the acceleration component, predicting the state of the next moment based on Kalman filtering, updating the three-dimensional coordinate of the label, and outputting a final three-dimensional space positioning result. According to the invention, high-precision three-dimensional positioning can be realized.

The invention belongs to the related technical field of cross-scale particle transport simulation, and discloses a particle transport discrete unified gas kinematics simulation method and system especially suitable for complex non-conservative collision operators. According to the method, high-precision compact reconstruction of a distribution function at a characteristic line is realized in a compact space of a single grid through a universal compact reconstruction method, and particle transport complex non-conservation collision implicit terms under time trapezoidal integration are effectively processed through a universal estimation-correction method. The defects of application limitation of an existing discrete unified gas kinematics method on a complex non-conservation collision term operator transport model or low calculation efficiency, error accumulation, numerical instability and the like existing in an existing repeated iteration method, a time splitting-discrete unified gas kinematics method and the like are overcome. And the problem that the calculation precision is relatively low when an existing interface reconstruction method based on a plurality of adjacent grids is used for solving a particle transportation problem with complex substance arrangement or relatively high heterogeneity is solved.

The invention belongs to the related technical field of power system optimization operation, and particularly relates to a non-iterative interconnected multi-microgrid system optimal power flow determination method based on a dimensionality reduction projection method, and the method comprises the steps: reconstructing a multi-microgrid centralized operation model, and obtaining a sub-problem of each sub-microgrid; taking a multi-dimensional variable space formed by all public variable sets in each sub-problem and a preset sub-microgrid operation cost variable as a projection space of the sub-problem; determining an initial vertex set of the projection of the convex hull corresponding to the original operation space constraint of each sub-problem in the projection space, and translating the coordinate origin to the interior of the convex hull enclosed by the vertex set; based on the convex hull and the outer normal vector of each boundary surface, circularly searching vertexes satisfying original operation space constraints outside each boundary surface in the projection space, and taking a space enclosed by a final vertex set as a projection space of the operation space constraints of the sub-problem; and reconstructing the sub-problem in the space and solving the sub-problem. According to the method, the optimal power flow can be solved under the condition that only public variables are disclosed.

The invention discloses an iterative satellite internet confrontation method based on momentum, and mainly solves the problem of low success rate of black box migration attack in the existing method. According to the method, a momentum item is introduced in an iterative optimization process of adversarial sample generation and is used for recording a historical direction of gradient updating. According to the momentum iteration method, the gradient updating direction in the adversarial sample generation process can be more stable, meanwhile, the adversarial sample is prevented from falling into a local extreme point of an optimization problem, the mutual restriction of the white box attack effect and the migration capability of the adversarial sample generated by the existing method is effectively relieved, and the black box migration attack success rate is improved.

The invention provides a financial research report generation method based on a large model. Comprising a data collection module, a data analysis module and a report writing module. The data collection module is used for receiving a predefined data collection task and an autonomously generated data collection task, then inputting the tasks into a deep search agent, and constructing a structured multi-modal memory for a search result for storage; the data analysis module constructs a data analysis agent, and realizes the generation of a structured multi-modal small report through cooperation of a financial calculation tool, a chart generation tool and a reference addition tool in an actor-reviewer iteration mode in which a large language model is matched with a visual language model; and the report writing module constructs a report writing agent to obtain a chapter first draft and then inputs the chapter first draft into the post-processing agent to obtain a final report. The problems that an existing deep research system and a large language model agent in the financial field are lack of financial field knowledge, limited in multi-modal ability, limited in research and report generation depth and comprehensiveness and the like are solved.

The invention provides a new energy station electricity-hydrogen energy storage collaborative configuration method based on time sequence production simulation, which comprises the following steps: constructing a degradation model of hydrogen-electricity conversion equipment in a new energy station, and constructing an electricity-hydrogen collaborative configuration model of the new energy station based on the degradation model and the time sequence production simulation; linearizing the electricity-hydrogen collaborative configuration model through a linear programming solving method, and obtaining a linearization result; simplifying a linearization result by using a matrix transformation method, and obtaining a calculation matrix; and solving the calculation matrix through an iterative method, and obtaining an optimal solution, thereby obtaining a new energy station electricity-hydrogen energy storage collaborative configuration scheme. According to the method, the influence on the service life of each type of equipment and the influence on the station operation cost are quantitatively analyzed through the degradation model, so that a more perfect electricity-hydrogen collaborative storage configuration model is constructed, solving is performed based on a linear programming solving method, a matrix transformation method and an iteration method, the solving difficulty of the model is reduced under the condition that the accuracy is ensured, and the efficiency is improved. And an optimal configuration scheme can be quickly obtained.

