64 results about "Climate system" patented technology

The invention relates to the technical field of urban climatic science, in particular to an urban climatic environment rapid evaluation system and method. According to the technical scheme, the system comprises a data acquisition module, an index standardization and feature extraction module, an index weighting and dynamic parameter adjustment module and a climatic environment comprehensive index generation module. According to the method, based on meteorological and environmental multi-source data of an urban area, a multi-dimensional evaluation index set is firstly constructed through standardization and normalization processing, and then a fuzzy logic harmonic function and a non-linear harmonic function are utilized to identify the coupling relation and the cooperation strength among the indexes; and meanwhile, a dynamic optimization mechanism is introduced to adaptively adjust each weight coefficient according to the real-time index sensitivity, an urban climate environment index is finally generated, and spatial visual expression and grade early warning are realized. According to the method, rapid evaluation and trend judgment of the urban climate system state can be realized, and the method is suitable for urban planning, climate risk monitoring and toughness analysis.

The invention provides a greenhouse climate prediction control method and device, electronic equipment and a storage medium, and relates to the technical field of agriculture, and the method comprises the steps: obtaining climate data and crop data in a greenhouse, and carrying out the multi-source data fusion, and obtaining multi-source fusion data; according to the multi-source fusion data, taking a crop growth state as output, training and verifying a deep neural network, and obtaining a nonlinear dynamic model of the greenhouse climate system; through a Bayesian inference technology, taking parameters of the nonlinear dynamic model as random variables, taking climate data inside and outside a greenhouse as observation data, and establishing posterior distribution of parameter uncertainty, so as to obtain a posterior distribution model of output uncertainty; establishing an optimization problem of a multi-target random opportunity constraint MPC according to a nonlinear dynamic model of a greenhouse climate system, a posterior distribution model of parameter uncertainty and targets of a greenhouse production system; and solving to obtain control input and a control strategy of the greenhouse.

A roof-mounted unit for a roof-mounted air conditioner, wherein the roof-mounted unit is arranged on an exterior wall surface of a roof, characterized in that the roof-mounted unit comprises a top cover and a base plate assembly (1), wherein the base plate assembly (1) comprises a base plate (2) and a cover element (3), and when the top cover is attached to the base plate assembly (1) and the roof-mounted unit is arranged on the roof, the cover element (3) covers at least a portion of the surface of the base plate (2) that is exposed outside the top cover and the roof, wherein the base plate (2) is provided with a snap-in fastener (21) extending outwards from a base of the base plate (2), and wherein the cover element (3) has a bottom provided with edges (31), wherein the snap-in fastener (21) interacts with the edges (31) to secure the base plate (2) and the cover element (3).and wherein the underside of the cover element (3) is provided with a pull cord (32, 33) extending between the edges (31), and wherein the base plate (2) is provided with a recess (22, 23) for receiving the pull cord (32, 33).

The invention discloses a construction method of an earth system coupling device and the earth system coupling device, and the construction method comprises the steps: a first component module construction step: constructing a plurality of first component modules of a global climate system based on full coupling, the plurality of first component modules comprise an atmospheric component module, a land component module, a sea ice component module, a ground ice component module, a river component module, a first ocean component module and a sea wave component module; a second component module construction step: constructing a second component module based on the ocean circulation simulation system, wherein the second component module is a second ocean component module; a replacement step: replacing the first ocean component module with the second ocean component module; and a coupling step: reconstructing a coupling application interface of the coupler of the global climate system based on full coupling, and carrying out data exchange and interaction among different component modules through the coupling application interface.

The invention provides a long-term climate prediction method based on a dynamic graph neural network model, and belongs to the technical field of deep learning and time series prediction.The long-term climate prediction method comprises the steps that firstly, a climate time series is acquired, and climate data sets suitable for training are constructed and comprise a training set, a verification set and a test set; inputting the climate time sequence into a deep learning model, simulating complex spatial-temporal characteristics among climate elements, and generating future long-term climate prediction data; adjusting parameters according to the expression of the model on the verification set; testing the model on the test set, calculating an error between a prediction result and real climate data, and further optimizing the model through an error feedback mechanism; according to the method, the complex time-space relationship in the climate system can be effectively modeled, so that high-precision long-term climate prediction is realized; compared with an existing method, the method has the advantages that the method is excellent in long-time-span climate prediction task, and a more valuable climate prediction service is provided for practical application.

