181 results about "Temperature correction" patented technology

The invention discloses a heat pump environment temperature self-adaptive regulation and control system oriented to peak-valley electricity price difference, and relates to the technical field of environment temperature regulation and control, and the system comprises a disturbance recognition module, a sampling scheduling module, a temperature correction module, a multi-source checking module, a regulation and control inhibition module and a self-optimization feedback module. And the change rate feature, the frequency spectrum mutation feature and the temperature measurement probe self-heating feature of the continuous external environment temperature sequence are extracted, a sampling risk index is generated, and a rapid oscillation mark is formed. Through adaptive sampling, probe self-heating compensation, multi-source consistency checking and feedback optimization mechanisms, dynamic response of the heat pump system to environment changes is achieved, data accuracy and control decision reliability are improved, and stability, energy saving performance and comfort control capacity under complex working conditions are remarkably enhanced.

The invention discloses an infrared calibration temperature measurement method based on a multi-component insulating gas multispectral imaging device, belongs to the technical field of electric power safety detection, and solves the problem of how to improve the temperature measurement precision of electric power equipment. The non-uniformity correction calibrates the response and bias of each pixel to the same numerical value, the temperature correction eliminates the influence of the lens temperature and the movement temperature on the received electric signal, the shading shutter correction ensures the accuracy and consistency of the shutter or the shading system, the radiation calibration is adopted to convert the measured blackbody voltage value into the temperature value, and the temperature value is converted into the temperature value. The real temperature of the surface of the detected electrical equipment is calculated by combining the temperature value after radiometric calibration conversion, the influence of the atmospheric environment on temperature measurement is eliminated, and the temperature measurement function of the electrical equipment based on an infrared multispectral imaging detector for insulating gas leakage in a complex environment can be realized. And a foundation is laid for further forming portable power multifunctional monitoring.

The invention discloses heat supply equipment based on computing power and a control method, and belongs to the technical field of heat supply control. The method comprises the following steps: acquiring heat supply data, and performing anomaly detection on the heat supply data; when the heat supply data is not abnormal, the distribution condition of the hot water in the heat supply pipe network is analyzed, and a flow analysis result and a pressure analysis result are obtained; optimizing the operation parameters of the heat supply network, and calculating the heat recovery efficiency of the heat supply network; constructing and training an autoregressive integral moving average model, inputting current power utilization related data and heat recovery efficiency, and outputting a thermal load demand prediction value; influence weights of the indoor temperature and the outdoor temperature on the thermal load demand are determined, a temperature difference is calculated, a temperature correction coefficient is calculated according to the temperature difference, and a thermal load demand prediction value is adjusted by using the temperature correction coefficient; setting a power corresponding relation, and adjusting the power of the electric boiler by stages; the operation time and the stop time of the electric boiler are calculated according to the operation state data of the electric boiler, and the electric boiler is set according to the operation time and the stop time obtained through calculation.

Provided is a temperature measurement device for, in a situation where the temperature of a silicon wafer which is a measurement target is indirectly measured, removing, from actually measured radiance, the effects of radiance coming from a chamber member, and calculating the amount of change in the temperature of the measurement target. The temperature measurement device comprises: a chamber for accommodating a measurement target object; a heating unit; a chamber window at a position in the chamber opposite from the measurement target object; a temperature measurement unit for measuring the temperature of the measurement target object and the chamber window; and a computation unit for calculating the temperature of the measurement target object from detected values of the temperature measurement unit. The computation unit is provided with: a conversion unit for generating, from actually measured temperatures calculated from the detected values of the temperature measurement unit, conversion data pertaining to the amount of change in the temperature of the measurement target object corresponding to the amount of change in the temperature of the chamber window; a condition acquisition unit for acquiring a condition under which the measurement target object is heated; a detected value acquisition unit for acquiring a detected value of the temperature measurement unit; and a temperature correction unit for estimating the temperature of the measurement target object by using the conversion data to correct an actually measured temperature calculated from the detected value of the temperature measurement unit.

