4164results about How to "Improve rationality" patented technology

The invention discloses a method for estimating the charge state of a power cell, which comprises the following steps that: 1. a continuous state space model capable of expressing the relationship of each element in an expression circuit is obtained by an equivalent circuit model of a power cell; the relationship between the open-circuit voltage and the cell charge state is obtained through the standing experiment of the power cell, and the cell charge state is introduced into the continuous state space model of the power cell as a state variable; the power battery model under the noise environment is obtained by combining the noise information; and finally the continuous state space model is subjected to linearization and discretization so as to obtain a linear discrete state space model; 2. a relationship curve of the open-circuit voltage and the cell charge state is obtained through the standing experiment of the power cell, and a parameter k and a parameter d in the power cell model are obtained approximately; 3. parameters of the power cell model are obtained through the identification of current and voltage data collected by a data collecting system; and 4. the power cell charge state is estimated by utilizing a moving horizon estimation method based on the determined power cell model.

The invention discloses a method for identifying abnormal motion in a video. The method comprises the steps that an area of which the pixels have certain change is extracted from a video sequence through a foreground extraction module; a movement target detected by the foreground extraction module is judged through a pedestrian judgment module, and a rectangular box judged to be a pedestrian is kept and transmitted to a target tracking module; each identified target in the scene is continuously tracked in a multi-target way through the target tracking module; the posture of each target tracked by the target tracking module within each frame of time is judged through an abnormal behavior trigger module and behavior analysis is performed on the abnormal behavior; and the abnormal behavior is processed and computed into a video segment through a behavior identification module, and the abnormal behavior is alarmed and the behavior type of the abnormal behavior is identified. The invention also discloses a system for identifying the abnormal motion in the video. The problem that abnormal behavior (falling down) detection of massive video data cannot be performed in real time can be solved and the detection accuracy can be greatly enhanced.

The invention discloses an event atlas construction system and method based on multi-dimensional feature fusion and dependency syntax. The event graph construction method based on multi-dimensional feature fusion and dependency syntax is realized through joint learning of event extraction, event correction and alignment based on multi-dimensional feature fusion, relationship extraction based on enhanced structured events, causal relationship extraction based on dependency syntax and graph attention network and an event graph generation module. According to the event graph construction method and device, the event graph is constructed through the quintuple information of the enhanced structured events and the relations between the events in four dimensions, and the defects that in the priorart, event representation is simple and depends on an NLP tool, the event relation is single, and the influence of the relations between the events on event graph construction is not considered at the same time are overcome. According to the event atlas construction method provided by the invention, the relationships among the events in four dimensions can be randomly combined according to different downstream tasks, and the structural characteristics of the event atlas are learned to be associated with potential knowledge, so that downstream application is assisted.

The invention discloses a staged multi-path model algorithm of urban rail transit network passenger flow distribution. The algorithm comprises the following steps of: dividing definite factors and indefinite factors affecting the outgoing of passengers into two stages to calculate and correct the passenger flow distribution proportion of a path, determining the initial distribution proportion of the passenger flow on the path by using the comprehensive outgoing impedance of time unit as a main factor, and correcting the proportion by considering the transfer times and the crowdedness degree on the basis of time window constraints according to a generated full origin-destination (OD) passenger flow distribution path set. The model and the algorithm provided by the invention have higher reasonability and practicability and can effectively serve the passenger flow management of the urban rail transit, meet the service requirement of clearing automatic fare collection (AFC) passenger flow and fare, and provide auxiliary decision proof for operation organization optimization and coordination.

The invention relates to a method and a system for space and time analysis of urban road traffic states. On the basis of a space and time autocorrelation theory, a basic theory of mathematical statistics is applied, and according to the real-time traffic flow data of a road network, the space and time evolution of the traffic states and the generation, development and dissipation process of congestion are analyzed. The distribution features of different road states in space and time are subjected to statistical analysis by the method, the space and time rule of the evolution of the road traffic states of the urban road network is analyzed, the congestion rush hour in time and the bottleneck road in space are identified and judged, and the formulation and implementation of traffic measures are further supported.

