34 results about "Law of total probability" patented technology

The invention provides a Copula function-based multivariate hydrologic uncertainty processing method. The method can be used for hydrologic forecasting, and is characterized by comprising the following steps: step 1, collecting hydrometeorological basic data and quantitative precipitation forecast data of a basin; step 2, establishing a hydrologic model to obtain forecast discharge processes of different forecast periods; step 3, determining marginal distribution functions of actually measured flow and forecast flow; step 4, utilizing a Copula function to construct a joint probability distribution function of the actually measured flow and the forecast flow; step 5, solving a Bayesian posterior transition probability density function of the actually measured flow of the different forecast periods according to the marginal distribution functions estimated in the step 3 and the joint probability distribution function constructed in the step 4; and step 6, acquiring a Bayesian posterior joint probability density function of the actually measured discharge processes through a total probability formula according to the Bayesian posterior transition probability density function, obtained in the step 5, of the actually measured flow of the different forecast periods.

The invention discloses a risk assessment based intelligent navigation method and device, equipment and a storage medium. The risk assessment based intelligent navigation method includes acquiring a route and navigation request sent from a client side, acquiring multiple original navigation routes according to starting location and target location of the route navigation, further acquiring to-be-assessed traffic data corresponding to each navigation route, performing rick assessment on the to-be-assessed traffic data corresponding to each navigation route through a road rick identification model trained in advance to acquire section risk probability of the corresponding road sections, acquiring the total risk probability corresponding to the original navigation routes according to the section risk probability of at least one corresponding navigation road section of each original navigation route, and finally determining the original navigation route with the lowest total risk probability as a recommended navigation route and sending the recommended navigation route to the client side. The risk assessment based intelligent navigation method can realize route planning based on safetyfactors, thereby guaranteeing safety in driving.

The invention discloses a same-tower multi-loop transmission circuit risk probability assessment method, comprising the following steps of: assessing each external risk value of a same-tower multi-loop transmission circuit through a statistical analysis method; modeling in a combined manner, and assembling each internal risk value of the same-tower multi-loop transmission circuit by combining the statistical analysis method; and accessing a total probability risk index value by combining each external risk value and each internal risk value according to a total probability formula. The same-tower multi-loop transmission circuit risk probability assessment method provided by the invention can be comprehensively and entirely realized, and reliable parameter estimation and reasonability analysis can be carried out by operating statistical data through a power transmission and transformation facility with national and local calibers, so that a rigorous mould principle, reasonable parameters and a credible assessment result can be realized. The invention provides a probability risk assessment method in a super-grid popularization same-tower multi-loop technology, and provides quantitative reliable assessment and engineering auxiliary criterion for the super-grid popularization same-tower multi-loop technology.

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 relates to a rapid analysis method for landing safety probability of a lunar probe. The rapid analysis method comprises the following steps: simulating landing of a lander on slopes of different angles to obtain slope threshold capable of turning over the lander; combining lunar surface landform models and detected data of Chang'e 2 to generate lunar surface landform models; dividing the lunar surface landform models into K landform models according to different slopes; performing N landing simulation experiments on each lunar surface landform model; analyzing according to the lunar surface data obtained by the Chang'e 2 to obtain a proportion Ci occupied by the slope ki in the lunar surface landform model; calculating a preliminary landing safety probability analysis result according to a full-probability formula. By using the technical scheme provided by the invention, a selection basis can be provided for a specific location for landing the lander on the lunar surface.

The embodiment of the invention provides a video semantics labeling method based on a bullet screen. The method includes: obtaining all words in the bullet screen of a target video and corresponding time stamps; averagely dividing the target video into a preset number of time slices; generating an initial topic set, which contains topics corresponding to all the time slices, and an initial plot set, which contains plots corresponding to all the time slices, according to preset probability correspondence relationships of words and the topics and the plots; generating a dictionary vocabulary setand a vocabulary distribution matrix; calculating temporal a priori information of the dictionary vocabulary set; using a preset total probability formula of bullet-screen vocabulary to calculate probability that each piece of the dictionary vocabulary corresponds to each topic and each plot; generating plot-topic distribution matrices of the time slices; merging adjacent similar time slices intoone time slice; determining plots corresponding to all time slices; and labeling the target video. By applying the scheme provided by the embodiment of the invention for video semantics labeling, labeling on video semantics is enabled to be more accurate.