The invention discloses an XBT-T5 observation data deviation analysis and temperature correction method, and relates to the technical field of ocean observation, and the method comprises the steps: obtaining the original temperature observation data of a target sea area based on an XBT-T5 front-end temperature sensor, calculating the depth, generating a temperature-depth profile, and constructing a temperature-depth database in combination with historical depth observation archive data; the method comprises the following steps: synchronously acquiring temperature and depth data by using a CTD temperature-salinity-depth instrument, and carrying out association pairing with a temperature-depth database to generate an XBT-T5 observation data deviation field under the same spatial-temporal scale; based on generation of an XBT-T5 observation data deviation field under the same spatial-temporal scale, designing a dual-channel adaptive encoder, and constructing a temperature-depth collaborative correction model; and according to the temperature-depth collaborative correction model, coupling the temperature-depth database and generating an XBT-T5 observation data deviation field under the same spatial-temporal scale, thereby realizing XBT-T5 observation data deviation analysis and temperature correction. The method improves the quality and application value of observation data.

The present invention relates to the field of water resource monitoring and early warning, and particularly to an intelligent water use monitoring and early warning method based on the Internet of Things. The content includes: obtaining water flow data and temperature data, and obtaining a water flow prediction value through a dynamic weighted sliding window prediction algorithm; calculating a water flow deviation value based on the water flow data and the water flow prediction value; calculating a temperature correction coefficient based on the temperature data, and calculating a comprehensive error value; calculating a risk assessment value based on the comprehensive error value and combining the temperature correction coefficient to evaluate the abnormal risk. It solves the problems that the prediction algorithm adopted by the traditional water use monitoring method is too simple, lacks dynamic adaptability to water flow fluctuations, and is difficult to effectively respond to sudden water flow changes; ignores the influence of external environmental factors on water flow, resulting in large prediction errors; the fixed threshold adopted cannot adapt to different environmental changes and cannot detect abnormal risks in real time and accurately.

The invention discloses a low-temperature correction method for an SF6 density relay, relates to a low-temperature correction technology for a circuit breaker density relay, and aims to solve the problem of measurement misalignment caused by remarkable limitation of an existing correction method for the SF6 density relay. The method comprises the following steps: installing a density relay in a sealing test device, and filling SF6 gas to a standard pressure; placing the sealing test device in a low-temperature environment, selecting at least five temperature points, standing for 1 hour, and recording an indicating value P standard of a standard densimeter and a measured value P1 of a density relay to be corrected; calculating an error value delta P of each temperature point; performing function fitting on the error value delta P and the corresponding temperature T by adopting a quadratic polynomial function, and solving a correction error delta P1; calculating the value P correction of the corrected density relay; and low-temperature correction of the density relay is completed. The beneficial effect is that the monitoring precision in the extremely cold environment is significantly improved.

The invention discloses a multi-meteorological factor mode forecast temperature correction method based on deep learning, and relates to the technical field of meteorological data processing, and the method comprises the steps: collecting multi-meteorological factor data and observation temperature field data, and outputting a meteorological chart structure; inputting the meteorological chart structure into a graph convolutional network for deep feature extraction, and outputting a multi-meteorological factor feature tensor; performing global and local space-time characteristic analysis on the multi-meteorological-factor characteristic tensor through a dynamic gating fusion network, and outputting a fusion characteristic tensor; inputting the fusion feature tensor into a full-connection neural network for nonlinear transformation and dimension mapping to form a temperature correction model of deep learning; performing different model parameter disturbances on the temperature correction model to generate an accuracy index; inputting into a quality detection model for training, and judging the quality of each temperature correction model. According to the invention, through dual-mechanism cooperation of meteorological chart structure construction and dynamic gating fusion, deep feature extraction and adaptive weight fusion of multiple meteorological factors are realized.

