102results about How to "Improve approximation accuracy" patented technology

The invention provides a method for estimating global vegetation coverage. The method comprises the following steps: firstly, selecting a plurality of global land surface space sampling points according to distribution of global vegetation types; acquiring a first earth surface reflectivity data with a high space resolution and a second earth surface reflectivity data with a low space resolution in satellite remote sensing data at the sampling points, and then acquiring a vegetation coverage training sample by using the first earth surface reflectivity data through a dimidiate pixel model; subsequently extracting the second earth surface reflectivity data and the vegetation coverage which is calculated according to the first earth surface reflectivity data with the space corresponding to the space of the second earth surface reflectivity data at the sampling points, respectively taking the second earth surface reflectivity data and the vegetation coverage as input and output of the training sample so as to train a generalized regression neural network; and finally estimating the global land surface vegetation coverage according to the second earth surface reflectivity data by using the trained model. The method for estimating the global vegetation coverage makes full use of ground actual measurement data, remote sensing observation data with high space resolution and artificial intelligence learning algorithm, and has the advantages of good stability, high adaptability, high accuracy, easiness in operation and the like.

The invention provides an air conditioning system sensor fault diagnosis method based on a wavelet neural network. The method is characterized by comprising the steps that comprehensive analysis and diagnosis are conducted for defining an air conditioner state control, a diagnosis condition set and a decision event set; sensor fault classification and characteristic description of an air conditioner system are used for classifying fault types; sensor fault diagnosis of the air conditioning system is used for generating a fault diagnosis flow; a network structure and a primary function are determined; selection and pretreatment of training samples are conducted; and an alarming threshold is set. The method has good diagnosis effect on abrupt changing faults such as bias faults and completefaults. Drift biases can be detected as long as the drift distance exceeds the alarming threshold. The method also has good fault detection effect on precision decrease faults of sensors.

The invention provides a method of simulating behavior of a flow interacting with an object. The invention improves the accuracy of the approximation of the spatial p^th derivative D_p, p≧1, and therefore reduces the cost of the simulation. It includes in the approximation values of the parameter at points which do not lay on grid lines passing through the point of computation P, and by using these values to optimize the approximation. The use of these additional points depends on a preferential direction, such as determined by the advection direction of the flow. The points used in the approximation extend beyond a unit cube on the computational grid. The simulation is in three or more dimensions. The numerical simulation produces output which can be used in the design or optimization of the object which interacts with the flow. In certain cases, it is the output by itself which is important.

The invention provides a rapid evaluation method of the disturbing gravity along a flight trajectory for the first time. The rapid approximation method with ballistic missiles as research objects aims at solving the problem of rapid evaluation on the disturbing gravity in the missile flight process. The rapid evaluation method comprises generating a standard trajectory according to a launch task; generating a flight pipeline with the standard trajectory as a benchmark and performing airspace subdivision; performing evaluation on the node disturbing gravity by a point quality method or a high-order spherical harmonic function method; calculating a disturbing gravity value of any point on an actual trajectory based on a network function approximation theory inside a calculation unit and achieving the whole rapid evaluation calculation on the disturbing gravity along the flight trajectory. Compared with the existing method, the rapid evaluation on the disturbing gravity along any flight trajectory can be implemented, the trajectory calculation requirements for the evaluation precision of the rapid evaluation method are met, the evaluation speed, the data storage and other indexes are excellent, and the real-time evaluation on the disturbing gravity missiles is implemented.

Systems and methods for approximating caloric energy intake and/or macronutrient composition using thermogenesis. The system may include one or more sensors for tracking body temperature over a period of time, and may include a processor configured to determine caloric energy intake and/or macronutrient composition based on body temperature. The system may be configured to normalize body temperature readings to compensate for factors other than thermogenesis that might affect core body temperature. The system may include one or more sensors for measuring normalization factors, and a processor for normalizing raw body temperature readings based on the measured normalized factors. The method may include the steps of: (a) collecting body temperature data, (b) normalizing the raw body temperature data and (c) determining caloric energy intake and/or macronutrient composition from the normalized data. The system may be configured to account for user calibration data when characterizing macronutrient composition.

