66 results about "Poisson point process" patented technology

The invention provides a heterogeneous cellular network base station deployment method based on a Poisson cluster process. The method comprises the following steps: on the basis of a random geometry theory, according to a hypothetical system model and adopting an instantaneous SINR cell selection mechanism as a cell selection mechanism of a user, deducing an SINR model based on the Poisson cluster process; carrying out analysis and inference on an interference model of a multi-layer heterogeneous cellular network by utilizing characteristics of the Poisson cluster process and a probability generation function thereof to obtain an interference distribution model; with the SINR model and the interference distribution model being combined, deducing a coverage probability model of the multi-layer heterogeneous cellular network; and carrying out simulated comparison and analysis on difference of coverage probabilities of the Poisson cluster process and a Poisson point process. The method is much closer to real communication scenes, is larger in coverage probability, can analyze coverage probability and throughput capacity better, and is of great importance in study of the heterogeneous cellular network in the future.

A system and method for detecting network intrusions using one or more statistical models and a generalized likelihood ratio test (GLRT) is provided. The system includes a computer system and a network intrusion detection engine executed by the computer system. To detect network intrusions, the system receives network traffic data, computes a likelihood using one or more statistical models, such as an Markov-modulated Poisson process, and processes the traffic data using a GLRT. The statistical models are used to assess the likelihood of seeing a particular pattern of network traffic. The GLRT is used to classify a particular pattern as either indicative of an attack or not indicative of an attack. The system could apply one or more types of statistical models, such as in a flexible multi-tiered approach.

The invention discloses a method for calculating an optimal cooperation distance of a D2D fusion network based on file popularity. The method comprises the following steps: cell user movement is modeled as random distribution in a spatial Poisson point process, each user caches a video file, the user can obtain the video file by selecting a cellular mode or a D2D mode, the popularity of the video file is simulated by Zipf distribution, a user number ND2D activated by D2D and the user number NBS activated in the cellular mode in a single cell are obtained according to different features of D2D and cellular communication, then a single user obtains the network capacity of the fusion network by the average throughput in the D2D mode and the cellular mode, and a specific application scene and a service demand are obtained by an existing fast iterative algorithm, so the D2D fusion network obtains an optimal cooperation distance d* with the maximum throughput.

The invention relates to a method for predicting the remaining life of high-reliability equipment under competing failure conditions. The fault mode causing failure of the equipment is considered as a combination of two modes including the slow variation fault mode described with a Wiener model with drift and the abrupt fault mode described with the Poisson process. Supposing that the two fault modes are independent of each other, and the remaining life of the equipment can be acquired after the remaining lives of the equipment in the two fault modes are acquired respectively. The method specifically includes the steps of constructing a dynamic performance degradation database, establishing an equipment performance degradation model under the competing failure conditions, estimating model parameters and predicting the remaining life. With the method for predicting the remaining life of the equipment, the individual life characteristic quantities of the equipment can be predicted and analyzed, power theoretical bases and technological support are provided for the maintenance guarantee of the equipment, and the method has very good engineering application prospects.

The invention provides a Poisson-process-model-based method for predicting the event popularity in a social network. The method comprises the steps as follows: Step 1, selecting a sample event, and obtaining a micro-blog propagation chain of the sample event; Step 2, performing user influence calculation, screening users with the strong influence as critical users, and marking the rest users as non-critical users; Step 3, modeling micro-blog forwarding processes brought by the critical users as a Poisson process model, and simply processing micro-blog forwarding processes brought by the non-critical users; Step 4, learning and estimating parameters of the Poisson process model of the critical users and parameters of the non-critical users by the aid of information of the sample event; Step 5, giving a new event with evolution information in certain duration, and predicting the popularity of the new event at a certain moment in the future according to the model in Step 3. By the aid of the method, the better popularity prediction can be provided at the initial stage of a micro-blog event, and very effective help can be provided for reasonable guidance of development of the event.

The invention discloses a new reliability model of a multi-degradation process and a stochastic impact competition failure system. It is assumed that random shocks obey homogeneous Poisson process, and the probability that the shocks are fatal and non-fatal is p (t) and q (t), respectively, where once the fatal shocks occur, the system will invalidate immediately; non-lethal shocks can have an impact on the degradation process, on the one hand,phase step degeneration increase will be increased, on the other hand, it will increase the degradation rate, and its effect is reflected by cumulativedamage. On this basis, by modifying the existing nonlinear Wiener process degradation model, the effect of non-lethal shock on degradation is considered, and the final system reliability function is established by time-varying Copula function. Finally, a numerical example is given to illustrate the mathematical model proposed in this paper.