The invention relates to the technical field of data processing, in particular to a cold-chain logistics whole-course tracking system and method. Obtaining a fluctuation point according to the discrete characteristic of the temperature time sequence, and obtaining a noise point according to the amplitude characteristic of the fluctuation point and the data difference characteristic of the fluctuation point and the adjacent data point; taking a vacancy moment and a moment of a noise point in the temperature time sequence as a target moment; taking the time period from the target moment to the historical nearest fluctuation point as a first time period, and taking the time period from the target moment to the future nearest fluctuation point as a second time period; when the temperature change trends of the first time period and the second time period are opposite, the correction degree is obtained according to the length features and the data difference features of the first time period and the second time period; and obtaining a correction temperature according to the data change characteristics and the correction degree of the moments before and after the target moment. A correction temperature time sequence is obtained according to all correction temperatures; monitoring is carried out according to the temperature correction time sequence, and the accuracy of temperature correction and temperature monitoring is improved.

The invention provides a power grid photovoltaic output short-term prediction method and system fused with a meteorological time sequence, and relates to the technical field of photovoltaic power, and the method comprises the steps: reading multi-source meteorological observation data of a target region; performing cloud field motion estimation, and establishing a cloud motion vector field; activating a temperature corrector, reading environment temperature and photovoltaic module temperature, constructing a temperature-module efficiency dynamic model by utilizing a temperature reading result and wind speed and wind direction data of a weather station, and establishing a power upper limit correction factor; after an illumination disturbance signal is established by using the cloud motion vector field, a short-time scale dynamic output prediction curve is generated; and performing power grid operation constraint mapping adjustment, and outputting a calibration prediction result. According to the method and the device, the technical problem of low photovoltaic output short-term prediction precision caused by instability and unpredictability due to the fact that photovoltaic power generation is easily influenced by weather changes in the prior art is solved, and the photovoltaic output prediction precision is improved and the power grid dispatching and operation are optimized by fusing the meteorological time sequence.

The invention relates to the field of household appliances, and provides an air conditioner intelligent control method and device.The method comprises the steps that based on a refrigeration mode, whether the set temperature of an air conditioner is larger than a first temperature threshold value or not, whether the humidity is larger than a first humidity threshold value or not, whether the air volume exceeds a first air volume threshold value or not and whether sunlight exceeds a first sunlight threshold value or not are judged; judging whether the sunshine corresponding time is daytime or not so as to determine a corresponding first temperature correction value; based on the heating mode, judging whether the set temperature of the air conditioner is smaller than a second temperature threshold value or not, judging whether the humidity is smaller than a second humidity threshold value or not, judging whether the sunlight exceeds a second sunlight threshold value or not and judging whether the time corresponding to the sunlight is daytime or not so as to determine a corresponding first temperature correction value; and correcting the set temperature of the air conditioner by using the first temperature correction value. The defect that the comfort is poor due to the fact that automatic control cannot adapt to different environments is overcome, the temperature of the air conditioner is automatically adjusted, and the comfort is improved.

The invention relates to the field of detection of temperature measuring devices, in particular to a temperature calibration method and system for a temperature measuring device, and the method is executed in an automatic system, and comprises the following steps: fixing a temperature measuring device to be calibrated and a reference temperature device on a heat conduction substrate in a coplanar manner; the temperature of the cavity is adjusted to a preset calibration point through a temperature control system, and heat balance dynamic judgment is executed; at least two bias currents with different amplitudes are applied to a to-be-calibrated temperature measuring device, corresponding original voltage signals are collected, a zero-power theoretical resistance value for eliminating the influence of the self-heating effect is calculated based on the original voltage signals, a corresponding reference temperature T is adopted as a data pair, parameter fitting is conducted on the resistance-temperature relation model, and the temperature measuring device is calibrated. A temperature correction calculation formula is established, a synthesis uncertainty evaluation model is established, each uncertainty source is analyzed and synthesized, and the synthesis uncertainty is calculated and output. According to the method, the risk of calibration failure caused by thermal stress or environmental interference is reduced.