The invention discloses a robot tail end multi-target position and pose approach method based on joint angle compensation. The method comprises the steps that when target values of all joint angles are determined according to nominal values of geometric parameters of a robot, and all joints of the robot are controlled to move to the target values of all the joint angles, geometric parameter errorsof the robot are identified according to the acquired measured data values of robot tail end position and pose, the identified geometric parameter errors of the robot are converted into correction values of all the joint angles of the robot, and the correction values, of the joint angles, obtained through conversion are combined to calculate to obtain compensation values, of the joint angles, forcontrolling the robot to execute the multi-target position and pose approach action. According to the method, the compensation values of the joint angles can be used for replacing the compensation ofthe geometric parameter errors to control the robot to move, so that the problem that a robot control system is closed or semi-closed, and a user cannot directly compensate the geometric parameter errors obtained through identification is solved, and the precision and efficiency of the robot tail end absolute position and pose are effectively improved.

The invention discloses a hyperspectral image classification method based on MNF (Minimum Noise Fraction) transform in combination with extended attribute filtering. The method comprises the steps of 1) performing MNF transform to a hyperspectral remote sensing image; 2) selecting MNF component number and selecting the MNF component number to be reserved according to two constraints, i.e. the characteristic value of band number and the gradient of the characteristic values of adjacent bands; 3) executing EAP (Extended Attribute Profile) operation to each MNF component; 4) stacking the image attribute open profile and the attribute closed profile of each MNF component and the component and performing classification by adopting a K-type SVM (Support Vector Machine) to obtain a final hyperspectral classified image. The method can realize noise reduction through MNF and can effectively reduce the dimensionality of hyperspectral data at the same time. On the basis, spectral information after dimensionality reduction and texture information obtained after EAP filtering are combined, then the characteristics that the K-type SVM can reduce the computation cost and simultaneously has performance similar to an RBF (Radial Basis Function) kernel are utilized and the classification accuracy of the hyperspectral remote sensing image is improved.

The invention discloses a pneumoelectric integrated energy system distribution network optimization method considering pneumoelectric joint demand response, and the method comprises the steps: establishing a pneumoelectric integrated energy system distribution network optimization operation model through employing the minimization of the operation cost of a distribution network system as a targetand combining with a set related operation constraint; aiming at the nonlinear alternating-current power flow equation constraint of the power distribution network, adopting a second-order cone relaxation method for processing; aiming at a nonlinear Weymuth power flow equation of the gas distribution network, proposing an enhanced second-order cone relaxation method of adding a gas pressure penalty term into a target function to further tighten a relaxed constraint condition, and converting a non-convex optimization problem into a convex optimization problem to be solved, so that relatively high relaxation precision is achieved. On the basis of a distribution network optimization scheduling model, an operation strategy for improving the new energy consumption capability and the operation economy of a distribution network system by utilizing gas-electricity joint demand response is provided.

The invention discloses a spatial hierarchical grid disturbance gravity field model building and disturbance gravity quick determination method which overcomes the defect that in the prior art, a disturbance gravity field still needs to be further studied. The method comprises the following steps that firstly, height level division is performed; in other words, external space is divided into a plurality of sections according to gravity variation characteristics of global outer disturbance; secondly, grid cell approach and grid division criteria are formulated; in other words, approach is performed through grid units based on wide-area polynomials different sections respectively, and accuracy is analyzed; thirdly, the criteria are utilized for disturbance gravity model building; fourthly, disturbance gravity is calculated in real time through a model, the application requirement of an aircraft in the high-speed flight process is combined, and therefore the disturbance gravity can be calculated efficiently in a high-accuracy mode. Compared with the prior art, the calculated amount is small, calculation can be achieved without a specially advanced computer, multiple types of gravity measurement data are not needed, and approach accuracy is high.

