241 results about "Random simulation" patented technology

A method, computer program product, and computer system for configuring a stochastic simulation scenario, wherein the stochastic simulation scenario may include one or more variables without a complete probability distribution. The stochastic simulation scenario may be executed to generate one or more results of the stochastic simulation scenario. At least a portion of the one or more variables without the probability distribution may be optimized using one or more optimization metrics on the one or more results of the stochastic simulation scenario.

System, methods, and apparatus for verifying microcircuit designs by interleaving between random and formal simulation techniques to identify input traces useful for driving designs under test into sequences of device states. In a method aspect the invention provides process for beginning random simulation of a sequence of states of a microcircuit design by inputting a sequence of random input vectors to a design under test model in order to obtain a sequence of random simulation states; monitoring a simulation coverage progress metric to determine a preference for switching from random simulation to formal methods of simulating states in the design under test; beginning formal simulation of states in the design under test and monitoring a formal coverage progress metric to determine a preference for resuming random simulation of states of said microcircuit design; and resuming random simulation. Preferably the process of interleaving simulation methods continues until an input vector suitable for driving the design under test model into each of a set of previously-identified goal states has been obtained.

The present invention discloses a multi-year regulating storage reservoir optimal scheduling method considering runoff uncertainty. The method comprises the following steps of: (1) analyzing historical reservoir runoff data; (2) establishing a runoff random simulation model, and generating a reservoir simulation annual runoff sequence; (3) simulating annual inflow runoff sequence classification and performing intra-annual distribution to obtain a three-year inflow runoff process sequence on a month scale; (4) establishing a multi-year regulating storage reservoir optimal scheduling model that considers multiple water demands; and (5) reducing dimension by using an optimization algorithm and optimizing a resolution model so as to obtain an optimal discharging and water supply decision. According to the method provided by the present invention, the scheduling with maximized comprehensive benefits of long-term multi-target operation can be performed on a multi-year regulating storage reservoir by considering runoff uncertainty, so that the method is suitable for promotion in long-term optimal scheduling of the multi-year regulating storage reservoir in China.

The invention provides a carbonate rock physical parameter seismic inversion method, which belongs to the field of petroleum geophysical exploration. The method comprises the following steps: (1) carrying out pre-stack AVO three-parameter inversion based on a pre-stack angle gather to obtain formation elasticity parameters M, wherein M includes P-wave velocity, S-wave velocity and density; (2) establishing a statistical rock physical model based on logging data; (3) randomly simulating physical conditions of a reservoir based on the rock physical model obtained from step (2) to obtain a random simulation result; and (4) carrying out Bayes classified simulation on the random simulation result obtained from step (3) to obtain a posterior probability distribution, and taking the M obtained from step (1) as the input of inversion to find a R with the maximum posteriori probability distribution, wherein R is the final inversion result.

A method, system, and data structure for incorporating random instrumentation logic within a simulation model. The data structure of the present invention includes a first field containing data representing an assigned target and a second field containing data representing a logic value to be assigned to the assigned target. The first field and the second field are incorporated within a comment line of a design target entity source code file. A pre-pended comment identifier field identifies the data structure as a hardware description language comment.

The invention discloses a noise parameter measurement uncertainty evaluation method based on a multi-chip module (MCM) and belongs to the field of measurement metering. The method includes utilizing an equivalent noise parameter equation as a measurement model for noise parameter measurement uncertainty evaluation, utilizing physical quantity measured from a measurement platform to calculate the function equation and obtain data reflecting equivalent noise parameter distribution condition, leading out noise parameter and noise parameter distribution from the equivalent noise parameter and finally obtaining uncertainty for noise parameter measurement. The method effectively combines digital random simulation, physical measurement boundary criterion and least square method optimization criterion, and enables noise parameter uncertainty evaluation to be effective, real and reliable. The method satisfies the national standard, and is flexible in simulation mode, multiple in applicable measurement system variety and strong in universality.

The invention discloses an energy scheduling method for a microgrid, which is characterized by including adopting the Monte Carlo method to conduct stochastic simulation on uncertainty factors in operation of the microgrid to generate samples formed by output power of a power supply with renewable energy sources and the like; providing the confidence level of load satisfying rate of the microgrid, setting rotating reserve probability constraint condition of the microgrid and forming a target function of microgrid energy scheduling in minimum mode through planning operation cost of energy scheduling time periods of the microgrid; designing energy scheduling algorithm combining the stochastic simulation in the Monte Carlo method and genetic algorithm to conduct solution of the target function of microgrid energy scheduling to obtain the optimum energy scheduling scheme of the microgrid. The energy scheduling method achieves balance between operation economical performance and operation reliability of the microgrid and meets actual operation requirements of the microgrid by setting the confidence level of the load satisfying rate of the microgrid, introducing the rotating reserve probability constraint condition of the microgrid and processing various uncertain factors in the microgrid.