The invention discloses an active learning based data automatic marking method, and belongs to the field of active learning. The data automatic marking method comprises the steps of 101, processing marked data and unmarked data; 102, classifying the unmarked data by using a plurality of different classifiers; 103, selecting data with low difference entropy; 104, performing manual marking on the data with low difference entropy; and 105, performing self-checking on a manual marking result. The invention provides a data automatic marking system with a self-checking function through combining an active learning method in allusion a problem of how to ensure the accuracy of manually marked data as far as possible while reducing the volume of the manually marked data, thereby achieving the purposes of reducing the workload and improving the accuracy of the manually marked data.

The invention discloses a switch processing method, a serving base station, an adjacent base station and a network communication system. In the switch processing method, the service base station selects a target base station from the adjacent base station which can receive switching request of a mobile terminal, and informs the mobile terminal; if the adjacent base station capable of receiving the switching request of the mobile terminal receives switching information corresponding to the mobile terminal, the adjacent base station is judged as the target base station and matched with the mobile terminal to switch; otherwise, the adjacent base station is judged as a preparation base station, and the resource amount reserved for the mobile terminal by the adjacent base station is reduced. The switch processing method can effectively improve the switching success rate.

The invention discloses a defrosting control method. The defrosting control method comprises the following steps: controlling an air conditioner in a steady state, and remaining to operate for some preset time in the steady state; in real time detecting the operation current of an outdoor fan; judging whether the change rate of the operation current of the outdoor fan is not more than a preset value under a preset period or not, if so, controlling the air conditioner unit in a defrosting state. The defrosting process is controlled according to the current change rate of the outdoor fan of the air conditioner, in comparison with the prior art, the defrosting process is controlled according to the temperature of the outdoor tube of the air conditioner and the current value of the outdoor fan, the operation is relatively simple, the defrosting process is relatively reasonable and the defrosting effect is relatively better. The invention further disclose a defrosting control device.

The invention discloses a space-ground integrated network resource allocation method based on an improved genetic algorithm, comprising the following steps: defining parameters and decision variables;establishing a multi-objective constraint model; and allocating resources based on the improved genetic algorithm. The method considers the allocation of multiple resources, so that the resource utilization rate of the space-ground integrated network is significantly improved. The improved selection mechanism effectively retains elite individuals and speeds up the convergence of the improved genetic algorithm. The shortest time for completing all tasks is taken as a objective function, and the priorities of the tasks are considered at the same time, so that the rationality of resource allocation is effectively improved; and the elite retention strategy is combined with the roulette strategy to improve the selection mechanism, adaptive crossover and mutation operators are designed to improve the existing genetic algorithm, and the improved algorithm can effectively avoid the shortcomings of poor local optimization ability of the genetic algorithm and easiness to fall into local optimum, prevent the loss of the optimal solution and effectively improve the optimization speed.

The invention discloses a dialogue generation model training method, which comprises the following steps: obtaining a dialogue data set, the dialogue data in the dialogue data set comprising questionsand annotation replies corresponding to the questions; based on the questions in the dialogue data set, obtaining the coded representation of the question through an encoder in a constructed dialoguegeneration model; fusing the coded representation of the question and knowledge information of transfer learning of the question from a knowledge base question and answer model through a decoder in the dialogue generation model to obtain a prediction reply corresponding to the question output by the dialogue generation model; and determining a loss function based on the prediction reply and the annotation reply corresponding to the question, and adjusting parameters of the dialogue generation model through the loss function until the loss function of the dialogue generation model is convergent. According to the method, the knowledge information can be better fused by the model, so that the dialogue generation accuracy and reasonability are improved. The invention further discloses a dialogue generation method and device, equipment and a medium.

The invention discloses an automatic driving overtaking decision-making method based on reinforcement learning under opposite double lanes. The method comprises the following steps of collecting the traffic state of an automatic driving vehicle through a sensor; inputting the collected traffic state into a trained decision model; enabling the decision model to select a corresponding driving actioninstruction from the action space according to the input information and output the driving action instruction, and driving the vehicle automatically to form a new traffic state after the driving action; calculating a reward value of the driving action through a reward function, and storing the original traffic state, the driving action, the reward value and the new traffic state into an experience playback pool as transfer samples; calculating a loss function value of the decision model, and optimizing parameters of the decision model according to the transfer sample and the loss function value; and repeating the steps until the automatic driving is finished. The safety and comfort of the overtaking decision-making process of the automatic driving vehicle are ensured, and the humanization and robustness of decision-making are improved through a reinforcement learning decision-making method.