The invention provides an energy-saving base station dormant method for a heterogeneous cellular network. An optimal base station dormant scheme is adopted according to the outage probability of a system and uplink transmitting power of a user. Macrocells, microcells and picocells are deployed in the poisson point process in a three-layer heterogeneous cellular network scene, and the outrage probability of the system and the uplink transmitting power of the user are derived according to a random geometric theory; a system power consumption optimization problem is solved, a part of the macrocells start a dormant state, the microcells and the picocells are added, the transmitting power of the macrocells is adjusted, and accordingly, the maximum system power consumption gain is obtained.

The invention belongs to the technical field of user accessing to a super-dense heterogeneous cellular network, and discloses a coverage and data plane separated super-dense heterogeneous cellular network user access method. The method comprises the following steps: building a microcellular base station system model based on a Poisson cluster process; assisting, by multiple micro base stations distributed around the same hotspot, a user in access service; building a macro base station system model based on a Poisson point process; on the premise that a macro base station is mainly used for completing a coverage function and the micro base stations are used for high-rate data transmission, respectively deducting an SINR (Signal to Interference plus Noise Ratio) distribution model and an interference distribution model which are received by a macro base station user and a micro base station user; deducting an average accessible rate when users in a network are served by different types of base stations by using the SINR distribution model and a known distance distribution model; and deducting a reliable closed upper bound and lower bound of Laplace transformation of the interferencedistribution model. A data simulation result shows that the coverage and data plane separated super-dense heterogeneous cellular network user access method provided by the invention can achieve a higher data rate.

The invention discloses a cache optimization method of real-time vertical search engine objects, comprising the following steps: predicting the popularity trend of different objects and calculating the cache weights of different objects by utilizing the relation between the objects and the object properties; calculating the initial distribution and adjustment method of the grasping quota in each object by utilizing the characteristics the query to the same object by users conforms to a poisson process and the data grasping is used as query driving; and calculating the dynamic balance method ofthe grasping quota in each object by utilizing the characteristic that the true change frequency of data conforms to the poisson process. The invention increases the use ratio of the vertical searchengine on the grasping quota of a data site, increases user experience of real-time vertical search engine and realizes the adaptive configuration of the real-time vertical search engine to differentdata sites.

A geostatistical method for gradually deforming an initial distribution of objects, of geologic type for example, from measurements or observations, so as to best adapt it to imposed physical constraints of, for example, a hydrodynamic type having applications of geostatistical modelling of heterogeneous reservoirs of various objects: fracture, channels, vesicles, etc., for example. The objects are distributed in a zone of a heterogeneous medium according to a Poisson point process in form of figurative points with a point density λ(x) that varies according to their position (x) in the zone, a realization of a uniform random vector according to which the position of each object is defined while respecting density λ(x) is formed, and the uniform random vector is gradually modified according to a gradual deformation process so as to obtain gradual migration of each object until a final realization best adjusted to parameters relative to the structure of the medium, such as hydrodynamic parameters, is obtained.

The invention discloses a cluster-based interference alignment method for a two-layer network. The method comprises the steps of: firstly, modeling the two-layer network based on stochastic geometry, then clustering femtocell base stations and users, and finally eliminating interference by using an interference alignment technology. A three-dimensional femtocell network structure model, particularly, a femtocell network model conforming to three-dimensional Poisson point process distribution, is close to the actual interference scene. Femtocell base stations and users are clustered according to the principle of square error function decrease, and cross-layer interference of macrocell users and each cluster and inter-cluster interference in a femtocell layer are finally eliminated by using the interference alignment technology, so that the complexity of interference management is reduced, and the method is applicable to actual communication systems.