The present invention discloses a tight sandstone reservoir modeling method. The tight sandstone reservoir modeling method comprises the steps of: taking drilling and logging information as constraints to perform lithology inversion based on post-stack three-dimensional seismic interpretation data to obtain a plurality of inversion data volumes; comparing the inversion data volumes with a logginginterpretation conclusion to optimize an inversion data volume which can most reflect different lithologies; determining a lithology partition criterion according to the dependency of lithology data interpreted from the logging and the values in the optimized inversion data volumes; obtaining a three-dimensional logging lithology data volumes through lithology identification of the values of the inversion data volumes in each three-dimensional grid in the three-dimensional space based on the lithology partition criterion; setting virtual wells at the main body centers of sedimentary facies andthe internal portion of each boundary, and determining the values in the three-dimensional lithology data volumes corresponding to the virtual wells as the lithology data of the virtual wells; and taking the lithology data of the actual drilling wells and the virtual wells as modeling basic data to perform random simulation modeling to obtain a three-dimensional reservoir lithology model so as toachieve the purpose of fine description of the reservoir.

In a finite state machine (FSMverify) a set of goal states, to be searched for their reachability from a start state, is defined.An overapproximated path is found from a start state to a goal state by a forward approximation technique. The overapproximated path representation relies upon a partitioning of the state and input bits of FSMverify. A state matrix of the overapproximated path is organized by time-steps of FSMverify along a first dimension and by partitions of FSMverify state bits along a second dimension.An underapproximated path, along the path of the stepping stone matrix, is determined. Underapproximation is typically accomplished by simulation.A sequence of states to be output is updated with the underapproximated path.If a start to goal state sequence has been found, the procedure ends. Otherwise, the above steps of over and under approximation are repeated, using the results of the last underapproximation as a start state.

The invention relates to a design method for a multi-target cooperative sampling scheme of randomly-distributed geographic elements, which includes the steps: 1 selecting multiple geographic elements with random distribution characteristics as sampling targets, and acquiring pre-sampling sample point data of the targets; 2 exploring spatial variation structures of the pre-sampling data by an ordinary Kriging method, fitting and generating a theory semi-variable function of each target, and obtaining a spatial distribution integral of all the targets by a Gaussian sequential random simulation method according to the theory semi-variable functions and the pre-sampling sample point data in the step 1; 3 computing the minimum cooperative sample size according to the precision requirements of the targets and prior variance, and setting a cooperative particle swarm optimization parameter; and 4 optimizing a current pre-sampling sample point scheme by means of cooperative particle swarm optimization, so that the multi-target cooperative sampling scheme is obtained. By the aid of the method, on-site sampling cost can be saved, self-organization and optimization during distribution of thesampling sample points are improved, and the design efficiency of the multi-target cooperative sampling scheme of the geographic elements is enhanced.

The invention provides a method for seeking a weak link of an electric network causing voltage sag, which comprises the following steps: recording voltage sag events and electric network faults; calculating a user voltage sag amplitude expected value and the fault probability of each place; establishing a random analog computation model; performing random analog computation to calculating the user voltage sag amplitude expected value; comparing a computing result and a statistic result; changing fault probabilities of different places, and calculating the voltage sag amplitude expected value; and calculating indexes of the weak link of the electric network, comparing the indexes, and obtaining a result. The method starts from identifying a fault place of the electric network which easily causes the voltage sag events, provides calculation of the indexes of the weak link of the electric network, combines two factors of the fault probability of the electric network and a user voltage sag amplitude caused by the fault, and accurately identifies the fault place of the electric network which easily causes large voltage sag amplitude of the electric network so as to provide priority selection basis for planning and establishment, daily maintenance and technical reformation of the electric network.

A circuit for generating chaotic signals implemented using heterojunction bipolar transistors (HBTs) and utilized in low probability intercept communications. The HBT chaotic circuit generates truly random analog signals in the GHz range that are non-repeating and deterministic and may not be replicated by preloading a predetermined sequence. A fully differential autonomous chaotic circuit outputs two pairs of chaotic signals to be used in a communication system. As it is impossible to generate identical chaotic signals at the transmitter and receiver sites, the receiver itself sends the chaotic signal to be used for encoding to the transmitter. The receiver includes a chaotic signal generator and digitizes, upconverts, and transmits the generated chaotic signal to the transmitter. The transmitter uses the received chaotic signal to code data to be transmitted. The receiver decodes the transmitted data that is encoded by the chaotic signal to retrieve the transmitted data.