The invention relates to a cytogene translation process modeling method. The cytogene translation process modeling method comprises the following steps: tracking a state of each mRNA (Messenger Ribonucleic Acid) molecule and updating a count in real time to obtain the quantity of mRNAs which can be initialized among various mRNAs; tracking a state of each ribosomal molecule and updating a count in real time to obtain the quantity of ribosomes which can be moved on various mRNA sites; calculating a total initialization speed of the mRNA molecules; calculating a total extension speed of the ribosomal molecules on the corresponding mRNAs; obtaining a total probability of mRNA initialization and ribosome extension according to the total initialization speed and the total extension speed; randomly selecting an event according to the weight of an event probability to carry out a response; after the response is ended, updating a cell state. According to the cytogene translation process modeling method disclosed by the invention, the possibility of error translation is considered while a correct translation is considered by adopting a principle based on a totally asymmetric simple repulsion process and by considering the half-life period of molecules at the same time, such that the translation process is closer to the essence of the biological problem.

The invention discloses a high-precision indoor wireless positioning method. The method comprises the following steps: A, obtaining distances from all N anchor nodes to a measured node and coordinates of the anchor nodes at a moment t; B, mining spatial correlation of adjacent moments through Kalman filtering, defining Kalman state equation coefficients on three coordinates of x, y and z at the moment t, and summarizing vectors and matrixes at all moments into a specified set form; C, performing factor decomposition on the global probability distribution by utilizing a total probability formula and a Kalman state equation; D, modeling by utilizing the factor decomposition obtained in the step C, and dividing the factor graph model into a lattice network part, a Kalman network part and a Kalman parameter estimation part; and E, carrying out message calculation on the lattice network part, the Kalman network part and the Kalman parameter estimation part through a message transmission algorithm. According to the method, the high-precision position information of the indoor to-be-tested node can be obtained efficiently and accurately.

The invention discloses a battery safety degree estimation method based on a naive Bayes theory, belongs to the field of battery safety degree estimation, and aims to solve the problem that the safetyof a battery cannot be visually quantified and displayed in the prior art. The method comprises the following steps: classifying battery working data, then establishing a naive Bayesian network, anddividing nodes in the network into father nodes, child nodes and intermediate nodes according to the relationship between the nodes and the nodes; etablishing a training set to solve the conditional probability of the occurrence of the intermediate node or the child node and the prior probability of the occurrence of the child node under the condition that the father node occurs; screening out a characteristic factor most related to the battery fault according to the prior probability; calculating a posterior probability according to a naive Bayes theorem and a total probability formula; and establishing a safety degree comparison table according to a naive Bayes classification principle and displaying the safety degree comparison table.

The invention discloses a risk probability assessment method for a power distribution line based on historical factor analysis, and the method comprises the following steps: (1), determining key factors for the assessment of the risk probability of the power distribution line; (2), respectively building a probability calculation model of the countable key factors and a probability calculation model with the key factors causing the tripping of the power distribution line; (3), respectively a calculation model for assessing the risk probability of the power distribution line for the uncountablekey factors; (4), calculating the risk probability, corresponding to each key factor, of the power distribution line according to the calculation models at steps (2) and (3), and then calculating theoverall risk probability of the power distribution line of an assessed region according to a total probability formula. The method is high in accuracy, provides a decision making basis for the risk assessment of the power distribution line, can achieve the estimation of the risk probability of the power distribution line in one region, and also can achieve the assessment of the risk probability ofone power distribution line according to the actual conditions.

