46results about How to "Improve inference accuracy" patented technology

Methods for detecting a common user of a plurality of user devices in a network and for detecting a common cohort for a plurality of users are disclosed. The methods comprise receiving a plurality of event records. Each of the event records corresponds to an event in a network and comprises a device identifier and event information. A correlation is then calculated between a first subset of the event records having a first device identifier and a second subset of the event records having a second device identifier. Based on the correlation, it is then calculated whether the first and second device identifiers relate to user devices associated with the same user, and whether the first and second device identifiers relate to user devices associated with users belonging to a common cohort.

The invention provides a welding channel emulate device of electric arc welding, which utilizes heat conduction computation to speculate the welding channel shape of electric arc welding and can perform the simulation corresponding to the type of welding power source used in construction. The device includes: a heat source model HSM which computes the input heat from electric arc to a melting pool, a melting pool model MPM which computes the shape of the melting pool via the heat conduction computation according to the input heat qc in order to speculate the shape of welding channel, and a welding power source simulation module PSS which modularizes the welding power source outputting transient welding current; in addition, the heat source model HSM comprises: an electric arc load simulation part which modularizes the electric arc load and takes the transient welding current io as input, takes transient welding voltage vo as output; the transient welding voltage vo is input to the welding power source simulation module PSS as a feedback signal, meanwhile, the input heat qc is computed in accordance with the transient welding current io and the transient welding voltage vo.

The invention provides a host vehicle position estimation device that can improve the accuracy in estimating the host vehicle position on the map. The host vehicle position estimation device 100 configured to detect objects of each of which a position on a map is set in advance using a vehicle-mounted sensor 2, and configured to use the objects for estimating a host vehicle position which is a position of the host vehicle on the map, the device including: a object database 5A configured to store information on the detected objects in which the position of each of the objects on the map and anobject-detectable area are associated with each other; a measurement position acquisition unit 11 configured to acquire a measurement position which is the position of the host vehicle on the map, measured by a vehicle-mounted GPS receiving unit 1; a candidate object recognition unit 13A configured to recognize a candidate object which is associated with the object-detectable area including the measurement position among the objects, based on the object-detectable area in the information on the detected objects and the measurement position; and a host vehicle position estimation unit 14 configured to estimate the host vehicle position based on a position of the candidate object on the map and a result of detection performed by the vehicle-mounted sensor.

An Attention LSTM-based reinforcement learning Agent knowledge reasoning method can effectively memorize a knowledge graph reasoning path through a bidirectional long-short-term memory network, and meanwhile, an attention mechanism weights the state of the memory path to obtain a state needing to be concerned, inhibits an invalid state, realizes memory path screening, and the problem that knowledge reasoning of a reinforcement learning Agent cannot effectively memorize a reasoning path is effectively solved. The LSTMAttention network model is used in the reinforcement learning Agent for relation path feature extraction, meanwhile, a return mechanism is optimized, and the reasoning precision of a knowledge graph reasoning algorithm based on reinforcement learning under multiple reference data sets is effectively improved.

The invention relates to the technical field of games, in particular to an information processing method and device in a game and a computer medium and electronic equipment for achieving the method. The method comprises the steps of for first touch operation, determining at least one piece of trace information; for second touch operation, associating the trace information with a preset informationcollection container; for third touch operation which acts on the preset information collection container, providing a preset collection display area, and displaying the collected trace information in the preset collection display area, wherein the collected trace information is the trace information associated with the preset information collection container; for fourth touch operation which acts on the preset collection display area, generating a relation instruction used for instructing a relation of the collected trace information. According to the technical scheme, by means of the information processing method in the game, the efficiency of collection and inference by means of traces can be improved, and meanwhile, an inference process can be embodied for a user visually, so that theinformation processing method in the game benefits improvement of the inference accuracy.

The present invention provides an air conditioner, which uses a plurality of human detection sensors to divide the area requiring air conditioning into a plurality of areas according to the positions of people in the area requiring air conditioning, and sets the frequency of each area according to the frequency of people. regional characteristics. Based on the response result of the human body detection sensor within the first predetermined time period, a judgment condition indicating human presence is set in each area characteristic, and whether there is a person in each area is estimated based on the set judgment condition. According to the response result of the human body detection sensor in the second specified time, when a person is detected in the first area, it is inferred that there is a person at a time interval shorter than that of the second area; Since no one is estimated at a long time interval, the time required for inferring presence in the first area is set shorter and the time required for inferring no one is set longer in the first area than in the second area.

The invention relates to a wear amount estimation device, a wear amount estimation method, and a wear amount estimation program for improving the estimation accuracy of the wear amount of a brake pad of a vehicle. The amount of wear function represents the amount of wear as a function of vehicle speed, brake pressure, and brake duration. When the vehicle is braked, the wear amount estimation device executes a wear amount calculation process for calculating a wear amount corresponding to the vehicle speed, the brake pressure, and the brake duration by using the wear amount function. In addition, the wear amount estimation device estimates the temperature of the contact portion of the brake pad in contact with the brake rotor on the basis of the vehicle speed, the brake pressure, and the brake duration. On the basis of the temperature of the contact part, the wear amount estimation device updates temperature history information indicating at least the temperature history of the contact part. In the wear amount calculation process, the wear amount function is variably set on the basis of the temperature history of the contact portion indicated by the temperature history information obtained at the time of the last braking.

