41 results about "Uncertainty interval" patented technology

The invention discloses a regional integrated energy system operation robust optimization method considering electricity-to-gas conversion and uncertainty, and the method comprises the steps: carryingout the detailed modeling of an electricity-to-gas conversion process according to the principle of an electrochemical reaction, and analyzing the coupling relation between different energy forms ina matrix mode based on an energy center model; establishing a regional comprehensive energy system operation optimization model considering the uncertainty of various load prediction powers, and establishing a two-stage robust optimization model according to a polyhedral uncertain interval; and decomposing the two-stage robust optimization model into a main problem and a sub-problem, converting the sub-problem into an optimization problem of a single target, and carrying out iterative solution to obtain a comprehensive energy system robust optimization scheme. According to the method, the potential of complementary mutual relief and flexible scheduling among multiple energy forms is fully excavated, wind curtailment can be reduced, and the operation economy and flexibility of the comprehensive energy system are improved; and the contradiction between the operation risk and the cost can be coordinated according to the actual condition of the regional integrated energy system.

The invention discloses a hydrological model comprehensive uncertainty analysis method based on a Copula function. The method comprises the following steps: (1) collecting data information of a water basin; (2) establishing a hydrological model to simulate a water basin outlet section flow process; (3) determining a marginal probability distribution function of actually measured flow and simulation flow; (4) using the Copula function to construct an united probability distribution function of the actually measured flow and the simulation flow; (5) solving a condition probability distribution function of the actually measured flow while the simulation flow is given; (6) acquiring median of the actually measured flow and an uncertainty interval. Through the adoption of the method disclosed by the invention, the uncertainties of the model parameter and the model structure can be more comprehensively considered at the same time so as to obtain the comprehensive uncertainty of the hydrological model. The method disclosed by the invention is independent from a certainty hydrological model, and can be synergistically integrated with the certainty hydrological model with any complexity without adding any assumption on the model, and a universal theoretical frame is provided for the analysis of the comprehensive uncertainty of the hydrological model.

A method reconstructs a depth image encoded as a base layer bitstream, and a set of enhancement layer bitstreams. The base layer bitstream is decoded to produce pixels of a reconstructed base layer image corresponding to the depth image. Each enhancement layer bitstream is decoded in a low to high order to produces a reconstructed residual image. During the decoding of the enhancement layer bitstream, a context model is maintained using an edge map, and each enhancement layer bitstream is entropy decoded using the context model to determine a significance value corresponding to pixels of the reconstructed residual image and a sign bit for each significant pixel, and a pixel value of the reconstructed residual image is reconstructed according to the significance value, sign bit and an uncertainty interval. Then, the reconstructed residual images are added to the reconstructed base layer image to produce the reconstructed depth image.

The invention relates to a service recommendation method based on user risk preferences. According to the service recommendation method based on the user risk preferences, an attribute extracting method based on the user risk preferences and the service recommendation method based on the user risk preferences are used. The attribute extracting method based on the user risk preferences is a simplifying method according to the characteristic of multiple attributes of services. According to the service recommendation method based on the user risk preference, considering that different users have different inclinations to take risks of unknown services, the users are classified according to the different user risk preferences, corresponding rules are adopted for different types of users, effective attributes better meeting requirements of the different types of users are extracted from multiple non-functional attributes from the services, similarity calculation is conducted, and a recommendation is formed finally. By the adoption of the service recommendation method based on the user risk preferences, simplification of the multiple attributes of services is achieved, a solution to the problem that uncertain intervals exists when the non-functional attributes of the services are grated during service recommendation is provided, in this way, recommendation results can better meet the requirements of the different types of users, and a powerful method and tool are provided for service recommendation.

The invention provides an expanded ellipsoid set-membership filtering method based on Chebyshev interpolation polynomial approximation. According to the expanded ellipsoid set-membership filtering method, the problems of complexness in computation and low efficiency and computational accuracy in a method based on Taylor-series linear approximation are solved. The expanded ellipsoid set-membership filtering method comprises the following steps: establishing a nonlinear strapdown inertial navigation system equation and an observation equation; computing an indeterminate interval of a system state parameter component of a (k-1) step; carrying out Chebyshev polynomial approximation computation on the nonlinear equation and the observation equation of the inertial navigation system; computing an error boundary of the Chebyshev polynomial approximation computation, so as to acquire outsourcing ellipsoids of the Chebyshev interpolation polynomial approximation computation errors of the nonlinear system equation and the observation equation; and by virtue of a linear ellipsoid set-membership filtering method, computing and predicting an ellipsoid boundary of a state variable, updating a computation state ellipsoid boundary, computing an estimation value of a state parameter variable of a k step, and estimating variance matrix. The expanded ellipsoid set-membership filtering method has the beneficial effects that a computational accuracy is relatively high, the computational complexness of an algorithm is reduced, and the computational stability of the expanded ellipsoid set-membership filtering method is effectively guaranteed.