The invention discloses a method for optimizing a reconstruction model of disturbing gravity along a gliding trajectory. The method comprises the following steps of firstly, computing a three-dimensional envelop of a trajectory of a pole changing coordinate system; secondly, dividing the whole airspace of the pole changing coordinate system; thirdly, establishing a whole reconstruction model of the disturbing gravity of a general coordinate system; fourthly, establishing a local reconstruction model of the disturbing gravity along the trajectory; fifthly, establishing a fast approximation algorithm of the disturbing gravity in a flight process based on this; sixthly, carrying out experiment design and constructing an agent model of the reconstruction model; and lastly, establishing an optimization method for the agent model. According to the method for optimizing the reconstruction model of the disturbing gravity along the gliding trajectory, a minimal storage capacity model under the given accuracy requirement and a highest accuracy model under the given memory space requirement can be obtained, the requirements of onboard real-time computation for data storage capacity, the computation speed and the reconstruction accuracy can be met, and the method has better prospect in engineering application.

An ECU obtains two data values (a peak value and a waveform correlation coefficient) that show the characteristics of a knock from the output of a knock sensor. The ECO approximately obtains the mean of each data value by smoothing each data value, and approximately obtains a variance by smoothing the squared deviation between the data values before and after the smoothing process. The ECU then computes the square root of the variance to approximately obtain a standard deviation. The ECU normalizes each data value using the mean and the standard deviation, obtains a distribution of the normalized two data values, and calculates a correlation coefficient that shows the correlation between the obtained distribution and an ideal knock distribution. Based on the correlation coefficient, the ECU corrects a knock determination threshold value. Therefore, the mean and the standard deviation of the data values are computed with a small RAM capacity.

The invention relates to a high time consumption constraint-oriented rapid approximate optimization method for aircrafts, and belongs to the technical field of multidisciplinary optimization. The method comprises the following steps of: in the process of optimizing an engineering design problem with constraints, constructing an agent model according to known sample point information, a constraint corresponding to a sample point and a penalty coefficient updated at each time in each iteration process; optimizing the agent model and adding a sample point; calling a real analysis model to obtain a corresponding function value and a corresponding constraint value; if the optimized sample point satisfies the constraint, decreasing the penalty coefficient to ensure that the next optimization iteration places emphasis on improving the optimality; if the optimized sample point does not satisfy the constraint, increasing the penalty coefficient to ensure that the next optimization iteration places emphasis on improving the feasibility; and carrying out repeated iteration until a termination criterion is satisfied. The method can consider the local approximate accuracy and the global approximate accuracy, has an ability of processing constraints and is capable of effectively improving the optimization efficiency and saving the aircraft optimization design cost.

The invention provides a full-drive ship trajectory tracking control method based on an instruction filtering neural network controller, which comprehensively considers unknown ship model parameters, external environment interference, input limitation and ship output transient state and steady state performance constraint, and effectively processes the problem of input limitation by utilizing an instruction filter. The method comprises steps that unknown parameters of the system are estimated by using the RBF neural network and the predictor, and approximation precision of the neural network is improved; recursive errors are designed for controller design, and non-vulnerability of the system is improved; the time-varying asymmetric obstacle Lyapunov function and the performance function are combined to effectively constrain the transient performance and the steady-state performance of the ship output trajectory, the application range is expanded, and the performance of the controller is better.