The invention relates to a lithium battery charge state estimating method and belongs to the technical field of batteries of electric vehicles. The lithium battery charge state estimating method aims at estimating the charge state of a lithium battery under the complex working conditions of charging and discharging at different multiplying power levels through an estimation method based on a parameter time varying observer. The lithium battery charge state estimating method specifically comprises the step that a battery charge state is regarded as a state variable to be introduced into a lithium ion battery continuous model, the upper limit of hysteresis voltages is determined according to the charging and discharging open-circuit voltage, the battery hysteresis phenomenon is considered to be a first order dynamic process related to the current absolute value, a battery polarization voltage model with parameters changing along with currents and an internal resistance model with parameters changing along with currents are structured through RC rings, battery model end voltages are structured, and a nonlinear parameter time-varying battery model is obtained. The lithium battery charge state estimating method is based on a parameter time-varying lithium ion battery equivalent circuit model, the model parameters are calibrated to be a function of current multiplying power, the characteristics of the battery can be accurately expressed, and meanwhile an existing estimation method can be easily used.

The invention discloses an intelligent inquisition method, an intelligent inquisition system, computer equipment and a storage medium. The intelligent inquisition method includes the following steps that: disease prior probability prediction is performed according to the main complaint content of a target object, disease prior probabilities for the target object are obtained; at least one candidate disease is determined based on the order of the disease prior probabilities; and at least one agent strategy correspondingly associated with the at least one candidate disease is determined from a pre-established multi-agent model based on reinforcement learning, wherein each agent strategy is used to indicate questions which are required to be raised for the output of next interaction under a current symptomatic state; based on each agent strategy, interactive consultation is conducted according to the interactive selection of the questions which are required to be raised for the output ofthe next interaction for the target object. With the intelligent inquisition method, the intelligent inquisition system, the computer equipment and the storage medium of the invention adopted, the rationality of inquisition logic for related diseases and user experience can be optimized with the accuracy of inquisition results ensured.

The invention relates to an establishment method for hydrocarbon source rock hydrocarbon production rate charts in petroleum resource assessment. The establishment method includes the steps of 1), collecting experimental samples and determining thermal simulation experiment data through experiments; 2), collecting materials; 3), calibrating kerogen generated oil, generated gas and oil-cracking gas kinetic parameters; 4), establishing sedimentary burial history and thermal-history models of hydrocarbon source rocks on a target stratum of a research area; 5), establishing constraint condition of hydrocarbon source rock hydrocarbon production rate; 6), establishing kerogen generated oil, kerogen generated gas, oil generated gas, clean and total gas conversion profile charts on the target stratum of the research area; 7), checking whether dynamics geological extrapolation results meet requirements or not; 8), putting forwards part of hydrocarbon expulsion mode adjustment coefficients, evaluating hydrocarbon production rate curves of the partial hydrocarbon expulsion model, and establishing the hydrocarbon source rock hydrocarbon production rate charts including three modes, namely the mode of complete hydrocarbon expulsion, the mode of partial hydrocarbon expulsion and the mode of no hydrocarbon expulsion. The shortcoming in an original calculating method and experiment simulated data of the hydrocarbon source rock hydrocarbon production rate is overcome, and the hydrocarbon source rock hydrocarbon production rate at the target stratum can be accurately and reasonably determined according to oil field exploration practice by oil field workers.

