176 results about "Stochastic algorithms" patented technology

The invention discloses a byzantine-fault-tolerant consensus method applied to a block chain. The method comprises the steps of specifying a certain number of right and interest accounts and initial consensus accounts in an initiated block of the block chain; after a consensus process is started, for the height h of a current block, selecting a consensus account to initiate a proposal of a new block according to a fixed random algorithm in a consensus account list; receiving the proposal and voting a block with the height of h by other consensus nodes; within a period of time, if the number of votes exceeds eta 1, representing that a consensus is formed, and starting the consensus of a block with the height of h+1 in the next round; if the number of votes does not exceed eta 1 but exceeds eta 2, representing that the consensus is possibly formed, broadcasting a voting request of the block in the previous round, and continuing to wait for a period of time; and if the number of votes does not exceed eta 2, cancelling the proposal in the round and re-performing the proposal of the new block. Therefore, computing resources can be saved; a large amount of blocks can be continuously generated; and computing power competition is avoided.

Methods and systems are provided for analyzing the business rules, business metrics, and decision parameters for a firm or organization, processing a subset of such data to form output, and offering access to selective views of such output including evaluation and comparative data regarding execution of such business rules, information on corresponding business metrics or sets of business metrics, information on corresponding decision parameters or sets of decision parameters or scenarios, and other useful analytic information which can help a firm or organization evaluate and modify business policies based on said rules, metrics, and parameters. In addition to said rules, metrics and/or parameters, the data for the business rule analysis can include conventional historical data or hypothetical data based on simulations which the current system and method provide based on prescribed random and non-random algorithms. The simulated or hypothetical data enables users to conduct rule analysis based on historical data, simulated data, or hybrid models. In this manner, the methods and systems described in this invention provide for both an evaluation of a firm's current policies as well as an evaluation of policy modifications not actually executed but for which hypothetical data can be provided and analyzed.

The embodiment of the invention provides an Internet of Things service low-delay load distribution method and device based on edge computing. The Internet of Things service low-delay load distributionmethod comprises the steps: acquiring a task request of each application in each terminal and the computing capacity of each edge node; and inputting the task request of each application in each terminal and the computing capacity of each edge node into a preset optimization problem model, and outputting a resource allocation matrix and a task allocation matrix, wherein the preset optimization problem model comprises a particle swarm algorithm model improved through an ant colony algorithm and a semi-definite relaxation algorithm model improved through a Gaussian random algorithm. The Internet of Things service low-delay load distribution method and device based on edge computing improve particle swarm optimization by applying the ant colony algorithm, reduce the convergence time of the algorithm, improve the performance of the resource allocation result, solve the rank 1 constraint in the semi-definite relaxation problem by applying the Gaussian random variable, improve the performance of the task allocation result, and finally reduce the service delay.

A method for developing a template of a reference document, such as a bank note and using that template to validate other test documents. The method involves using images of a plurality of reference documents, such as banknotes and segmenting each image in a like manner into a plurality of segments. Each segment is then classified using a one-class classifier to determine a reference classification parameter. These parameters are used to define a threshold reference classification parameter. Optionally, the step of segmenting is optimized to determine a preferred number of segments, and a preferred combination of these for use in a subsequent validation process. Preferably, this is done using a stochastic algorithm such as a genetic algorithm.

A stochastic algorithm has been developed for predicting the drug-likeness of molecules. It is based on optimization of ranges for a set of descriptors. Lipinski's “rule-of-5”, which takes into account molecular weight, logP, and the number of hydrogen bond donor and acceptor groups for determining bioavailability, was previously unable to distinguish between drugs and non-drugs with its original set of ranges. The present invention demonstrates the predictive power of the stochastic approach to differentiate between drugs and non-drugs using only the same four descriptors of Lipinski, but modifying their ranges. However, there are better sets of 4 descriptors to differentiate between drugs and non-drugs, as many other sets of descriptors were obtained by the stochastic algorithm with more predictive power to differentiate between databases (drugs and non-drugs). A set of optimized ranges constitutes a “filter”. In addition to the “best” filter, additional filters (composed of different sets of descriptors) are used that allow a new definition of “drug-like” character by combining them into a “drug like index” or DLI. In addition to producing a DLI (drug-like index), which permits discrimination between populations of drug-like and non-drug-like molecules, the present invention may be extended to be combined with other known drug screening or optimizing methods, including but not limited to, high-throughput screening, combinatorial chemistry, scaffold prioritization and docking.

The invention discloses a wireless network sensor network coverage distributed method. Assigned task completion time is set as a fixed value, and a mathematic model is established aiming at how to enable coverage of nodes-to-point positions to be maximum; the assigned task completion time is divided according to turns to solve the model, how to select the most suitable working node in each turn and close other redundant nodes at the same time is achieved, and the actual network service life is made to be longer than the assigned task completion time; in addition, how to select the optimal working time scheme of the working nodes in each turn to enable the coverage of nodes-to-point positions to be maximum is achieved; therefore, an improved distributed algorithm is proposed. According to the wireless network sensor network coverage distributed method, through simulation experiments, the performance of the improved algorithm exceeds that of an original algorithm and that of a random algorithm in the aspects of total effective coverage time, network service life, average weighting event detectivity and network node residual energy evenness.