The invention discloses a flexible inclinometer temperature correction method for monitoring the deflection of a concrete panel, and relates to the field of structural health monitoring, and the method comprises the following steps: S1, collecting the environmental data of the concrete panel, and constructing a structural state feature vector in combination with preset material parameters; s2, establishing a thermal drift correction model, and calculating a thermal drift response value; s3, stripping the original deflection data based on the response value to obtain a real deflection value; s4, calculating a deflection simulation value through finite element simulation, and comparing the deflection simulation value with a true value to obtain a drift prediction consistency residual error; s5, based on the spatial distance between the structural state feature vector and the historical feature vector, reconstructing a deflection correction value by adopting a semantic weighted interpolation algorithm; and S6, dynamically monitoring residual change according to the time window, and updating the thermal drift correction mode. Through multi-source sensing fusion, physical simulation feedback and tensor interpolation reconstruction, the accuracy, stability and robustness of thermal drift correction are effectively improved.

The invention provides a precision compensation method and device for a real-time clock of an electric energy meter. The method comprises the following steps: acquiring the current environment temperature of a to-be-measured electric energy meter; when it is determined that the current environment temperature exceeds a preset normal temperature interval, on the basis of a plurality of preset temperature correction points and compensation coefficients corresponding to the preset temperature correction points, real-time clock correction is carried out on the to-be-measured electric energy meter at the preset temperature correction points in sequence according to the temperature from low to high; wherein the compensation coefficient is obtained by performing polynomial fitting on the original temperature value reading of the sensor corresponding to the preset temperature correction point and a reference temperature value. According to the invention, error transmission during precision compensation is avoided, and the real-time clock precision of the electric energy meter is improved.

The invention discloses a silicon rod surface resistance automatic detection and intelligent correction system and method. The system comprises a measurement execution module, a data processing module, a temperature correction module, an exception handling module and a result judgment module. The measurement execution module accurately positions and measures the temperature and the surface resistance of the silicon rod; the data processing module preliminarily corrects the data and identifies abnormity; the temperature correction module optimizes and corrects the measured value according to the temperature data and the influence curve; the exception handling module automatically retests the exception data; and the result judgment module gives final evaluation. The method sequentially comprises the steps of measurement preparation, data acquisition, primary processing, temperature correction, exception processing and result judgment and uploading. The problems that traditional measurement is greatly influenced by temperature, data deviation is prone to occurring and the automation degree is low are solved, the requirement of detection for the environment can be effectively lowered, energy waste is avoided, abnormal data are automatically recognized and processed, manual intervention is reduced, the detection accuracy and efficiency are improved, quality detection of the silicon rod in photovoltaic production is guaranteed, and the production efficiency is improved. And powerful technical support is provided for development of the photovoltaic industry.

The invention discloses an air conditioner heating temperature compensation method, device and equipment and a medium. The method comprises the steps that if the air conditioner enters a heating mode, the indoor environment temperature, the indoor air outlet temperature, the indoor set temperature and the current freeze-frame air sweeping position of an air deflector are obtained, and the initial heating compensation temperature is determined through a preset temperature compensation model according to the current freeze-frame air sweeping position of the air deflector, the preset temperature compensation model is constructed based on the corresponding relation between the freeze-frame air sweeping position of the air deflector and the operation angle of the air deflector; judging whether the running time of the air conditioner reaches a preset running time threshold value or not; and if yes, the initial heating compensation temperature is corrected through a preset compensation temperature correction model according to the indoor environment temperature, the indoor air outlet temperature and the indoor set temperature, and the target heating compensation temperature is determined. Through a dual temperature compensation mechanism, thermal stratification is effectively restrained, comfort is improved, and energy consumption is reduced.