The invention discloses an electromobile charging and exchanging power station stationing and planning system and method. The system and method comprises an electromobile charging and exchanging power station stationing, planning and decision-making management centre, a vehicle-mounted collection terminal and a method for stationing and planning by using the system. The electromobile charging and exchanging power station stationing, planning and decision-making management centre is connected with the vehicle-mounted collection terminal through an electric power private network, the electromobile charging and exchanging power station stationing, planning and decision-making management centre comprises a preposition service device, a data storage device and a layout planning service device, the data storage device comprises a relation data base server and a real-time data base server, and the layout planning service device comprises servers such as a global information system (GIS) server and an area calculation server. The electromobile charging and exchanging power station stationing and planning system and method can effectively prevent newly-built electromobile charging and exchanging power stations from building in the service scope of the existing electromobile charging and exchanging power station, improves feasibility and rationality of an electromobile charging and exchanging power station stationing and planning scheme, improves use ratio, charging ratio and work efficiency of the electromobile charging and exchanging power station.

The invention discloses a medical interrogation dialogue system and a reinforcement learning method applied to the medical interrogation dialogue system, and relates to the technical field of medicalinformation. The system comprises a natural language understanding module used for classifying the intentions of users and filling slot values to form structured semantic frames; a dialogue managementmodule used for interacting with a user through a robot agent, inputting a dialogue state, performing action decision on the semantic frame through a decision network, and outputting final system action selection; a user simulator used for carrying out natural language interaction with the dialogue management module and outputting user action selection; a natural language generation module used for receiving system action selection and user action selection, enabling the user to check the selection through generating sentences similar to a human language by using a template-based method. According to the invention, the medical knowledge information between diseases and symptoms is introduced as a guide, and the inquiry historical experience is enriched through continuous interaction witha simulated patient. The reasonability of inquiry symptoms and the accuracy of disease diagnosis are improved, and the diagnosis result is higher in credibility.

The invention belongs to the technical field of intelligent robots and control and particularly relates to a mobile robot path planning method based on a variable-dimension particle swarm membrane algorithm. The mobile robot path planning method based on the variable-dimension particle swarm membrane algorithm includes the main steps of performing environment modeling, inputting path parameters, setting a fitness function, initializing parent particles and child particles of an effective path, classifying and re-classifying the path particles, evaluating the fitness function, updating the positions of d-dimension particles, judging whether the current particles have invalid dimensions or not, correcting the particles with invalid dimensions, removing redundant dimension information and the like. According to the mobile robot path planning method based on the variable-dimension particle swarm membrane algorithm, the optimum path suitable for a robot to walk along can be fast planned through global known or local position information of a complex environment and state parameters of an undetermined mobile robot.

The invention discloses a method and a device for realizing load balance among neighboring cells in order to solve the problems in the prior art such as low efficiency of the realization of the load balance among the neighboring cells and low after-balancing mobile communication network quality. The method comprises: determining to-be-regulated cells requiring load balance currently according to the load ratio of cells; according to the performance information of the neighboring cells of the to-be-regulated cells, selecting target cells to participate in load balance with the to-be-regulated cells from the neighboring cells; according to the performance information of users in the to-be-regulated cells, selecting target users to participate in load balance from the users in the to-be-regulated cells; and adjusting the target users to the target cells. According to the technical scheme of the invention, the effectiveness of the realization of load balance among neighboring cells is improved and the quality of a mobile communication network is improved.

The invention provides a special disease knowledge graph construction method and device. The method comprises the following steps of: on the basis of constructing a special disease knowledge system, extracting medical entity information by utilizing a pre-constructed entity extraction model; extracting attribute information and relation information of the medical entity on the basis of the specialdisease knowledge system; and based on the extracted information, building a knowledge map of the disease, wherein the entity extraction model is a model trained on the basis of a pre-labeled training data set, and the training data set is constructed by using medical word list matching in combination with manual auditing and labeling. When medical entities are extracted, the training data set required by entity extraction model training is constructed by using medical word list matching in combination with manual auditing and labeling, so that the workload of constructing the training data set can be reduced, the consumption of manpower resources and time resources is reduced, and meanwhile, the construction efficiency and knowledge rationality of a special disease knowledge map can alsobe improved.