The invention discloses a Stirling interpolation polynomial approximation based ellipsoidal set-membership filtering method. The method includes: firstly utilizing Stirling interpolation polynomial to obtain linear approximation of a nonlinear state equation, constructing an uncertain interval of system state variable, using a second order difference operator to obtain a linear error bound, constructing a virtual noise outsourced ellipsoid, using the current state variable estimate value to predict a system state variable prediction error boundary of the next moment, carrying out system state variable update operation according to the observation vector, then utilizing linear ellipsoid set-membership filtering steps to carry out estimation calculation of system state variable and calculation of system state variable's estimation error ellipsoid, thus completing the estimation calculation task of system state variable. The method provided by the invention utilizes Stirling interpolation polynomial approximation calculation to realize ellipsoid set-membership filtering, effectively reduces the calculation amount, enhances the computational efficiency, and improves the calculation precision of extended set-membership filtering algorithm.

The invention discloses a validation method of a non-probabilistic Bayesian model for an aircraft structure. The validation method comprises the following steps: firstly deducing a non-probabilistic Bayesian theory according to a proposed interval inclusion degree theory; then updating and validating an uncertainty numerical simulation model based on the proposed non-probabilistic Bayesian theory and in combination with validated test data and an uncertainty interval propagation algorithm. The validation method disclosed by the invention is performed under a Bayesian probability theory framework, prior information can be fully utilized, and the reliability of the numerical simulation model can be given; the model validation can be performed aiming at the situations of poor information and less data, so that the problem that a large amount of experimental data is needed when a traditional model confirmation method is utilized is solved.

The invention discloses a structural interval response propagation analysis method with multiple uncertain parameters based on an adjoint variable method. In the method, Taylor series expansion is performed on structural interval response, and a first-order approximate model of system response is obtained in an uncertain parameter interval. Based on this, upper and lower bounds of the interval response are obtained. For systems with multiple uncertain parameters, when the Taylor series is expanded, a partial derivative of the response with respect to the uncertain parameters is solved based onthe adjoint variable method, so that the number of times of system reanalysis can be reduced to obtain a partial derivative of the response with respect to all uncertain parameters, and the upper andlower bounds of the uncertainty interval of the system response are determined. The method greatly improves the computational efficiency under the premise of ensuring the accuracy of calculation. Therefore, the response boundary of the structure can be efficiently predicted.

The invention discloses a multi-unmanned aerial vehicle target allocation decision making method in an interval information condition, which comprises the following several steps: 1, multi-unmanned aerial vehicle target allocation decision making variables are defined; 2, ranking acceptability analysis indexes are calculated; 3, global acceptability analysis indexes are calculated; 4, a target allocation model is built; and 5, the obtained index result is substituted to the model, and the optimal allocation scheme is obtained. On the basis of stochastic multi-attribute acceptability analysis method, the target allocation model is brought forward, the multi-unmanned aerial vehicle target allocation decision making problem in an unclear interval information condition can be effectively solved, target allocation effects are improved, and needs of a real complex battlefield environment can be met.

The present invention discloses a digital PCR method and a detection kit for detecting HER2 copy number variation in breast cancer. The kit comprises at least one pair of primers and a matching probefor detecting HER2 gene copy number variation and a pair of primers and a matching probe for detecting internal reference gene. The method is conducted by using three sets of HER2 gene specific primerprobes and one set of internal reference gene, thereby effectively eliminating false negative results caused by amplification of a single primer probe. Therefore, compared with prior art, the methodhas higher accuracy, uncertainty interval of the prior art is reduced from (1.8-2.2) to (1.0-1.2), and the method has higher sensitivity.

The invention discloses an assembly gross error determination method and system. The method comprises obtaining a measured assembly deviation amount of an assembly matching surface; analyzing the variation range of the assembly deviation; performing finite element simulation on the variation range to obtain assembly deviation simulation data; removing a limit value in the assembly deviation simulation data, and obtaining confidence assembly deviation simulation data; grouping the confidence assembly deviation simulation data to obtain a plurality of assembly deviation simulation data sets; calculating the uncertainty interval of each assembly deviation simulation data set to obtain an assembly deviation qualified interval; fusing each assembly deviation simulation data set and a measured data set composed of the measured assembly deviation amount, to obtain a plurality of merging data sets; calculating the average uncertainty of all fused data including the same measured assembly deviation amount; and determining the measured assembly deviation amount corresponding to the average uncertainty outside the assembly deviation qualified interval. According to the technical scheme, the gross error recognition and screening accuracy can be improved.