A method for processing seismic data. The method includes performing a plurality of stochastic simulations for one or more rock model parameters to generate one or more anisotropic parameters for a subsurface area of the earth. The method then derives one or more joint multi-dimensional probability density functions for the anisotropic parameters. Using the joint multi-dimensional probability density functions and measured well log data, the method computes one or more posterior probability density functions. The method then includes deriving one or more anisotropic profiles from the posterior probability density functions and generating a seismic image from the anisotropic profiles.

The invention provides a partial discharging positioning method based on time delay error stochastic simulation and statistic analysis. The partial discharging positioning method comprises the following steps that firstly, four time delays needed by positioning are obtained according to the generalized cross-correlation algorithm based on a set of waveforms received by a quaternary ultra-high frequency antenna array; secondly, the time delay error range is set with the time delays as base points, n sets of time delays are simulated in the time delay error range in a random mode, random functions are distributed in a normal mode, and the time delays worked out in the first step are adopted in the center; thirdly, the two-dimensional positioning information of a discharging source is calculated according to the n sets of time delays, and a direction angle distribution diagram is obtained; fourthly, the angle with the maximum angle distribution probability is set to be the positioning angle according to the statistical analysis method; fifthly, a search area is spread with the positioning angle as the center, grid searching is carried out, and the positioning angle and the radial distance of the discharging source are calculated. The partial discharging positioning method based on time delay error stochastic simulation and statistic analysis can improve the accuracy of partial discharging positioning.

The invention provides a multipoint geologic statistics method based on geologic vector information. The multipoint geologic statistics method based on the geologic vector information comprises the steps that vectorization partition is conducted on a training image and a modeling area, so that multiple stable sub-blocks are obtained, stochastic simulation is conducted based on comprehensive geologic research achievements, the problem that according to a multipoint geologic statistics modeling method in the prior art, the instability of a training image and condition data is hard to overcome is solved, the reliability and rationality of a geologic model are effectively improved, and the method can be widely applied to the fields such as the geological exploration field, and the environmental monitoring field.

The invention relates to a meteorological-energy-contained integrated energy system typical scene set generation method, and belongs to the technical field of electric power system operation and analysis. The meteorological-energy-contained integrated energy system typical scene set generation method is characterized in that modeling is performed on the meteorological correlation based on a Copula function theory and a Latin hypercube sampling theory; the correlation between meteorological variables is fully considered; the algorithm can significantly improve accuracy of random production simulation of the meteorological variables; and an optimal quantile theory based on Wasserstein distance is used to perform discretization on randomly simulated continuous variables to obtain a small number of integrated energy system typical scene sets. In the meteorological-energy-contained integrated energy system typical scene set generation method, the optimal quantile theory can generate extreme scenes and can greatly improve the calculating precision. The optimal quantile theory utilizes the discrete variables to enable the meteorological-energy-contained integrated energy system typical scene set generation method to be distinguished from other existing research results. The generated typical scene sets can help an operator to analyze the problem brought to operation and planning of the integrated energy system by nondeterminacy, and the analysis result of typical scenes can provide support for safe and stable running of the system.

The invention discloses a disease concrete bridge bearing capability evaluation method, which supposes various uncertainties influencing disease concrete bridge bearing capability evaluation to possess random variables of certain probability distribution characteristics, and defines disease index influence degrees to a bridge bearing capability as bearing capability partial checking computation coefficients according to a bearing capability calculation method. Based on an actual disease index detection result and mathematical statistics, the method employs monte carlo random simulation calculation and a fuzzy comprehensive evaluation principle to obtain a probability distribution characteristic approximating the disease concrete bridge bearing capability to be evaluated, an furthermore obtain a bearing capability evaluation result possessing a certain probability guarantee. The method overcomes the uncertainty influences caused by neglecting randomness of various factors and fuzzyness of evaluation grade division in a present highway bridge bearing capability evaluation standard, thereby realizing more scientific and rational evaluation results.

The invention provides a communication network robustness assessment method based on a complex network and in combination with big data. A communication network is abstracted into the complex networkthrough building a communication network model; a data mining algorithm is used for processing fault data; simulation modeling is performed on the model, analysis data is loaded into a simulation platform, a forwarding capacity, a caching capacity and a forwarding load are set and adjusted, and a routing strategy is changed, and thus a truer, more reliable and more accurate simulation assessment result is acquired. The network model of a real world complex system is built based on a complex network technology, system performance such as robustness, security and reliability are assessed and anoptimization scheme is provided by using a random simulation technology and operation and maintenance big data of the system; a cascade spreading and diffusion problem after a fault occurs in the communication network is found, weak links, including fault equipment and a fault spreading path, affecting the security and reliability of the whole network are found, and the optimization scheme is further provided based on a network topological structure.