The invention relates to a switching current Gauss low-pass filter which is comprehensively implemented by using the central limit theorem to obtain a transfer function of a Gauss low-pass filter and adopting a switching current bilinear integrator cascade structure with a plurality of negative feedback branches. The switching current Gauss low-pass filter comprises a current mirror circuit, a plurality of first switching current bilinear integrators and a second switching current bilinear integrator, which are in cascade connection sequentially. The switching current Gauss low-pass filter has the following beneficial effects: the filter is constructed by adopting a switching current bilinear integrator cascade structure with a plurality of negative feedback branches, so that the sensitivity of the filter is effectively reduced, and the actual frequency response characteristic of the circuit is enabled to be close to the ideal frequency response characteristic; and the switching current Gauss low-pass filter is large in dynamic range, high in approximation accuracy and simple in design process, needs no analog-to-digital converter, and is applicable to low-voltage and low-power large-scale integration.

A method of designing a small-sized, self-shielding magnetic field gradient coil assembly that is for use in an NMR spectrometer, provides high approximation accuracy, is simple in structure, and has a large inside diameter. The gradient coil assembly consists of tightly wound inner and outer coils. The designing process starts with setting or resetting the number of the inner coils and the number of turns of each inner coil. Their positions are optimized such that the magnetic field gradient strength falls within a tolerable range under shielded condition. Then, the number of the outer coils and the number of turns of each outer coil are set. The Fourier components of a current distribution necessary for the outer coils are calculated.

The invention discloses a cycloidal gear tooth curve variable step size discretization method, which comprises the following steps of S1, setting a cycloidal gear tooth curve parameter; S2, deriving out a cycloidal gear tooth curve equation; S3, deriving out a formula of the curvature radius Rho of the practical tooth curve of a cycloidal gear; S4, deriving out an equation of phi relevant to a pressure angle alpha; S5, deriving out an inflexion equation of the cycloidal gear tooth curve; S6, giving the curve linear interpolation initial step size discretization method. The discretization errors and given errors are compared for automatically regulating the closing step size, so that the maximum step size smaller than the closing errors can be obtained; on the premise of meeting the precision requirements, the number of cutting feeding times is reduced; the processing efficiency is improved. The cycloidal gear tooth curve variable step size discretization method provided by the invention has the advantage that the good integral index is realized in the aspects of closing precision, discretization efficiency and calculation speed.

The invention discloses a random orthogonal expansion method for solving the uncertain heat conduction problem. The method comprises the following steps of performing quantification representation on uncertain parameters in the heat conduction problem by introducing random variables; building a random differential control equation of the heat conduction problem by combining the random variables; selecting an orthogonal polynomials substrate function according to the random variable distribution type; performing orthogonal expansion on the random temperature response; giving the collocation point number of each random variable; building a collocation point set of the whole uncertain space by using a tensor product law; calculating the temperature response in positions of all collocation points; solving each coefficient in the temperature response orthogonal expansion formula by using the generalized inverse of a matrix; and calculating the average value and the standard deviation of the random temperature response according to the orthogonal relationship of the substrate function. The method has the advantages that the heat conduction problem containing random uncertain parameters can be systematically solved; the calculation precision of a random uncertain analysis method is further improved; and the effect cannot be achieved by general commercial software.

The invention discloses a method for numerical solution of a fuzzy steady state heat conduction problem based on a full grid point collocation theory. The method comprises the first step of carrying out finite element modeling of a steady state heat conduction structure; the second step of utilizing fuzzy variables to represent uncertain input parameters and then obtaining a fuzzy finite element equation of the heat conduction problem; the third step of utilizing cut set operation to rewrite the fuzzy finite element equation to be a group of interval finite element equations; the fourth step of performing approximate representation on temperature response functions in the interval finite element equations based on a polynomial theory; the fifth step of quickly solving the interval variation range of a temperature response approximate functions according to the full grid point collocation theory; the sixth step of utilizing a fuzzy resolution theory to recombine temperature response intervals under all cut set levels, and finally obtaining a membership function of the fuzzy temperature response. According to the method, the prediction of structure heat conduction temperature field containing fuzzy uncertain parameters can be achieved systematically, and the calculation accuracy can be effectively improved on the premise of guaranteeing that the calculation efficiency meets the engineering requirements, which cannot be achieved through common commercial software.

