33results about How to "Achieving Adaptive Optimization" patented technology

The invention provides a high-frequency CRM boost type PFC converter capable of adaptively optimizing the THD (total harmonic distortion) of input current and belongs to the AC-DC power conversion field. According to the high-frequency CRM boost type PFC converter, the THD (total harmonic distortion) of the input current is decreased based on a charge conduction time control mode; a digital table look-up mode is adopted to generate modulation wave signals, charge conduction time control is realized through a preset conduction time data table, and therefore, the problems of poor control precision and high cost of a digital real-time calculation mode of an analog control mode can be solved; all circuits except a modulation wave signal generating circuit, are realized by an analog mode, so that the defect that a digital controller is limited in MHz high-frequency signal response speed can be eliminated, and performance requirements for the digital controller can be lowered; preset limited data in the data table are transformed, so that the charge conduction time control can be adaptively adjusted with input voltage and output power with output power detection not required, and therefore, the THD (total harmonic distortion) of the input current can be adaptively optimized, and system cost can be significantly reduced.

The invention provides a mesh distortion optimization algorithm based on discrete attribute data, comprising the steps of: 1, adopting a seed point method to perform region searching aiming at one discrete attribute value of a mesh to generate a region mesh set; 2, tracking the boundary of the region to generate a region mesh boundary segment set, analyzing the adjacency relations of the segments according to segment coordinates, sequentially connecting the segments end to end, tracking the region mesh boundary to form a polygonal boundary set, and removing the inner boundary by an area sorting method; 3, adopting a five point method to smoothen the curve to form a smooth region boundary under the premise of using the region area as the weight to restrain the smooth movement of the shared region boundary; and 4, adjusting mesh angular points to the corresponding smooth polygon to self-adaptively optimize the mesh angular points. The mesh distortion optimization algorithm based on discrete attribute data implements the self-adaptive optimization of the original mesh angular points, and can be used for solving the problem that the boundary of the model mesh region is saw-toothed and unsmooth.

The embodiment of the invention provides a tobacco process quality control method, system and device and a storage medium, and relates to the technical field of tobacco industry. The tobacco process quality control method is based on a cloud platform and comprises the following steps: acquiring tobacco process data in a production process; judging whether the tobacco process data is abnormal or not, and if the tobacco process data is abnormal, obtaining the tobacco process data again; if the tobacco process data is not abnormal, judging whether the tobacco process data meets the production process technical standard or not, and obtaining a judgment result; and according to the judgment result, calling a corresponding solution from a tobacco industry database. According to the method, through process quality defect control and process parameter self-adaptive deviation rectification, self-adaptive optimization on a process program is realized, the productivity and the production qualityare improved, and meanwhile, the labor cost and the time cost are reduced.

The invention discloses a Spark parameter adaptive optimization method and system, and the method comprises the steps: 1, building a prediction model of Spark task execution time, and training the prediction model through sample data; 2, sequentially decomposing a Spark application to be executed into a job, a stage and a task according to a Spark execution mechanism, allocating each task to eachcore of each Executor node, predicting the execution time of each task by utilizing a task execution time prediction model, simulating the task scheduling process of the Spark stage based on the taskexecution time, and calculating the execution time of the stage under different parameter combinations; and 3, determining a final optimized parameter combination according to the stage execution timepredicted under different parameter combinations. According to the parameter self-adaptive optimization method, the execution time required by each parameter combination in an actual test is avoidedin a prediction mode, so that the feasible parameter self-adaptive optimization method is realized.

The invention provides a game optimization method, a game optimization device, a mobile terminal and a computer readable storage medium, and the method comprises the steps: monitoring a game application program when the mobile terminal operates the game application program; if it is monitored that a to-be-optimized scene appears in the game application program, generating a preset key event signal, wherein the to-be-optimized scene is a scene meeting a preset triggering condition, and the key event signal is used for notifying a system of the mobile terminal that optimization operation needs to be conducted currently; and optimizing the game application program of the mobile terminal according to a preset optimization strategy based on the key event signal. Through the scheme of the invention, the method can be decoupled from a signal sent by a game manufacturer, achieves the adaptive optimization of a game, and improves the stability of the game and the fluency of user operation.

The invention discloses a phased array antenna directional pattern performance parameter optimization method and an electronic device. The method includes the following steps that: the performance parameter of the directional pattern of a phased array antenna is determined; an objective function corresponding to the performance parameter of the directional pattern of the phased array antenna is determined; the attenuation value of the T/R component of the phased array antenna is obtained, and the change value of the objective function corresponding to the attenuation value is obtained; and an optimal amplitude weighted iteration direction is determined based on the change value of the objective function. With the method provided by the invention adopted, the technical problem that the directional pattern performance parameter of an active phased array antenna in the prior art does not satisfy actual demands can be solved.

The invention discloses a game optimizing method, a game optimizing device, a mobile terminal and a computer readable storage medium. The game optimizing method comprises the following steps: based onpreset first period time, periodically calculating the average image rendering frame rate of a graphics processing unit (GPU) of the mobile terminal within the preset time period; updating the current resource optimizing strategy based on the current average image rendering frame rate, wherein for the resource optimizing strategy, the resource parameter information of the mobile terminal is configured; and optimizing the resource of the mobile terminal according to the current resource optimizing strategy. Through the technical scheme, decoupling with a signal sent by a game manufacturer canbe realized, meanwhile, the resource optimizing strategy is dynamically updated based on the image rendering frame rate of the mobile terminal, so that the self-adaptive optimization of the game is realized, and the stability of a game and operation fluency of a user are promoted.