The invention discloses a statistical correction method for land water resource availability simulation data, and belongs to the technical field of climate data analysis. Constructing a space-time distribution simulation capability evaluation model, screening out a global climate system mode with a relatively good simulation effect, and determining historical simulation data # imgabs0 # and future simulation data # imgabs1 #; a cumulative distribution function is established, and the variable quantity and the change rate from historical simulation data # imgabs2 # of the same quantile to future simulation data # imgabs3 # are quantized; selecting a mode simulation trend storage mode, and obtaining deviation-corrected future simulation data # imgabs4 # by using a quantile mapping method; and sequencing the future simulation data # imgabs5 # subjected to deviation correction to obtain future simulation data # imgabs6 # based on a time sequence, and performing deviation correction on the multi-period simulation data to form a perfect historical simulation data set and a future simulation data set. According to the method, the WA simulation precision is fundamentally improved by taking the WA as a correction target variable, the statistical correction effect of the quantile mapping method on the WA variable is analyzed, and most climate scale research requirements are met.

The invention provides a water-wind-light power multi-target interval forecasting method considering forecasting error complementarity, and the method comprises the steps: arranging the historical monthly scale data of a selected water-wind-light complementary system, including water-electricity power time sequence data, wind power time sequence data, photoelectric power time sequence data, total power time sequence data and various climate system indexes; the method comprises the following steps of: calculating correlation among a climate system index, hydroelectric power, wind power, photoelectric power and total power by adopting a maximum mutual information coefficient method in consideration of various time lags, screening forecast factors corresponding to the power on the basis, and screening the forecast factors corresponding to the power in consideration of complementarity among the hydroelectric power, the wind power and the photoelectric power. And constructing a point forecasting and interval forecasting model based on a deep learning model, performing accumulated forecasting on the total power after performing independent forecasting on each power, and performing combined forecasting on the total power after accumulating each power. According to the method, the complementarity of forecasting errors is considered, so that the forecasting precision of each power of the water-wind-light system is improved.

Air conditioning unit, including: a housing comprising a first chamber and a second chamber separated from the first chamber by a partition arranged in the housing, the housing having an air inlet and an air outlet; a coolant circuit which includes a compressor located in the first chamber; an airflow path extending through the second chamber, wherein the airflow path is arranged to direct an airflow from the air inlet to the air outlet, a blower arranged in the airflow path; a coolant leak detection system designed to detect a coolant leak within the housing; and an inducer arranged in the housing, wherein the inducer is configured to move air from the first chamber into the airflow path when the coolant leak is detected by the coolant leak detection system.

A closed-loop climate system including a water tank; cooling pads positioned above the water tank, a thermoelectric unit (TEU) connectable to a power supply, and configured to cool / heat water received from the water tank, a sprinkler tube positioned above the cooling pads and configured to sprinkle the water heated by the TEU onto the cooling pads.

The invention belongs to the technical field of hydrology and water resource and climate prediction crossing, and discloses a medium-and-long-term runoff prediction method fusing a data enhancement technology and a machine learning model, which comprises the following steps: collecting runoff data and climate system index data of a target area, performing factor screening by adopting a replacement accuracy method, the method comprises the following steps: dividing data into a training set and a test set, constructing a time lag factor, carrying out SMOTE data enhancement on the training set, carrying out runoff prediction model construction by using a support vector machine regression model, carrying out parameter optimization by using grid search, calculating an evaluation index to carry out model performance evaluation, and finally predicting and outputting a medium and long-term runoff time sequence according to the model. The method effectively solves the problem of low prediction precision caused by data scarcity and insufficient factor selection in a traditional method. The method overcomes the problems of data scarcity, imbalance and insufficient model generalization ability in medium and long term runoff prediction, and has wide application prospects in the fields of medium and long term runoff prediction and water resource management.

The application discloses a filtering method in marine climate research and application thereof, and comprises the following steps: (1) Fourier transform is conducted on time or space data x to obtain results in a frequency domain or a wave number domain; (2) a function is used to conduct a truncation processing on the frequency domain or the wave number domain, and low-pass and high-pass filtering frequency domain results are obtained respectively; (3) energy of the low-pass and high-pass filtering results is calculated and analyzed; (4) inverse Fourier transform is conducted on the low-pass filtering frequency domain or wave number domain result, and a large-scale characteristic distribution in the time or space domain can be obtained; (5) when the filtering result meets a filtering quality index in the frequency or wave number domain obtained in the step (3) by 20%, the function parameter in the step (2) belongs to a range of function parameters suitable for scale division; and (6) the filtering result is brought into a marine climate system of the earth to improve accuracy. The application aims to provide a filtering method and application for judging and improving scale division accuracy in marine climate research.