The invention provides a method for multi-wave continuum speed analysis, and belongs to the field of oil and gas geophysics. The method comprises the following steps of (1) performing continuum speed analysis on a longitudinal wave common center point gather or a conversion wave common conversion point gather, and generating a continuum speed field; (2) when the travel of each of the longitudinal wave common center point gather or the conversion wave common conversion point gather is calculated, performing continuum speed dynamic correction on a longitudinal wave or conversion wave pre-stack gather, and correcting to the vertical traveltime t0.

The invention discloses a scenic spot passenger flow volume prediction method and system based on a hybrid optimization RBF neural network, which are used in the field of scenic spot management, and the prediction process adopts a radial basis function neural network and a hybrid optimization algorithm, and comprises the steps of data collection, data preprocessing, model establishment, center andvariance determination, global optimization, local optimization and passenger flow prediction. Compared with the traditional BP neural network, the RBF neural network adopted by the method has stronger generalization ability and higher approximation precision, is more suitable for the field, and improves the timeliness of prediction. The hybrid optimization improves the prediction accuracy through the global search capability of the fish swarm algorithm and the local convergence of the particle swarm algorithm. The invention can more accurately predict the number of tourists in each scenic spot in the next few days, and provides help for scenic spot managers to make decisions.

The invention provides a formation control method for a multi-quadrotor aircraft with a predictor. The method comprises the following steps: 1, setting one quadrotor aircraft as a leader, setting N quadrotor aircrafts with unknown dynamics as followers, and enabling a networked system formed by the followers and the leader through the connection of a one-way topological graph to serve as a controlled object; and 2, arranging a position controller and a posture controller on the ith follower in the N followers, connecting the input end of the position controller and the input end of the posturecontroller of the ith follower with the output end of a directed graph G, connecting the output end of the position controller of the ith follower is connected with the input end of the position controller of the ith follower, and connecting the output end of the ith follower posture controller with the input end of the posture controller of the ith follower. Collision avoidance and connection maintenance among the multi-quadrotor aircrafts are realized, an expected formation pattern is completed, obstacles are avoided, and a formation control target is completed in a predetermined performance range.

The invention discloses a high-precision numerical value method for solving an interval heat convection diffusion problem. The high-precision numerical value method comprises the following steps: establishing a heat transfer control equation of the heat convection diffusion problem; introducing an interval variable to represent the uncertainty of an input parameter in a heat transfer model, and establishing an interval control equation of the heat convection diffusion problem; utilizing a Legendre polynomial expansion to carry out approximate representation on temperature response in the interval control equation; according to tensor product operation, determining a collocation point set in a high-dimension space; utilizing a finite element program to calculate the temperature response of all collocation points, establishing a linear equation set in regard to an expansion coefficient in a temperature response approximate expression, and adopting a least square method to solve; and on the basis of the smoothness of a polynomial function, determining an extreme point of the temperature response approximate expression, and obtaining the upper bound and the lower bound of interval temperature response. The high-precision numerical value method can systematically solve the heat convection diffusion problem with interval uncertainty parameters and effectively improves the calculation precision of the interval numerical value method.

The invention discloses a milling stability analysis method based on an overall discrete strategy. The method comprises the following steps: converting a milling time delay kinetic equation of a milling system into a state space equation; obtaining an analytical solution of the state space equation according to the situation that the milling system is in the free vibration process, and for the situation that the milling system is in the forced vibration process, adopting a Lagrangian interpolation function to integrally approach a periodic coefficient item, a state item and a time delay itemof the state space equation for solving; constructing a Floquet transition matrix according to the solution of the state space equation; and calculating the spectral radius of the Floquet transition matrix, and judging the stability of the milling system according to the spectral radius. According to the method, the calculation process of milling stability analysis is simplified, the calculation efficiency is improved, and compared with an existing semi-discrete method and an existing full-discrete method, higher approximation precision can be obtained.