The invention discloses a deep learning model reasoning method, system and device, and a computer medium. The method comprises the following steps: determining channel quantization parameters of each channel in a target deep learning model; determining a branch quantization parameter of the model branch based on the channel quantization parameter according to a relationship between a channel in the target deep learning model and the model branch; quantizing the target deep learning model based on the branch quantization parameters to obtain a quantized deep learning model; and reasoning based on the quantized deep learning model to obtain a reasoning result. In the application, the channel quantization parameter of each channel in the target deep learning module is determined, fine-grained quantization parameter determination is realized, the branch quantization parameter of the model branch is determined based on the channel quantization parameter, reasoning is performed based on the quantized deep learning model, and the reasoning result is obtained. The deep learning model reasoning based on the fine-grained channel quantization parameters is realized, and the reasoning precision of the deep learning model is improved.

There is disclosed systems and methods to enhance reliability of measured position data. Measuring devices, such mobile phones equipped with location measurement elements (such as GPS, LBS, network location reporting, or tower location triangulation reporting) may collect various samples of positions where the device is believed to be located at particular moments in time; however such measurements often vary even if the device is not moving because of device inaccuracy, atmospheric conditions, obstructing buildings, and the like, making it difficult to determine whether such devices are actually stationary or are in motion over predetermined time periods. Systems and methods of the present invention provide for enhanced accuracy of position data by selectively merging varying location positions that are attributable to noise or accuracy deviations, and providing an enhanced assessment of actual device position.

An object of the present application is to provide a stage of charge (SOC) estimation device and a charge state estimation method that can improve the estimation accuracy of the SOC even if the discharge or charge of the secondary battery continues. In the SOC estimation apparatus, a measurement value acquiring unit obtains a voltage measurement value, a current measurement value, and a temperature measurement value of the second battery; an estimation value calculating unit calculates a SOC estimation value of the secondary battery based on the current measurement value; a voltage monitoringunit determines whether or not the voltage measurement value of the secondary battery has reached a predetermined voltage threshold during charge or discharge of the secondary battery; and in a case where the voltage measurement value of the secondary battery is determined to have reached the voltage threshold, a compensation unit corrects the SOC estimation value based on the current measurementvalue and the temperature measurement value that are obtained at a correction time point at which the voltage measurement value of the secondary battery has reached the voltage threshold.

This invention provides a gas concentration concluding method of a boiler equipment, making use of a neural network to conclude the concentration of the gas component exhausted from the boiler equipment, and making use of the neural network used by a plurality of neural networks prepared for each coal category and the neural network for judging the coal category proportion to conclude. The invention further provides a gas concentration concluding apparatus of the boiler equipment, making use of the neural network to conclude the concentration of the gas component exhausted from the boiler equipment, a, comprising a summate which makes use of the neural network used by a plurality of neural networks prepared for each coal category, the neural network for judging the coal category proportion and the mixed proportion concluded by the neural network for judging the coal category proportion to do weighted average to the concluded value of the gas concentration exported a plurality of neural networks prepared for each coal category.

The present invention provides a parameter estimation device, a parameter estimation method, a power storage system and a program. The parameter estimation device comprises: a state quantity actual measurement unit (11), which acquires the actual measurement value of a state quantity correlated with a plurality of parameters; Part (12), according to the correlation between the estimated values ​​of the plurality of parameters and the above-mentioned state quantities, calculates and obtains the calculated values ​​corresponding to the actual measured values; The value of the error evaluation function calculated by multiplying the sum of the absolute magnitudes of the errors of the corresponding calculated values ​​by the first coefficient and the deviation degree of the error by the second coefficient, changing the above-mentioned estimated value, and An optimum estimated value that minimizes the value of the error evaluation function is determined.

The invention discloses a step-by-step inference method for business relationships of Internet autonomous domain systems, which comprises the following steps: firstly, based on a valley-free path principle, according to top-level autonomous domain system information and autonomous domain system degree information, carrying out principle inference on relationships between adjacent autonomous domain systems of each path in a path table; secondly, performing re-judgment on an autonomous domain system relationship with conflicts in principle inference by using a mode of combining probability inference and principle inference, preferentially determining a result with a high global inference proportion, and updating the principle inference according to a new result; and for the autonomous domain system relationship of which the inference result is still not determined, inference is carried out according to the autonomous domain system degree information, and finally the commercial relationship between the adjacent autonomous domain systems on the path in the routing table is obtained. According to the method, the accuracy of deducing the types of the business relations between the autonomous domain systems is effectively improved, and the method is suitable for Internet routing security and business relation analysis of the autonomous domain systems.

The invention provides a network information diffusion source inference method based on a differential pre-solution set and belongs to information technology processing field. The method comprises steps of using G = (V, E) to represent a connection relationship between the network nodes, wherein V represents a network node set, e represents a set of network edges; selecting a difference pre-solution set S from the difference pre-solution sets; establishing diffusion source characteristics, collecting cascading information, judging the module | Ic | of an index set, if the module | Ic | is greater than a preset value, extracting a characteristic vector of cascading C, adjusting the diffusion source characteristics of each node v belonging to V, calculating norms of all nodes v belonging toV one by one, and finding out the node with the minimum norm as a source. According to the method, the data source can be actively optimized and selected, the quality of input data is improved, and the source inference precision is greatly improved.