The invention discloses a temperature correction method and device and a storage medium, and the method is applied to an infrared temperature measurement device, and the method comprises the steps: obtaining the temperature state data of the infrared temperature measurement device, and enabling the temperature state data to be obtained through the temperature difference values corresponding to a plurality of regional environments of the infrared temperature measurement device, the temperature difference value corresponding to the regional environment is the difference value between the real-time temperature of the regional environment and the zeroing temperature of the regional environment at the zeroing moment; based on the temperature state data and a correction reference factor, the reference temperature of the infrared temperature measurement equipment is corrected, and the correction reference factor comprises the current environment temperature sensitivity of the infrared temperature measurement equipment; the environment temperature sensitivity represents the change condition of temperature related data detected by the infrared temperature measurement equipment along with the temperature of the reference area environment of the infrared temperature measurement equipment; and calculating to obtain a temperature measurement value of the infrared temperature measurement equipment by using the corrected reference temperature. In this way, the temperature measurement precision of the equipment can be improved.

The present application relates to the technical field of heat supply balance management, in particular to a heat supply balance management method and system for end user heat supply. The method comprises the following steps: S1, a heat supply global data acquisition model is built, heat supply pipeline data is collected, and an end user list is obtained according to the heat supply pipeline data; outdoor temperature and historical heat supply temperature of each end user are synchronously obtained; independent temperature periods are divided according to the outdoor temperature value; the same heat supply scheme is adopted for classification and elimination of regulation and control interference; temperature differences of different users are compared under the same heat supply condition; exclusive heat loss coefficients of each household are quantitatively generated; heat loss differences caused by floors, orientations and wall heat preservation can be accurately distinguished; user target heat supply temperature is dynamically corrected according to the heat loss coefficient; the temperature correction range of users with large heat loss is increased, and the correction range of users with excellent heat preservation performance is reduced; the uneven heating and cooling problem caused by inconsistent heat dissipation of different houses is solved from the heat loss level of the user itself.

The invention relates to the field of clock frequency compensation, in particular to a clock frequency prediction method based on temperature and aging mixed compensation. According to the method, linear fitting is carried out on the original observation points in the multiple aging rate estimation time periods, local linearization is carried out on the nonlinear clock frequency aging offset process, compared with an overall nonlinear fitting mode, the calculated amount is reduced, potential error accumulation caused by inaccurate models in overall nonlinear fitting can be prevented, and the accuracy of the overall nonlinear fitting is improved. And the fitting accuracy is improved. In addition, piecewise linear fitting can also adapt to dynamic changes of data, and prediction precision is improved. Meanwhile, the temperature correction values of the adjacent reference points are used for estimating the temperature correction values of the to-be-predicted points, and the accuracy is high.

The application provides a temperature control method, device, storage medium and equipment. In the method, a single in-vehicle temperature sensor arranged at a central position in a vehicle obtains an in-vehicle temperature sampling value. According to a current vehicle speed, an outside temperature and an air conditioner cycle state, an air outlet temperature and an illumination intensity of a target temperature zone, a temperature correction value corresponding to the target temperature zone is determined. Then, the in-vehicle temperature sampling value is corrected based on the temperature correction value to obtain a head temperature of the target temperature zone, and the target temperature zone is controlled in temperature based on the head temperature. In this way, the cost of the in-vehicle temperature sensor is reduced, and the accuracy of temperature control of each temperature zone is improved.

The application relates to the correction technical field of a temperature sensor, and discloses a temperature sensor correction method and device, electronic equipment and a storage medium, wherein the method comprises the following steps: obtaining temperature difference values of different preset temperature ranges through a plurality of preset time periods, a comprehensive temperature response model is constructed, a nonlinear characteristic is extracted by using a change value of adjacent temperature difference values, a relational function is fitted, a target temperature difference value of a current time point is dynamically obtained, and the intelligentization and real-time of temperature correction are realized.The application has the beneficial technical effects that the inconvenience of a traditional temperature sensor depending on factory correction is avoided, errors caused by temperature floating in actual application are reduced, and calibration time and cost are reduced.