While a speed of a first compressor during operation is less than a threshold speed, a speed of a second compressor during operation is prevented from falling below a minimum threshold speed that is defined by a sum of the speed of the first compressor and a predefined offset speed delta such that the minimum threshold speed changes as the speed of the first compressor changes.

Carbon dioxide air conditioning system comprising a cooling device (2) with a refrigerant circuit (3), wherein carbon dioxide (K) is incorporated as a refrigerant in the refrigerant circuit (3) and wherein the refrigerant circuit (3) comprises means for evaporating and condensing the carbon dioxide (K).

A method for determining a setpoint heat transfer rate. The method comprises receiving a cabin temperature and an input of a human-machine interface and / or an autonomous climate system, detennining a current heat loss of an occupant based on the cabin temperature, detennining a desired heat loss of the occupant based on the input, and detennining the total setpoint heat transfer rate based on the current and desired heat losses.

The invention provides a system modeling method and device based on multi-time scale characteristics, equipment and a medium, and relates to the field of data processing. The method comprises the following steps: determining a to-be-modeled target system and target parameters in the target system, wherein the target system (such as a climate system) is used for predicting a state value of the target parameters at any moment; acquiring sample track data of the target parameters changing along with time; according to the sample trajectory data, obtaining feature representations of the target parameters on a plurality of different time scales; determining an initial value of a slow variable and an initial value of a fast variable corresponding to the target parameter according to the plurality of feature representations; and training the target system according to the initial value of the slow variable, the initial value of the fast variable, the normal differential equation corresponding to the slow variable and the normal differential equation corresponding to the fast variable. According to the method, a complex system (target system) with significant multi-time scale characteristics can be modeled, so that the target system can accurately predict the system state.

The invention relates to a climate control system (1, 1a) for a vehicle (12), comprising a multi-zone climate control system (3, 3a) which has a first air outlet element (4) for releasing pre-set tempered air into a first zone (5) and at least a second air outlet element (4a) for releasing pre-set tempered air into a second zone (5a), wherein a sensor system (2, 2a) is provided at least for detecting a driver as driver data and an existing passenger as passenger data, and wherein an evaluation unit (7, 7a) is provided for evaluating the driver data as driver state and driver face position and existing passenger data as passenger state and passenger face position, wherein the multi-zone climate control system (3,3a) designed to generate and adjust a first temperature of the exhaust air into the first zone (5) based on the driver's condition and to generate and adjust a first blower direction of the exhaust air by means of the first air guide elements based on the driver's face position, and to separately generate and adjust a second temperature of the exhaust air into the second zone (5a) based on the passenger's condition and to generate and adjust a second blower direction of the exhaust air by means of the second air guide elements based on the passenger's face position.

Disclosed are climate systems for vehicles and methods for controlling the climate systems. In some implementations, a climate system includes: (1) a temperature sensor configured to measure a temperature within the compartment of the vehicle; (2) a first compressor powered by an engine of the vehicle to compress a refrigerant; (3) a second compressor driven by an electric motor to compress the refrigerant; and (4) a controller electrically coupled to the first compressor and the second compressor. The controller configured to: (1) calculate a thermal load of the compartment based on a difference between a desired temperature and a measured temperature; and, (2) based on the calculated load, selectively activate: (i) the engine, (ii) the first compressor, and / or (iii) the second compressor.

The application relates to the field of atmospheric science and discloses an El Nino event identification and La Nina transition early warning method, equipment and medium. The method uses the sea surface temperature and the near-surface 2-meter air temperature data in the fifth-generation atmospheric reanalysis product ERA5 of the European Centre for Medium-Range Weather Forecasts, calculates the lag cross-correlation coefficient between the sea temperature grid points and the air temperature grid points, and constructs a directed network between the global air temperature and the equatorial mid-east Pacific and equatorial mid-Pacific sea temperature. The average link strength is used to quantify the importance of the air temperature node, the spatial and temporal changes of the link number and the link strength are combined, the key area with a leading response to the El Nino is identified, and the transition of the El Nino event to the La Nina event is early warned. The application helps us to deeply understand the influence of the El Nino event on the global climate system, improves the prediction accuracy of the La Nina event, and thus provides a scientific basis for the formulation of disaster prevention and response strategies.