The invention discloses a sensor-network-based low-energy-consumption ecological environment monitoring node deploying method and relates to the Internet of Things. The method comprises the following steps: firstly determining factors to be monitored and key points with relative factors; building an optimal mathematic monitoring model according to the monitored factors and the key points; then solving the mathematic model and finding a key point with most attributes and taking the key point as a pre-selection point; invoking an attribute optimizing method for selecting the key points with all the attributes which are close to an attribute mean value if the number of the pre-selection points is greater than 1; invoking a crop growth factor weighing method for determining monitoring points if more than two pre-selection points exist after the treatment; randomly determining that the pre-selection points processed by the crop growth factor weighing method are taken as the monitoring points by using a random algorithm; finally processing a matrix T formed by the key points and the attributes by using a matrix optimizing method of the key points and the attributes to obtain the number of the final monitoring nodes and the distribution positions of the monitoring nodes.

The invention discloses a consensus method of an alliance block chain network. The alliance block chain network is composed of peer nodes; a leader node is selected from the peer nodes; then the leader node selects 13 packers from the peer nodes; and one packer election chain records the election information of the packer. The leader node is selected from the peer nodes, and used for collecting the peer node information to build a peer information table, selecting the packers from the peer nodes in the block chain network by using a random algorithm, collecting and verifying transaction information sent by a client, adding transactions passing the verification into a transaction pool, sending transaction data to the packer nodes after the untreated transactions in the transaction pool reach a certain amount, and deleting the transactions from the transaction pool after the transaction information is successfully added into the block chain. The packers are selected by the leader from the peer information table by using a random number matching method, for receiving and verifying the transactions sent by the leader, and packaging the transactions passing the verification into a block. The invention is the consensus method that is random, fair, flexible, reliable and capable of tolerating Byzantium errors.

The invention discloses a robot personification handwriting writing system and a control method thereof, and particularly relates to an intelligent simulation printer device and a handwriting writing platform matched with the device. A computer obtains user handwriting paths in the writing process of a user on a software platform, and a dedicated word stock is built; in cooperation with the stochastic algorithm, any field and handwriting selected by the user are called to be output to the writing system, and the writing process is finished by hardware equipment instead of manpower. The system is simple in flow, compact in structure and high in writing quality efficiency, and the writing handwriting approaches to that of the user.

The invention discloses a real task allocation method applied to a preference crowd-sourcing system. A preference crowd-sourcing system model is put forward, the model has multiple preference task requesters, and each task requester submits one task. Each task has different work load, and the value of each task is related to the difficulty of the task and the effort level of a crowd-sourcing worker executing the task. Regarding the model, the invention further provides a real task allocation method, having the target of maximizing the total value of the allocated task. The real task allocation method is mainly composed of two core algorithms: a task allocation algorithm based on value greed and a task allocation algorithm based on value density greed. The real task allocation method is a random algorithm established over the two core algorithms. The real task allocation method has the characteristics of calculation effectiveness, work load feasibility, preference reality and constant factor approximation ratio.

The invention relates to a data storage method and device, a storage medium and computer equipment. The method comprises the following steps: receiving original data which comprises timestamp; carrying out iterative computation by taking the timestamp as a random seed of a preset random algorithm to generate a random secret key; encrypting portions, which correspond to sensitive field names in a preset sensitive field name database, in the original data by a preset first encryption algorithm according to the random secret key; carrying out transformation treatment on the encrypted original data to generate replacement data; and storing the random secret key and the replacement data to a database table. By the data storage method and device, the storage medium and the computer equipment, safety of data storage is improved.

The invention provides a finite element modeling method of a random microstructure of a heterogeneous material, and particularly relates to a method of establishing a finite element network model of the random microstructure of the heterogeneous material based on microstructure probability distribution information and a random algorithm. The method comprises the following steps of: determining a microstructure probability distribution function by using a real or dummy heterogeneous material component phase physical distribution form; converting a probability distribution function into a discrete space of the model on the basis of establishing the finite element network topological model of the material; and determining material attributes of each unit in the definite element model by using random real numbers generated by a pseudo random number generator and consistently distributed in an interval [0, 1], thereby establishing the random microstructure model of the heterogeneous material. The method is suitable for the heterogeneous materials in different modes; the established definite network model can be directly used for analyzing relation among microscopic property, microscopic structure, macroscopic performance of the heterogeneous material; and basis is provided for development and preparation of a new material.