The invention relates to a self-adaptive parameter setting method and device for an active-disturbance-rejection controller. The method comprises the steps: setting uo initial parameters of a linear active-disturbance-rejection controller according to the order of a controlled system; initializing an environment and network parameters in the DQN; according to the initial parameters and the network parameters, adopting an epsilon-greedy strategy to carry out experience accumulation, and storing experience samples in a memory playback unit; training the network by using the experience samples in the memory playback unit to obtain a decision network; and selecting controller parameters by using the trained decision network. The parameter adaptive optimization of the active disturbance rejection controller is realized, the control performance of the controller is improved, the controller obtained through the technical scheme provided by the invention can adapt to control under different working conditions, and the robustness of the controller is improved. Intelligentization of the controller is achieved, and decisions can be made according to the system state on the premise of not depending on model information.

The invention discloses a model updating method and device, and belongs to the field of AI. The method comprises the following steps: obtaining exception explanatory information, the exception explanatory information being explanatory information for explaining content exception, and the explanatory information being information for explaining an output result of a machine learning model; adjusting a training sample set of the machine learning model based on the abnormal interpretive information; and obtaining an updated machine learning model, wherein the machine learning model is obtained by training based on the adjusted training sample set. The reliability of the updated machine learning model can be improved.

The invention discloses a method for adaptive optimization of power supply decision-making of a photovoltaic building power supply system. The method comprises the three steps including quantification of preventive and post-accident power supply control costs of the photovoltaic building power supply system, optimization model building and solution and simulated analysis on the optimization model. Based on the coordinated optimization theory, a mathematical model for adaptive optimization of power supply decision-making of the photovoltaic building power supply system, and based on the sensitivity of cost to parameter, the optimization algorithm of the optimization direction is guided to solve the model, so that the economical efficiencies of various power supply control schemes are quantified, and sensitivity analysis on the influence from the preventive and the post-accident controlled quantity to the power supply decision-making is carried out so as to provide decision-making reference to economical operation and reliable power supply of the photovoltaic building power supply system. Therefore, the method provided by the invention is a simple and efficient decision-making optimization method.

The invention discloses a multi-dimensional dynamic interleaving device for multi-antenna scatter communication, and belongs to the technical field of wireless communication and scatter communication.Adaptive coded modulation, interleaving, spatial mapping, frequency conversion and amplification are carried out at a sending end, and conversion from a baseband channel to an analog signal is realized; after the signals are converted into baseband signals through frequency mixing, amplification and channel equalization at a receiving end, a proportional relation and a distribution relation of channel quality and signal-to-noise ratio of each channel are obtained by utilizing a multi-dimensional channel state feedback device; an interleaving/de-interleaving matrix is obtained by utilizing a dynamic interleaving rule planner, and finally optimization of interleaving and de-interleaving rules is realized, so that the bit error rate can be improved by two orders of magnitudes, and a good transmission effect is realized. The multi-dimensional dynamic interleaving device can be used for high-speed information transmission under a beyond visual range fading channel, and is particularly suitable for a multi-input multi-output multi-antenna scattering communication system.

The present invention discloses a double-factor adaptive judgment system of telecontrol uplink communication enabling time. The system includes a data object model defining module, a database real-time maintenance module and an uplink channel protocol module; the data object model defining module is used for adding a database construction preparation attribute in the initialization of a data object model; the database real-time maintenance module is responsible for maintaining the database construction preparation attribute of the data object; and the uplink channel protocol module is used for scanning the database construction preparation attributes of all related data objects at a current channel, performing overtime calculation according to the uplink communication enabling time threshold value of the channel, and deciding whether to enable uplink communication. With the system adopted, problems such as low efficiency, low adaptability and requirements for extra configuration work of a telecontrol uplink communication device can be solved. The invention also discloses a double-factor adaptive judgment method of telecontrol uplink communication enabling time.

The invention discloses a public space thermal environment air conditioner control device and method. The device comprises a plurality of clients which form an intelligent group, wherein the clients are used for collecting thermal comfort feedback information of a user and sending the thermal comfort feedback information to the server; a temperature and humidity monitoring module which is used for collecting current temperature and humidity information of indoor and outdoor environments of the public space and sending the current temperature and humidity information to the server side; the server which is used for performing decision processing on the received thermal comfort feedback information of the user and the current temperature and humidity information of the internal and external environments of the public space, generating an infrared control instruction and sending the infrared control instruction to the infrared control module; and an infrared control module which is used for converting the received infrared control instruction into an infrared control signal and sending the infrared control signal to the air conditioning system so as to control and adjust the air conditioning system. According to the invention, the clients are adopted to form an intelligent group, so that self-adaptive optimization, energy conservation and efficiency improvement of group thermal comfort are realized, and thermal requirements of residents in a single or multiple occupied spaces are met.