A climate-controlled freight container (10) comprises a casing (12), enclosing a cargo compartment (20) and a control compartment (26). The container further comprises a climate system (30) that has at least two climate modules (40) and an air distribution arrangement (21), configured to distribute air from the climate system into the cargo compartment and. A central climate-control unit (52) is configured for collection of measurements associated with climate conditions of the cargo compartment and for controlling the climate system. Each of the climate modules is configured for adapting climate properties of air flowing through the climate modules from a return air plenum (36) to a supply air plenum (34). Each of the at least two climate modules comprises a local climate-control unit (46), configured for controlling an operation of the climate module. The central climate-control unit is configured for providing operational instructions to the local climate-control units.

The invention discloses a method and a system for constructing a climatic change comprehensive evaluation model E3METL. The method comprises the steps that the model CE3METL takes a lambda endogenous economic growth model as a kernel and is completed by coupling an energy system and a simple climatic system, and the specific construction steps are as follows: constructing an input-output relationship of an economic department based on a lambda endogenous economic growth theory; an investment consumption relationship; a traditional Cobb-Douglas production function is improved, and energy serves as independent input to be introduced into an input-output relation; the method comprises the following steps: introducing technical cost, carbon tax, subsidy and other emission reduction policy variables, modifying a classical Logistic technology diffusion curve, considering the resource potential of each technology, and constructing a Logistic curve group to describe the multi-energy technology evolution; and developing a two-factor learning curve based on the'dry middle school 'and the'research middle school', so as to describe the progress of the endogenous technology. The method and the system for constructing the climatic change comprehensive evaluation model E3METL have a wide market prospect.

The invention discloses a method for analyzing long-term response of ozone in the Antarctic stratosphere to high-energy particle sedimentation, which comprises the following specific steps: firstly, acquiring vertical distribution characteristics of ozone from the Antarctic stratosphere to the middle layer from January to December in 30 years, and drawing a historical vertical distribution diagram; compiling a special method technical scheme for analyzing the long-term response of the ozone in the Antarctic stratosphere to the sedimentation of the high-energy particles, and carrying out technical disclosure to workers; then, the geomagnetic index is adopted as an agent index of high-energy particle sedimentation, a unary linear regression model of the southern hemisphere winter atmospheric variable is established, and the regression model is shown in the specification. The process that high-energy particles are settled and generated and conveyed to the stratosphere through polar region vortex and the ozone loss chemical process of the high-energy particles can be quantitatively analyzed, and the potential influence of extreme space weather events on an earth climate system can be conveniently evaluated.

The application relates to the technical field of data processing, and discloses a hydrological climate element history sequence reconstruction method based on multi-layer nested coupling, which comprises the following steps: unifying the time resolution of multi-source substitute data and observation sequences; performing adaptive noise complete ensemble empirical mode decomposition, recombining to generate high-frequency layer and low-frequency layer control sequences; calculating cross wavelet power spectrum, extracting instantaneous phase difference sequences and wavelet square coherence sequences; constructing a nested coupling regression benchmark model, calculating dynamic high-low frequency regression coefficients and generating a two-dimensional system lookup table; using the two-dimensional system lookup table to obtain regression coefficients of a history period, combining with coherent logic gate control sequences generated by the wavelet square coherence sequences to process distorted data, and outputting reconstructed sequences. The application isolates the interference of signals of different frequency bands, adapts to the time-varying properties of climate system parameters, and improves the reconstruction quality of long-term trends and short-term fluctuations.

This invention discloses a climate prediction method and apparatus based on observation constraints and a multi-time-dependent sliding window. The method includes: acquiring the first climate data for the current and historical years predicted by a specified climate system model; for each month in the historical year: using the first climate data of that month and a predetermined number of previous months as input features, and the actual climate data of that month as labels, generating sample pairs for that month and adding them to a training sample library; training a pre-constructed climate prediction model using the training sample library with the objective of minimizing the joint loss, the joint loss including the root mean square error, spatial anomaly correlation coefficient, and prediction score characterizing the model's prediction performance; for any month to be predicted in the current year: inputting the first climate data of that month and a predetermined number of previous months into the trained climate prediction model, and outputting the climate prediction result for that month. This invention improves the reliability and fine spatiotemporal resolution of climate prediction.

The invention comprises systems and methods for evaluating changes in the operational efficiency of an HVAC system over time. The climate control system obtains temperature measurements from at least a first location conditioned by the climate system, and status of said HVAC system. One or more processors receives measurements of outside temperatures from at least one source other than said HVAC system and compares said temperature measurements from said first location with expected temperature measurements. The expected temperature measurements are based at least in part upon past temperature measurements.