The invention relates to the technical field of wireless communication, in particular to a task unloading and resource allocation method in an uncertain network environment, which comprises the following steps of: modeling a task unloading process into a two-stage unloading model, and optimizing the model into a task unloading and resource allocation problem based on two-stage stochastic programming; adopting a random simulation method for converting the problem into a sample mean value approximation problem, and decoupling the problem into a local computing resource allocation sub-problem, a transmission power and edge computing resource joint allocation sub-problem and an unloading decision sub-problem; solving three sub-problems by adopting a standard Lagrangian multiplier method, a genetic algorithm and time delay estimation and energy consumption budget for analyzing local calculation and edge calculation; and enabling a user to obtain an optimal allocation strategy for task unloading by solving the three sub-problems. According to the method, the requirement of task calculation delay in a network with uncertain delay can be met, and meanwhile, the energy consumption of the system is minimized.

The invention relates to an active distribution network fault recovery method with consideration of random variation of distributed power supply outputs. The method is characterized by comprising thefollowing steps: step one, carrying out active distribution network island division based on a depth and breadth alternate joint strategy; and step two, on the basis of comprehensive consideration offault recovery whole-period flow changes, carrying out active distribution network reconstruction optimization by using a low-offset stochastic simulation method. Therefore, the maximum output of theDG is utilized fully and loads are recovered as many as possible; and uninterrupted power supply of important loads is ensured.

The invention discloses an energy-saving risk probability considered provincial power grid electricity purchasing decision making system. The system comprises a power plant tradable electricity quantity input unit, a random risk probability environment simulation unit, an electricity purchasing scheme generating unit and an electricity purchasing cost and energy-saving risk probability output unit. An electricity purchasing model is built inside the system, and a provincial power grid electricity purchasing scheme is obtained. According to the energy-saving risk probability considered provincial power grid electricity purchasing decision making system, the network loss factor of market transactions in an energy-saving electricity market is considered, and unit transaction electricity quantity energy-saving benefit evaluation indexes are built; with the reference of the probability risk concept, the market price, hydropower unit electricity quantity generation and randomness of system load electricity quantity requirements are considered, power grid company market electricity purchasing energy-saving risk probability indexes are built, an energy-saving risk probability considered provincial power grid electricity purchasing model is built in a randomly-planned theoretical framework for achieving optimization management of power grid company market electricity purchasing energy-saving risks, and a genetic algorithm with the dominant embedded target and the Monte-Carlo random simulation technology is adopted for solution.

The invention disclose a full voltage sequence integrated power grid reliability and risk evaluation method, belonging to the technical field of power system reliability analysis. Based on the real-time data calculation of the power grid and depending on the advantage of online safety and stability analysis and calculation, the method provided has the advantages of reliable calculation result and quick calculation speed and effectively reduces the problems of large data bulk and long time consumption of calculation caused by the random simulation of a conventional sampling algorithm. Through the information exchange between the transmission and distribution network reliability evaluation systems, the integrated evaluation of the full voltage sequence power grid can be carried out, and thus greatly improving the accuracy of the power grid evaluation, and overcoming the defects of inaccurate evaluation result and repeated evaluation due to the isolation of power grids in different voltage grades; the risk evaluation and prevention and control decisions of the real-time operation of the power grid take into account the power generation / load reduction cost, so that the balance of the reliability and economy of the real-time operation of the power grid can be solved. The method greatly promotes the engineering application of the large power grid in the reliability evaluation and management technology.

The invention provides a stochastic simulation method for geologic risk evaluation, which belongs to the field of uncertainty evaluation of oil and gas resources. The stochastic simulation method comprises the steps of: (1) determining evaluation parameters; (2) fuzzifying the evaluation parameters and establishing a fuzzy rule; (3) carrying out fuzzy logic calculation on each evaluation parameter to obtain geologic evaluation result of each evaluation parameter; (4) quantifying score results, namely, acquiring final quantified results of geologic risk evaluation from the geologic evaluation results obtained in step (3) through a defuzzification manner; (5) selecting a random data generator; (6) selecting a probability distribution model; (7) and acquiring Monte Carlo simulation results. The simulation results obtained by utilizing the stochastic simulation method for geologic risk evaluation can well reflect the uncertainty in geologic evaluation, thereby greatly improving the decision-making capacity of the geological risk probability method.