The invention discloses a full-duplex cognition radio network cooperation spectrum sensing method based on integrated learning; the method is featured by comprising the following steps: 1, randomly forming positions of each secondary user in an area according to the Poisson point process distribution of the secondary users; 2, building a system framework according to work features sensed by the cooperation spectrum in the full-duplex cognition radio network; 3, building a secondary user energy detection model matched with a network model according to the self-interference and multi-signal source problems under the full-duplex mode; 4, analyzing and training statistic attributes of a concentration energy level vector; 5, selecting a single-layer decision tree as a weak classifier, and calculating each training data weighing coefficient and each weak classifier coefficient so as to build a strong classifier. The method can improve the system cooperation spectrum sensing performance, canincrease the radio frequency spectrum resource utilization rate, and can improve the cognition radio network throughput.

A minisatellite and its constellation availability evaluation method based on Monte Carlo simulation. The method includes following steps: 1, acquiring a fault list of faults of classes I and II in severity of classes I and II through FMEA analysis; dividing the faults in the list according to whether the faults are repairable or not; 2, for the repairable faults, utilizing the Poisson process tomodel fault laws, utilizing on-orbit data to calculate repairable fault failure rate, determining parameters of the Poisson process; for unrepairable faults, utilizing the Wiener process to model thefault laws, and utilizing ground test data or on-orbit failure data to determine parameters of the Wiener process; 3, determining minisatellite fault criteria and constellation fault criteria, and performing availability simulation on a minisatellite and its constellation; 4, through a simulation result, calculating a ratio of on-orbit normal working duration to service life of the minisatellite,and calculating on-orbit availability of the minisatellite and its constellation. By the method, complexity of availability evaluation can be effectively reduced while minisatellite availability evaluation result accuracy is ensured.

The invention discloses a wireless virtual mapping method in consideration of inter-cell interference under an ultra-dense environment. The method comprises modeling a ultra-dense network by using a random geometric Poisson point process, determining a channel and interference model through a network model, then virtualizing a wireless frequency resources, and dividing the frequency of a spectrum resource by using a wireless network mapping method so that the receiving signal-to-interference ratio of a user is guaranteed, interference is reduced, the throughput of the entire system is improved. On one hand, the spectrum allocation method in the present invention has a good theoretical performance guarantee; on the other hand, the wireless virtual mapping method is beneficial to implementation and has good application prospect.

The invention relates to a rolling bearing vibration performance reliability variation process detection method and a rolling bearing vibration performance reliability variation process detection device. In the method provided by the invention, according to a time sequence counting process, extremely little variation intensity original information shown by bearing vibration is obtained at a short time interval; through the self-help re-sampling on the variation intensity original information, much variation intensity generating information is simulated; the generating information is processed by using a grey prediction model, and a variation intensity estimation value is obtained; a Poisson process is used for expressing a reliability function; and the variation process of the bearing vibration performance reliability is predicted in real time. The method and the device provided by the invention have the advantages that on the basis of the time sequence of the vibration information, the grey self-help principle is merged into the Poisson process, and a grey self-help Poisson method is provided for predicating the variation process of the rolling bearing performance reliability.

The invention provides a dynamic arrival spectrum sensing method based on absolute value accumulation. The method is mainly divided into two steps: a signal detection process and a signal decision process; and the method specifically includes the step that: a secondary user first takes a dynamic arrival signal of a Poisson process as a received signal, and then performs absolute value processing on the received signal, takes a cumulative summation result as the decision statistic, and further judges whether a primary user exists or not to achieve spectrum sensing. According to the scheme of the invention, in the case of low signal-to-noise ratios, the problem of 'spike' of Laplace noises can also be improved, the detection performance of an algorithm can be improved, and thus the effectiveutilization of spectrum can be achieved.

A method that collects data and subjects it to statistical analysis to detect localized events, which assists in network provisioning. Illustratively, the data employed is hourly network traffic count that is collected at cell sites. By taking the advantage of additive property of Poisson process, the method integrates spatial neighbor information by aggregating temporal data in various areas, and iteratively estimating the event location and the radius of event impact by examining the posterior probability base on the aggregated data.

The invention provides a spectrum-energy efficiency balance method for a double-layer ultra dense heterogeneous network based on stochastic geometry. The method comprises the following steps: step 1, constructing the double-layer ultra dense heterogeneous network by using a Poisson point process in the stochastic geometry; step 2, obtaining a total system throughput based on a probability density function and a probability generation function of the Poisson point process; step 3, obtaining a relation among spectrum efficiency, energy efficiency and network density of the overall system from the definitions of spectrum efficiency and energy efficiency; and step 4, obtaining a relation closed expression between the spectrum efficiency and the energy efficiency via the optimization theory. The method has the advantages: 1) the network coverage is enlarged, and the network capacity is improved; and 2) the density of the network can be effectively changed to realize spectrum-energy efficiency balance of the system. Therefore, the method has better mobile user experience, and provides an effective reference for 5G honeycomb deployment.