The invention discloses a method and device for controlling an electronic expansion valve. The method for controlling the electronic expansion valve includes the steps of a, periodically obtaining the current outdoor environment temperature and the current frequency of a compressor, obtaining a first adjusting range of the electronic expansion valve according to the adjustment range, corresponding to the preset outdoor environment temperature, of the electronic expansion valve, obtaining a second adjusting range of the electronic expansion valve according to the adjustment range, corresponding to the preset frequency of the compressor, of the electronic expansion valve, b, obtaining the intersection of the first adjusting range of the electronic expansion valve and the second adjusting range of the electronic expansion valve, taking the intersection as a final adjusting range of the electronic expansion valve, c, obtaining the variation trend of exhaust gas temperature, and correspondingly adjusting the electronic expansion valve within the final adjusting range of the electronic expansion valve according to the variation trend of exhaust gas temperature. According to the method and device for controlling the electronic expansion valve, the electronic expansion valve is adjusted fast and reasonably under the control of the outdoor environment temperature factor adjusting range and the compressor frequency factor adjusting range and on the basis that the electronic expansion valve is controlled by the exhaust gas temperature.

A composite energy system of solar energy, ground source heat pump and chilled water storage comprises an air conditioner, a domestic hot water supply device, one or more device (hereinafter referred to as host) of a solar energy heat-collecting device, a heat storage water tank unit, a cold storage water tank unit and a ground source heat pump system, a ground heat exchanger, an auxiliary heating device, a circulating water pump, a first electric three-way valve, a second electric three-way valve, a first electric two-way valve and a second electric two-way valve, wherein the circulating water pump is communicated with the air conditioner, and the auxiliary heating device is communicated with the domestic hot water supply device. The invention fully utilizes renewable energy sources such as solar energy, geothermal energy and biomass energy to masterly combine the ground source heat pump air-conditioning system with the solar energy hot water system and the chilled water storage system and construct a comprehensive energy system combined by the domestic hot water system, the ground source heat pump, the chilled water storage air-conditioning system and the like; and the invention is completely combined with the entire building so as to greatest reduce the floor space and the investment and increase the energy efficiency and economic performance of the system.

The invention discloses an explicit congestion control method based on bandwidth estimation in a high-bandwidth delay network, which comprises the following steps of: calculating the current available bandwidth of a network by a TCP (Transmission Control Protocol) sender through observing an ACK (Acknowledgement Character) receiving interval, loading a router by a packet header ECN (Explicit Congestion Notification) 2bits information feedback network, carrying out network state judgment by the sender through explicit feedback information and estimated available bandwidth values, and adjusting a congestion mechanism according to a judgment result. The congestion is judged by combining end-to-end feedback and router explicit feedback, i.e. finer congestion information is given by using the bandwidth estimation values based on the explicit feedback of coarseness, thus an algorithm ensures high congestion feedback precision while reducing the explicit feedback overhead and improving the protocol popularization, and improves the efficiency and the convergence rate of the protocol.

The invention relates to the technical field of computer information processing, and especially relates to an order processing method and system. The method comprises the following steps: a, receiving an order, and obtaining the data of the order; b, enabling the order to be distributed to a service point which is the most nearest to the order according to the obtained data of the order; c, enabling the service point to carry out the matching of address coordinates, service time and service skills of service staff according to the data of the order, and carrying out the order distribution according a matching result. The method achieves the automatic matching of the corresponding service worker according to the data of the order, reduces the order distribution workload, improves the order distribution reasonability, and facilitates the improvement of the work efficiency and users' satisfaction.

The invention provides a method and a device for improving the accuracy and energy-saving efficiency of an 'on-off time-area process' heat allocation system. The device comprises total heat supply metering devices arranged in building heat supply pipes and room temperature controllers and electrical heat balance flow regulating devices which are installed by heat supply users respectively, wherein the room temperature controllers are arranged at reference positions in heating areas of the users; and the electrical heat balance flow regulating devices comprises on-off control valves which are arranged in house branch heat supply pipes of the users. The room temperature controllers monitor indoor temperatures, and the electrical heat balance flow regulating devices control the flows in the heat supply pipes and the opening and closing of the heat supply pipes, and calculate and store the total opening time length of on-off control valves.