One embodiment of the present invention provides a system which verifies a circuit design by biasing input stimuli for the circuit design to satisfy one or more temporal coverage properties to be verified for the circuit design. This system performs a simulation in which random input stimuli are applied to the circuit design. The system performs the simulation by using a finite state automaton (FSA) instance for a temporal coverage property to observe inputs and outputs of the circuit, and by using soft constraints associated with the FSA instance to bias the input stimuli for the circuit design so that the simulation is likely to progress through a sequence of states which satisfy the temporal coverage property.

The invention provides a method for calculating distributed photovoltaic grid connected maximum penetration level. The method comprises the following steps: S1, acquiring basic data of a power distribution system; S2, establishing a probabilistically distributed model by using photovoltaic output and load power consumption as random variables; S3, establishing a chance-constrained programming model of the distributed photovoltaic grid connected maximum penetration level by using the basic data, wherein the chance-constrained programming model comprises an objective function and a constraint condition; S4, sampling the probabilistically distributed model by a random simulation technology to generate sample data, and checking whether the sample data meet the constraint condition, if the sample data meet the constraint condition, carrying out the step S6, and if the sample data do not meet the constraint condition, carrying out the step S5; S5, numbering a penalty function into the objective function; and S6, carrying out global optimization on chance-constrained programming model by a genetic algorithm. By the method for calculating the distributed photovoltaic grid connected maximum penetration level, the distributed photovoltaic grid connected maximum penetration level can be calculated accurately for randomness and fluctuation of photovoltaic output and load power consumption.

The invention provides a probabilistic earthquake economic loss calculation method and system. The method comprises the following steps: selecting a seismic zone and a potential seismic source regioninfluencing a target region, and determining a seismic activity model and seismic activity parameters; generating a seismic event database through a Monte Carlo random simulation method; selecting anattenuation model, and calculating the seismic intensity of any field point in the target area according to the seismic directory library; calculating the economic loss of the target area according tothe seismic intensity and the macroeconomic vulnerability model; and calculating the earthquake loss occurrence probability of any field point in t years and the economic loss of the field point under the specified probability condition in combination with a large number theorem and a full probability formula. The system comprises a model and parameter determination unit, an earthquake event database generation unit, an earthquake intensity calculation unit, an economic loss calculation unit and an earthquake loss occurrence probability and loss calculation unit. The method considers that thefield points may suffer from the same intensity influence for many times, and provides technical support for earthquake loss prediction.

The invention discloses a method for quantificationally predicting gas containing probability through prestack automatic fault indication (AFI) inversion, which comprises the following steps of: using log information for carrying out trend analysis, carrying out random simulation on the probability distribution condition of n depth layer characterization parameters of a target layer section, and obtaining the random geology model in different depth positions through the random combination of different parameters; carrying out fluid replacement on each random geology model, obtaining the corresponding response of sandstone models in various fluid states and forming three different depth template patterns; and correcting amplitude versus offset (AVO) attribute points of the actual chemical mechanical polishing (CMP) gather data body, projecting the corrected actual data point results to the corresponding depth template patterns and obtaining the quantificationally predicted probability distribution of the gas containing probability. The method of the invention solves the problem of uncertainty of the AVO existing in the oil gas detection and belongs to a method of converting the uncertainty in the AVO analysis into the certainty of the gas containing probability distribution, and the accurate gas containing probability distribution is obtained through the quantitative inversion of the gas containing probability.

The present invention relates to a new random generation method of rainfall events. The method comprises the following steps: (1) segmenting rainfall events according to the definition of rainfall events, and extracting rainfall characteristics and rainfall course lines of the rainfall events; (2) randomly simulating rainfall eigenvalues based on the Copula method; (3) based on the K-Means clustering analysis method, classifying the rainfall course lines, and introducing the clustering effective discriminant method to optimize the optimal classification number of rainfall patterns; (4) according to the appearance probability of the rainfall patterns, using the converted Monte Carlo method to randomly generate the rainfall patterns; and (5) using the multi-step combination method to combine the randomly simulated rainfall eigenvalues and the rainfall patterns to reconstruct the rainfall events. According to the method provided by the present invention, the dependency between the rainfall capacity and the rainfall duration are taken into account, so that the simulation is more in line with the actual situation and the simulation precision is improved; different rainfall patterns are taken into account, so that the technical support is provided for the government to take different response tactics for water allocation and storage; and the sequence length of the rainfall events can be significantly increased.