The invention discloses a method for optimizing energy efficiency based on stochastic geometry in the coexistence of wireless body area networks. The method comprises the following steps: a) buildinga Poisson point process model by adopting a stochastic geometry method; b) calculating the probability density f(p) of transmission power of a node; c) calculating transmission success probability P<s>; and d) calculating energy efficiency etaEE of the node. A relationship between the transmission power and the energy efficiency in the coexistence of networks is analyzed, so that the energy efficiency of a system can be increased better in a wireless network coexistence design, and the aims of lowering interference and enhancing the network communication reliability are fulfilled.

The invention discloses a Poisson process user-to-shop behavior prediction method based on an automatic fitting mean function, and in the prediction method, the Poisson process modeling prediction is performed by the means of an automatic fitting mean function in a case where a user-to-shop behavior of buying a commodity has a strong randomness, so as to fully analyze whether a user will go to the shop to buy a commodity in the future. According to the invention, the problems of the unknown supply and demand information relationship of the number of shops and commodity demanders in the unknown supply and demand information reflection is solved, and the problem that the customer loyalty cannot be evaluated in part is solved; meanwhile, a set of prediction algorithm suitable for the prediction of user-to-shop purchase and integrated with data acquisition, parameter training, training result analysis and modeling prediction is developed, the most appropriate prediction parameters for specified prediction indexes are set, and the purpose of accurate prediction is achieved; and finally, the invention solves the problem in the rational use of historical data and determination of the validity of prediction results by using the automatic fitting mean function.

The invention provides a shielding data-based open source software reliability evaluation method. According to characteristics of shielding data, and by utilizing a non-homogeneous Poisson process theory which can be superposed, a cumulative failure function and a failure rate of an open source software system are calculated, and the reliability of the open source software system is further evaluated. By using an EM (Expectation Maximization) algorithm, the problem that maximum likelihood estimation is difficult to implement in reliability evaluation of open source software under general shielding data can be solved, and a reliability evaluation result of the open source software can be timely given, so that the demand of rapidly evaluating the reliability of the software in real time is met.

The invention relates to the field of seismic engineering and the field of giant disaster insurance services, and provides a seismic random event set simulation method considering large seismic time correlation, which comprises the following steps: determining seismic activity parameters on a seismic zone and a potential seismic source area; setting a random event set seismic sequence time length;for the potential seismic source area, generating a seismic random event set according to seismic magnitude grades; adopting a Poisson process model to obtain the magnitude, the size and the time ofthe earthquake for the low-magnitude gear; adopting a time correlation process model for a high-magnitude gear to obtain the magnitude, the size and the time of an earthquake; and integrating the seismic directories of the potential seismic source regions to obtain a seismic directory on the whole seismic zone. The invention creatively proposes that the seismic activity on the seismic zone integrally meets the Poisson distribution (time independent model) in statistical significance, and meanwhile, the potential seismic source region locally adopts a large seismic time correlation model, so that the whole and the local are organically combined, the accuracy and the practicability of seismic random event set simulation are greatly improved, and the method has a good application prospect.

The invention relates to an optimal bread supply method and a system under random distribution. The method comprises the following steps: first, simulating a Poisson process of bread sales; 2, the probability distribution of bread sales is modified; 3, establish the probability model of bread sale; 4, establish a daily supply quantity table; the model in the invention studies the probability distribution of daily bread sales, can well explain the randomness of bread sales, and with the updating of sales data, the probability distribution of bread sales is modified in real time, so as to improve the generalization of the model. In the invention, the probability model is used to study the optimal supply quantity strategy of the next day's bread sales, which has little dependence on data anddoes not need a large amount of data to corroborate the sales law among the data. The invention focuses on the small and medium-sized bread retailers, helps them to effectively manage the sales and operation of bread products, effectively predicts the optimal supply quantity of the next day's products, and achieves the scientific decision of the bread sales strategy.