The invention discloses an enterprise power consumption load prediction method based on a k-means clustering radial basis function (RBF) neural network. The method includes steps: historical load data acquisition, meteorological data acquisition, date discrimination, neural network prediction, error calculation and correction, load curve drawing, and prediction data export. A prediction result is obtained by employing the neural network via the historical load data and meteorological factor input quantity, and correction is realized via an error correction module. Based on the requirement control technology of load prediction, with the combination of an industrial enterprise production plan and the condition of power consumption load usage, the system performs requirement control via a built-in requirement curve node determination method at a control point before the load prediction value reaches the maximum requirement, whether unnecessary loads are removed is determined, the current most appropriate energy-saving scheme is automatically selected, the maximum requirement is controlled in advance, over-load operation and even tripping operation can be effectively avoided, and safety and energy-saving production is guaranteed.

The invention provides a driving behavior analysis method based on a vehicle-mounted monitoring and management platform. The method comprises the steps that: a terminal collects vehicle state data; the terminal packages and uploads the vehicle state data; a front-end processor transmits data uploaded by the terminal to a service server; the service server stores the initial vehicle state data into a database; the service server calculates a driving behavior analysis result; after the driving behavior analysis result is obtained, a monitoring work station is informed of the driving behavior analysis result; after driving behavior analysis result is obtained, the terminal is informed of the driving behavior analysis result; and the driving behavior analysis result is stored in the database. According to the invention, in a driving behavior analysis model generation process, many factors such as different road conditions, weathers, different road segments and different drivers are considered, and the rationality of practical application of an original single driving behavior analysis model is improved.

The invention discloses an intelligent three-view linkage method and an intelligent three-view linkage system for a production line. The intelligent three-view linkage method includes the steps of acquiring design requirement information of the production line, subjecting a simulation system to three-dimensional modeling, setting up production line simulation model views, setting up or partially setting up the production line or unit physical system views and establishing configuration monitoring views; developing a management and control system, setting up a control network and establishing data and information channels between the management and control system and the control network. The intelligent three-view linkage method is capable of driving physical equipment, configuration monitoring interfaces and a simulation model to move simultaneously through data synchronization so as to achieve synchronous linkage of three views. An integrated platform integrating design, assembly, debugging, optimization and monitoring of the production line is achieved by means of the three-view linkage. The intelligent three-view linkage method for the production line has the advantages that all units are subjected to unit testing and integrated testing in a production line design and manufacturing process, so that production design schemes are optimized timely, a debugging period is shortened, input cost is reduced and value chains of a whole enterprise are superposed together effectively.

The invention puts forward a synonym expansion method and device for search information. The method comprises the following steps that: carrying out word segmentation processing on the search information to obtain at least one segmented word of the search information; obtaining the candidate synonym set of the segmented word, wherein the candidate synonym set comprises at least one synonym of thesegmented word; forming a synonym pair which contains the synonym and the segmented word by aiming at each synonym; carrying out feature extraction on the synonym pair to obtain a synonym pair featureset; according to the feature set, predicting the synonym pair to obtain a target probability that the synonym pair is predicted as reasonable replacement; and if the target probability exceeds a preset threshold value, forming a synonym expansion item by the segmented word and the synonym, and searching and obtaining a search result on the basis of the synonym expansion item. Through the method,synonym replacement rationality and accuracy can be improved, the recall rate and the accuracy of a search result are improved, and therefore, the technical problems in the prior art that synonym replacement is inaccurate and a search result recall rate is poor can be solved.

The present invention discloses a human body behavior prediction method based on human body skeleton movement information, comprising the following steps: calculating a normalized relative orientative feature of each articulation point of each limb by using human body skeleton information extracted from an RGB D image; carrying out dynamic segmentation on a feature sequence by using a segmentation method based on feature sequence potential difference so as to acquire a posture feature sub-sequence and an action feature sub-sequence; extracting a key posture and an atomic action from the posture feature sub-sequence and the action feature sub-sequence, and constructing a multi-layer graph model based on the key posture and the atomic action; extracting a human body sub-behavior pattern contained in the multi-layer graph model, and constructing a context probability statistical model of the human body sub-behavior pattern; and carrying out identification and prediction of the human body sub-behavior pattern. The human body behavior prediction method based on the human body skeleton movement information has strong robustness for body differences, spatial position differences and the like between different individuals, has strong generalization capability for action differences between different individuals in the same category of behaviors, and has strong identification capability for the action similarity between different categories of behaviors.