The invention discloses a combined sampling method for evaluating the reliability of a power system. On the basis of the combined sampling method with equal-dispersed sampling and total-probability-formula sampling, a reliability index of a system is evaluated; one group of system elements are selected to apply the total probability formula and the equal-dispersed sampling method is applied to the rest elements of the system. The combined sampling method comprises the following steps: inputting original data and selecting one group of elements according to an importance degree principle; enumerating component events and corresponding probabilities of the selected system elements, carrying out equal-dispersed sub zone sampling on the rest elements of the system and carrying out combination with the events to form a system state; and calculating the state in each equal-dispersed sub zone, calculating a sample variance, carrying out multi-times cyclic sampling till meeting of a set requirement by the sample variance, and outputting a result. With the combined sampling method having the equal-dispersing method and the total probability formula method, the sample variance, the sampling number of times, and the calculation time are reduced; the sampling efficiency is improved; and the precision is enhanced.

The invention provides a method for solving the steady state probability of a polymorphic system under a general distribution, which can establish a system state equation for a system of arbitrary distribution and give a method for obtaining the steady state probability of the system. The transition of system state is described as a generalized Markov process by using the supplementary variable method, and the state equation of the system is transformed into an ordinary differential equation according to the characteristic that the system state does not change according to the absolute time inthe steady state. Combined with the boundary conditions and initial conditions of the system, the equations are solved preliminarily, the important parameters of the system state equation are extracted by using the generalized integral mean value theorem, and the system state equation is transformed by means of the equivalence relations among the parameters. The generalized probability equation is obtained by using the total probability formula and solved by using the least square method. This method can significantly reduce the difficulty of obtaining the steady-state solutions of state probabilities of multi-state systems and has certain universality. It is suitable for solving the problems of system state analysis and maintenance strategy optimization in the fields of reliability engineering and mechanical engineering.

The invention discloses a flood probability forecast method based on an error transfer density function. According to the method, a flood forecast historical database is constructed, a variation function of forecast error statistical characteristic values according to forecast flow is analyzed according to the historical database, the transfer density function of forecast errors is solved based ona forecast error first-order autoregressive hypothesis, and a distribution function of the forecast errors is solved through a total-probability formula. At last, the distribution function solving law of a random variable function is adopted to solve a distribution function of a forecast quantity. In this way, a flood probability forecast is realized, and flood forecast uncertainty is quantified.The method is applied to the flood probability forecast of a certain station, and it is verified by a data result that the flood probability forecast can be effectively realized through the method.

A method of rapidly producing a new cyber response tool (e.g., in near-real-time) by matching vulnerabilities of enemy threats (e.g., a missile and/or a tank) to corresponding portions of other response tools that effectively exploit the matched vulnerability. An iterative framework may be utilized to repeatedly prioritize a set of cyber response tools based on a corresponding probability of success. For example, a computer or computer network may implement the iterative framework to carry out the probability computation and corresponding cyber response tool prioritization. If a total probability of success is below a given threshold (e.g., 95%), then creation of one or more new cyber response tools may be initiated. The probability of success may be a function of time (e.g., ten minutes before an expected launch) and/or a function of a phase of a lifecycle of the enemy threat (e.g., a launch phase).

The invention discloses a method for predicting heavy overload of a distribution transformer. The method comprises the following steps: acquiring historical data of heavy overload of a transformer area; according to the historical data of the heavy overload of the transformer area, determining characteristic variables influencing the heavy overload of the distribution transformer; determining the influence proportion of each characteristic variable; analyzing the historical data of the heavy overload of the transformer area to obtain a danger set value of each characteristic variable; according to the historical data of the heavy overload of the transformer area, obtaining the probability that the heavy overload occurs when each characteristic variable reaches a dangerous set value; according to a Bayesian rule, determining the probability of heavy overload when each characteristic variable reaches a dangerous set value; by monitoring each characteristic variable, acquiring the probability of heavy overload of the distribution transformer according to a total probability formula. Through the data integration platform based on the power grid big data, the real-time distribution transformer heavy overload probability is analyzed by using the statistical principle and probabilistic analysis, so that the risk of distribution transformer heavy overload is prevented, and the safety and economic benefits of power equipment operation are improved.