The invention relates to a mass transmission method and device based on an elliptic curve, and the method comprises the steps that S1, a receiver generates a private key d through employing a random algorithm, and generates a public key Q based on an SM2 elliptic curve; S2, a sender constructs multiple pieces of selection information, each piece of selection information comprises an identifier andinformation content, and only an identifier list of the multiple pieces of selection information is sent to the receiver; S3, the receiver selects an identifier from the identifier list, gives an identifier value to the selected identifier, encrypts the selected identifier and the identifier value by using an elliptic curve algorithm to generate an encryption parameter, and sends the encryption parameter to the sender; S4, the sender encrypts all the selection information by using the encryption parameter and the public key Q, and sends the encrypted ciphertext to the receiver; and S5, the receiver decrypts the ciphertext transmitted by the sender by using an elliptic curve algorithm to obtain the information content corresponding to the selected identifier. According to the method, the problems of privacy data protection and the like involved in a blockchain project scene can be solved.

The invention discloses a node transmission sequence optimization competitive channel underwater acoustic network parallel communication method. According to the invention, each source node uses the same non-random algorithm to calculate the sequence and time of data transmission of the node in the transmission cycle; data are transmitted to a corresponding destination node after timing is up to the time; after the data of all source nodes are transmitted, each destination node uses the same non-random algorithm to calculate the sequence and time of ACK or NACK signaling transmission of the node in this transmission cycle; and after timing is up to the time, the destination node with correct received data transmits ACK signaling to the corresponding source node, and the destination node with wrong received data transmits NACK signaling to the corresponding source node. According to the method, the time required for one transmission cycle is effectively reduced and the channel utilization efficiency is improved under the premise of conflict-free parallel node data transmission. The method can be widely used in various underwater acoustic communication networks based on competition agreement, an underwater acoustic sensor network and other occasions.

The present invented method contains through given decetor trajectory information to proceed environment judgement and automatically generating barrier, based these barrier through planning algorithm to generate stance mobile route, wherein said planning algorithm adopting submissive improved RRT algorithm, in stochastic tree expansion through single axle stochastic algorithm, simplifying three-dimension programming wide angle mobile planning problem into two-dimension planning problem, and leading-in illumine factor speeding-up convergence of algorithm, and utilizing forward search to proceed optimizing to programmed route. The present invention has strong interactivity, visual, and immediacy etc properties.

The invention discloses a method for preventing Trojans ferrying via movable memories to steal files and belongs to the technical field of information security and computer software. The method includes that a monitoring module is arranged, a verification process is started when the module acquires a query of transmitting data to the movable memories, users submit verification information, and then the verification process judges whether the verification information is correct or not, if the verification information is corrected, then the query is received, and if the verification information is uncorrected, then the query is rejected. The verification process can judge correction of the verification information via methods as follows: generating a dynamic verification code by adopting a randomized algorithm after starting the verification process, displaying the verification code to users, and then judging whether the verification information is identical to the verification code by the verification process after the users submit the verification information. By aid of the method, safe data ferrying of the movable memories between the internal network and the external network can be realized.

The invention discloses a method for generating a character adversarial verification code based on frequency domain noise addition. The method comprises the following steps of generating a string of character sequences by a random algorithm, and respectively converting characters in the character sequences into a character image containing the single corresponding character in sequence; convertingthe character image from a spatial domain to a frequency domain, adding adversarial noise to the character image of the frequency domain according to an adversarial learning method, and converting the character image added with the adversarial noise of the frequency domain from the frequency domain to the spatial domain; and splicing the character images added with the adversarial noise togetheraccording to the sequence of verification code answers in order to form the character adversarial verification code. The invention further discloses a system for generating the character adversarial verification code based on the frequency domain noise addition. On the basis of the adversarial learning method, the adversarial noise is added to the character images at the frequency domain, and thegenerated character adversarial verification code can effectively avoid or reduce the image preprocessing adopted by an attacker, so that the safety of the character verification code is improved.

The embodiment of the invention provides a random number generation method and device based on a block chain. The method comprises the following steps: receiving a seed display value issued to the block chain by each participant of an event in a first time period after the event occurs; wherein the seed display value is a value obtained by operating a seed selected by the participant through an encryption algorithm; receiving seeds issued to the block chain by each participant of the event in a second time period after the event occurs; respectively detecting whether seeds corresponding to seed display values published by each participant of the event in the first time period are consistent with seeds published in the second time period or not through the encryption algorithm, so as to verify each participant of the event; and calculating seeds published by all verified participants of the event in the second time period by using a random algorithm to obtain a random number. Through the embodiment of the invention, the fairness of the generated random number can be ensured.

The invention relates to the technical field of smart terminals, and provides a method, device and system for preventing cheating. According to a preset random algorithm, the participating user ID forentering each random virtual room is extracted; the user's location maintained by the current server for the user ID is read, if it is confirmed that in a same random virtual room, the similarity oftwo users' locations corresponding to their user IDs is greater than or equal to a first preset threshold value, then at least one participating user is re-extracted for the random virtual room, and the similarity verifying is conducted again; and if it is confirmed that in the same random virtual room, the similarity of two users' locations corresponding to their user IDs is less than the first preset threshold value, then theme activities in the current random virtual room start. According to the method, device and system for preventing cheating, pre-treatment of cheating behaviors is achieved, the probability of cheating behaviors occurring in the random virtual room is further reduced, and the effectiveness of the theme activities in the random virtual room is improved.