The application discloses a pipeline temperature measurement temperature correction method, comprising the following steps: performing calibration experiments, obtaining first temperature measurement array data and second temperature measurement array data on the outer and inner surfaces of the pipeline respectively; constructing a thermal physical model of the pipeline to be measured, calculating a first temperature derivative, and obtaining an energy balance equation of the relationship between the inner and outer surfaces of the pipeline; substituting the first temperature measurement array data and the second temperature measurement array data into the energy balance equation to obtain a complete energy balance equation; performing verification experiments, obtaining third temperature measurement array data and fourth temperature array data on the outer and inner surfaces of the pipeline respectively; substituting the third temperature measurement array data into the complete energy balance equation, reconstructing the pipeline inner surface temperature array data and calculating a second temperature derivative; and comparing the reconstructed temperature array data with the fourth temperature array data to calculate errors. The application adopts a reverse heat conduction temperature correction method to correct the pipeline temperature measurement, so that the accuracy and stability of the measurement results are improved.

The invention discloses an air conditioner control method and device, an air conditioner and a storage medium, and relates to the technical field of air conditioners. The air conditioner control method comprises the steps that position information of the space where the air conditioner is located is obtained; when the position information of the space where the air conditioner is located meets the temperature correction condition, the temperature correction value of the air conditioner is determined; the target temperature is corrected according to the temperature correction value, and the corrected target temperature is obtained; and performing temperature control on the air conditioner according to the corrected target temperature. By means of the mode, when the position information of the space where the air conditioner is located meets the temperature correction condition, the temperature correction process is started based on the temperature correction value, the temperature of the air conditioner is controlled, and the problem that due to the fact that the air conditioner cannot know the layout of the space where the air conditioner is located, air conditioner control fails when the air conditioner mistakenly senses the high environment temperature is solved; accurate control over the air conditioner is guaranteed, the situation of large cooling capacity output is avoided, and the user experience is improved.

A temperature control device controls power supplied to a heater based on a temperature estimate value estimated over time so that a temperature control target to which heat propagates from the heater of the fixing unit reaches a preset target temperature. The temperature control device includes a temperature sensor, first and second storage circuits, a temperature difference detection circuit, and a target temperature correction circuit. The temperature sensor detects a temperature of the heater. The first storage circuit stores the temperature estimate value. The second storage circuit stores a sensor temperature. The temperature difference detection circuit calculates an actual temperature rise amount from a temperature difference between the temperature estimate value and the temperature of the heater from the respective storage circuits. The temperature correction circuit performs control such that a target temperature is lowered in accordance with the actual temperature rise amount.

The present application relates to the field of intelligent sensor temperature measurement technology, and specifically to a method, device, and medium for early warning of thermal radiation risk in live working scenarios. The method comprises: determining the temperature deviation of each intelligent sensor based on the average distribution and discreteness of all temperature data of each intelligent sensor in each time period, as well as the distribution of deviation data; determining the temperature variation similarity based on the correlation of all temperature correction data between any two intelligent sensors; determining the temperature offset value based on the average distribution of all temperature variation similarities in each detection area; and determining the total abnormality score of each intelligent sensor based on the abnormality score of the electromagnetic interference vector to determine the risk assessment coefficient and provide early warning of thermal radiation risk in live working scenarios. The present application aims to eliminate the influence of electromagnetic interference on the accuracy of thermal radiation risk early warning and improve the accuracy of thermal radiation risk early warning in live working scenarios.

A fast-response temperature and humidity sensor includes a humidity-sensitive material, a cylindrical frame disk, a temperature sensor, and an MCU with on-chip ROM. The frame disk has multiple deep-groove air channels evenly distributed around its perimeter. The frame disk has a socket for fixing the temperature sensor, which is electrically connected to the microcontroller. The temperature sensor measures the ambient temperature around the temperature and humidity sensor, and the MCU performs temperature correction on the humidity measurement value. The MCU's on-chip ROM stores a standard database containing multiple humidity-sensitive resistance (R)-humidity (H) curves of the fast-response temperature and humidity sensor at different temperatures (T). Based on the measured temperature value (T) and resistance value (R), the MCU looks up the corresponding humidity value (H) in the standard database.