The application discloses a kind of gas-liquid two-phase flow numerical simulation method considering coalbed gas desorption lag, comprising the following steps: using well logging, indoor experiment means to obtain productivity calculation parameter;Desorption equation of matrix system is defined in combination with desorption lag effect, diffusion equation;Gas-water two-phase percolation equation of fracture system is defined, and desorption equation of matrix system, diffusion equation is combined, and double medium gas-water two-phase coupling flow equation set is formed;The porosity and permeability change of matrix system and fracture system in production process is calculated respectively, and the physical property change equation set of double medium is deduced;Using the numerical solver of COMSOL, the coupling equation set is solved using iterative method, and the gas production and water production are calculated.The application is simple to operate, can more scientific and reasonable assess the influence of coalbed gas desorption lag effect on gas well productivity, while greatly reducing the cost and time of gas well numerical simulation calculation, and also has important inspiration for other unconventional gas reservoir development affected by desorption lag.

The embodiment of the invention discloses a nonlinear system dynamic characteristic calculation method based on a structural dynamic modification method, and the method achieves the high-precision reduced-order modeling of a nonlinear structure through enabling a complex nonlinear effect to be equivalent to an additional stiffness field and combining with a structural dynamic modification algorithm. And based on the decoupled linear substructure modal space, a nonlinear correction operator is introduced, and the global dynamic response of the nonlinear structure is solved through a resolving method after modification. Structural vibration frequency, vibration shape and energy dissipation characteristics under a nonlinear effect can be efficiently obtained, and dynamic characteristics under different nonlinear amplitudes can be obtained. Compared with a traditional iteration method, the method has the advantage that the calculation complexity is remarkably reduced by equivalently linearizing a nonlinear part.

The invention discloses a gas-liquid two-phase flow numerical simulation method considering coal bed gas desorption lag. The method comprises the following steps: acquiring productivity calculation parameters by using logging and indoor experiment means; defining a desorption equation and a diffusion equation of the matrix system in combination with a desorption hysteresis effect; defining a gas-water two-phase seepage equation of the fracture system, and forming a dual-medium gas-water two-phase coupling flow equation set in combination with a desorption equation and a diffusion equation of the matrix system; the porosity and permeability changes of a matrix system and a fracture system in the production process are calculated respectively, and a physical property change equation set of the double media is deduced; and solving the coupling equation set by using a numerical solver of COMSOL and adopting an iteration method, and calculating to obtain gas production and water production. The method is easy and convenient to operate, the influence of the coal bed gas desorption lag effect on the gas well productivity can be evaluated more scientifically and reasonably, meanwhile, the gas well numerical simulation calculation cost and time are greatly reduced, and important inspiration is also provided for development of other unconventional gas reservoirs influenced by desorption lag.

The invention discloses a series robot calibration algorithm based on an index product, and the algorithm comprises the following steps: A1, building an index product motion model according to a robot joint axis and coordinate points on the axis through an index product modeling method, a2, differentiating the positions of the robot hand-eye, the kinematics and the calibration object relative to the robot base coordinate system to obtain a hand-eye, kinematics and calibration object position error model based on an exponential product; b1, obtaining an initial value of a robot system hand-eye matrix # imgabs0 # and an initial value of a calibration object relative to the position Bp of a robot base through a closed solution method based on a Kronecker product; b2, taking the difference between the predicted value and the measured value of the base position of the calibration object under the robot base as a target function; and B3, establishing an optimization algorithm by taking the hand-eye, kinematics and calibration object position parameters of the robot as to-be-optimized parameters, and carrying out iterative optimization calculation on the hand-eye, kinematics and calibration object position parameters of the robot by using a Newton iteration method.

The embodiment of the invention provides a calculation method and device for boundary parameters of a supercritical fluid heat exchanger, computer equipment and a medium, and relates to the technical field of fluid mechanics and heat transfer science calculation.The method comprises the following steps that design parameters and target working conditions of the heat exchanger are obtained; calculating to obtain the single section length of each infinitesimal section; based on the initial inlet pressure guess value, according to the length of the single section and the pressure and the temperature of the infinitesimal section i, the pressure and the temperature of the infinitesimal section i + 1 are obtained through calculation, the difference value between the outlet calculation pressure and the target outlet pressure is calculated, and the difference value serves as a pressure error; if the pressure error is greater than the convergence tolerance, updating the inlet pressure guess value by adopting a numerical iteration method, and performing iteration again based on the inlet pressure guess value after iteration; otherwise, iteration is terminated, and the final inlet pressure value and the final outlet temperature value are output. According to the scheme, the calculation efficiency and accuracy of solving the inlet pressure and the outlet temperature of the supercritical fluid heat exchanger under the given target outlet pressure are improved.