An air conditioning device (1) comprises an air conditioning housing (12) defining an air passage (120) through which ventilation air flows to a climate control target room, and an air cooler (16) located within the air conditioning housing to cool the ventilation air by absorbing heat from it. The air conditioning device further comprises a blower fan (18) located within the air conditioning housing on the downstream side of an airflow from the air cooler to generate an airflow that passes through the air cooler, and a resonator (50) located outside the air passage. The resonator has a cavity section (52) having a predetermined volume and a connecting section (54) that provides a connection between the cavity section and the air passage.The cavity section is provided with a partition component (56, 56A, 56B) that divides an interior of the cavity section into several enclosed spaces, and each of the several enclosed spaces is designed to be connected to the air passage via the connecting section.

The invention relates to the technical field of photovoltaic generating capacity prediction. The invention provides a regional photovoltaic annual generating capacity prediction method and system fused with a climate change trend. The method comprises the following steps: constructing and preprocessing a multi-source data set including historical power generation, historical meteorological observation, climate system mode output and photovoltaic module performance parameters; extracting trend components and volatility components of climate key factors in a future year, and generating a multi-path climate change scene; establishing a component performance attenuation-climatic factor dynamic response model, and outputting a photovoltaic component equivalent power generation efficiency sequence considering a climatic change cumulative effect; based on photovoltaic power station space distribution and landform data, a region-level power generation capacity space-time aggregation model is constructed, and through scale conversion and probability aggregation, a prediction result and a confidence interval of photovoltaic annual power generation capacity of a target region are output. The problem that the long-term prediction deviation is large due to the fact that an existing photovoltaic generating capacity prediction method does not fully consider the future climate change trend influence is solved.

This invention, based on spatiotemporal analysis and deep learning, proposes a joint downscaling method for multiple oceanic elements, belonging to the field of meteorological and climate prediction and data processing technology. It includes: S1, data preparation and preprocessing; S2, multivariate empirical mode decomposition (MEOF); ​​S3, constructing an SRGAN model capable of learning spatial mode mapping relationships at different resolutions; and S4, generation and reconstruction of high-resolution ocean fields. This invention obtains joint spatial modes and time series through multivariate empirical mode decomposition. The model's learning of the joint spatial modes maintains the inherent spatiotemporal coupling relationships between multiple variables. It significantly improves the detail restoration capability of the downscaling results. In adversarial training, the model can generate more realistic and detailed high-resolution spatial structures, effectively capturing complex nonlinear processes in the climate system. It is highly efficient and flexible; after model training, it can quickly downscale long-term, multi-scenario low-resolution data, greatly saving computational resources.

An indoor lighting and climate system includes a plurality of lighting units arranged in a dispersed manner in a room and a control unit arranged to control the operation of the lighting units in relation to preset climate settings and input signals from at least one temperature sensor, wherein each of said lighting units include a cup shaped housing with an opening, a lamp attachment fora lamp, an open inside space between said lamp and said cup shaped housing, and a fan arranged to produce a forced air flow in said space, characterized in that a circumferentially extending inner dividing wall member is arranged within said cup shaped housing, which circumferentially extending dividing wall separates said open inside space from a heat flow channel arranged within said cup shaped housing.

The invention belongs to the technical field of palaeoclimate data assimilation, and discloses an application method of a novel efficient multi-scale coupling assimilation system in iCESM, comprising: acquiring an observation increment at an observation point, and acquiring a projection of the observation increment; solving of observation increment is improved, and updated projection is obtained; an MSHea-EnKF coupling assimilation algorithm is embedded into an earth system mode CESM1.3; and an MSHea-EnKF coupling assimilation algorithm is embedded into an earth system mode iCESM1.3 mode containing isotope change of an f19g16 resolution version. According to the invention, the construction of the novel efficient multi-scale coupling assimilation algorithm MSHea-EnKF in the f19g16-resolution isotope earth system mode iCESM1.3 mode is realized, the multi-scale assimilation function is set to be selectable switch control, the calculation cost can be reduced, and the complex change of the climate system can be accurately captured.

Disclosed are systems and methods that provide a novel framework for a secure, geofenced-based control and management of a thermostat and / or an associated HV AC / baseboard climate system. Activities related to a status, cunent operation mode, temperature control and / or operation / temperature changes can be based on detected user presence / occupancy within a geofenced area that corresponds to the climate system. The disclosed framework can further or alternatively base control and / or management of the thermostat based on whether operational values (e.g., temperatures, for example) conelate with particular deviations from operational settings (e.g., setpoints, for example). Thus, the disclosed framework can enable an automated and / or dynamic operational control of a climate system based on geofenced and current and / or requested operational values.