This invention provides a method, apparatus, and system for multi-point temperature correction of an array induction logging tool. The method includes: acquiring measurement signals from the array induction logging tool during temperature changes, the measurement signals being detected by a preset number of temperature sensors; constructing a temperature coefficient matrix for each temperature sensor based on the measurement signal, resulting in a preset number of temperature coefficient matrices; calculating a temperature correction coefficient matrix based on each temperature coefficient matrix; acquiring actual measurement signals from the array induction logging tool downhole, and performing temperature correction on the measured signals based on the temperature correction coefficient matrix. The multi-point temperature correction method for an array induction logging tool provided by this invention can calculate the temperature correction coefficient matrix based on the actual measurement signals and correct the measured signals based on the temperature correction coefficient matrix, thus avoiding errors caused by formation temperature changes and improving the accuracy and reliability of the array induction logging tool.

The invention discloses a photometer detection temperature correction method and system based on machine learning, and belongs to the technical field of data processing. The working environment information of the photometer is comprehensively mastered by acquiring the atmospheric state inversion data, the channel irradiation relation data and the temperature environment change data. The atmospheric state correction viewpoint determined based on the atmospheric state inversion data can balance the measurement result according to the atmospheric state confidence coefficient, and the measurement error caused by the unknown atmospheric state is avoided. The relation correction strategy is determined according to the channel irradiation relation data, so that the channel irradiation disturbance in the temperature environment can be accurately corrected, and the accuracy of channel irradiation measurement is ensured. The temperature sensitivity correlation strategy is determined by means of the temperature environment change data, and adjustment can be carried out according to different temperature sensitivity disturbance types. The temperature correction strategy integrates multiple factors, effectively eliminates the influence of the temperature on the measurement of the multispectral solar photometer, and enables the application data of the multispectral solar photometer in the fields of atmosphere, meteorology and environmental science to be more accurate and reliable.

The invention relates to a temperature correction method based on a full-connection neural network. The method comprises the following steps: constructing an EMFCNN temperature model based on the full-connection neural network; the EMFCNN temperature model is trained, and after training is completed, an EMFCNN 24h highest temperature model, an EMFCNN 24h lowest temperature model and an EMFCNN hourly temperature model are obtained; performing temperature correction based on the EMFCNN 24h highest temperature model, the EMFCNN 24h lowest temperature model and the EMFCNN hourly temperature model; according to the method, deep fusion of spatial features and meteorological elements is realized through station number Embedding coding and mode forecasting element splicing operation, the limitation of a single data source of a traditional numerical mode is broken through, and joint modeling of gridding station features and numerical forecasting data is realized. According to the forecasting element screening strategy based on the temperature local change equation, forecasting day key meteorological element combinations are selected through physical equation constraints, the scientificity of feature selection is improved, and blindness of a traditional machine learning method is avoided.

This application relates to a control method, apparatus, control device, equipment, computer-readable storage medium, and computer program product for a water heater. The method includes: acquiring the outlet temperature of hot water in the heating pipes of the water heater; calibrating the outlet temperature based on outlet temperature correction parameters to obtain a calibrated corrected outlet temperature; the outlet temperature correction parameters are obtained based on the outlet temperature obtained by the hot water flowing through the heating pipes and a reference temperature of the hot water; controlling the operating power of the water heater's heating system according to the target temperature and the corrected outlet temperature, so that the heated corrected outlet temperature reaches the target temperature, wherein the heating system is used to heat the water in the heating pipes. This method enables more precise control of the heating power of the heating system, resulting in a higher consistency between the actual temperature of the hot water to be discharged and the user-set target temperature, thereby improving the user's water comfort.