The invention discloses a field end for assisting global positioning of an unmanned vehicle in a limiting scene. The field end comprises a plurality of semantic feature patterns which are different from each other, wherein the plurality of semantic feature patterns are arranged on at least one side of a traveling road of the unmanned vehicle in the limiting scene at a distance D according to a semantic cyclic code; the semantic cyclic code is formed by a plurality of code combinations, and the codes correspond to the semantic feature patterns in a one-to-one mode; a periodic sequence of the semantic cyclic code does not have ambiguity at a positioning uncertainty interval; the distance D is computed through a formula L=(D*(N-1)), wherein L is the length of a semi-major axis of the uncertainty interval, and N is the length of the periodic sequence. A vehicle end can be guaranteed to quickly complete global repositioning at the positioning uncertainty interval of the vehicle, the arrangement efficiency is high, the cost is low, and the operation and maintenance cost is low, the communication burden of the field end and the vehicle end is reduced, and the design difficulty of a three-end integrated system is simplified.

The invention discloses a segmented type P code capturing method, which comprises the steps of segmenting P code uncertainty time, acquiring a current captured satellite number m and a current captured channel index number I, calculating a signal transmitting moment of a current captured satellite, setting capture parameters and starting a capturer, reading a capture peak value returned by the capturer and judging whether the capture is success. Through segmenting the P code uncertainty time, respectively calculating the signal transmitting moments of satellites, carrying out correlation operation through the capturer and capturing P code signals, the segmented type P code capturing method effectively solve the problems that the PRM placement time error is large, the capture is difficult and large amounts of correlator resources are occupied during P code capture. The invention further discloses a segmented type P code capturing device, which comprises an uncertainty interval segmentation module, a satellite number acquisition module, a captured P code time calculation module, a capturer setting module and a capture peak value threshold judgment module which are connected in sequence, and is an accurate, simple and effective capturing device designed for a satellite receiver.

The invention belongs to the technical field of mechanical dynamics, and particularly relates to an uncertainty analysis method for frequency response function of a hoop-pipeline system. The method comprises the following steps: A1, establishing a finite element model of a hoop-pipeline system based on a beam element model and a spring model; A2, taking the pre-obtained uncertain interval of the hoop rigidity as an interval variable, applying the interval variable to a finite element model in the hoop-pipeline system, and obtaining the uncertain interval of the frequency response function of the hoop-pipeline system by utilizing a Chebyshev polynomial approximation method. The uncertainty interval of the frequency response function of the hoop-pipeline system obtained by the method is highin accuracy and high in efficiency.

The invention discloses a conflict evidence combination method based on weighted correction in order to solve the problem that a plurality of evidence combinations containing conflict evidences are inversely intuitive. The method comprises the following steps: firstly, determining a representation method of an uncertain interval, and then according to the uncertain interval, giving a new intervaldistance calculation method based on a focal element reliability and a likelihood function; secondly, calculating interval distances among the focal elements with the same evidence, and summing to generate a distance matrix among all the focal element evidences; then, generating weights among the evidences through the distance matrix, and correcting the original evidences according to the weights;finally, completing new evidence combination through the DS and the PCR6, and the method is suitable for multi-evidence and multi-conflict situations in engineering.

The invention discloses a method for calculating a data message transmission reliability lower limit of a FlexRay bus network with incomplete information. The method comprises the following steps: (1) determining corresponding change intervals, which are shown in the description, of respective mean values and variances of three variables, namely, blocking time T, transmission delay T<f> and software system processing delay T<s> of a data message in a source node according to measurement results of the three variables; (2) determining reference probability distribution f<T> of a sum T=T+T<f>+T<s> of the three delay variables T, T<f> and T<s>; (3) calculating maximum cross entropy R<max> of T=T+T<f>+T<s> and the corresponding reference probability distribution in uncertain intervals of the mean values and the variances of the three delay variables T, T<f> and T<s>; (4) determining a communication deadline W<m> according to a real-time requirement of the message in the FlexRay network, and further determining a message transmission reliability function; and (5) calculating a communication reliability lower limit P<l> of the message according to the message transmission reliability function. Through adoption of the method provided by the invention, communication reliability of different messages in one FlexRay network can be calculated rapidly and accurately, and a reliable basis is laid for the design of a FlexRay-based network control system.