33 results about "Climate system" patented technology

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.

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).

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 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 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 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.

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.

The application provides a system modeling method and device based on multi-time scale characteristics, equipment and medium, and relates to the field of data processing. The method comprises the following steps: determining a target system to be modeled and a target parameter in the target system, the target system (for example, a climate system) being used to predict the state value of the target parameter at any time; obtaining sample trajectory data of the target parameter changing over time; obtaining feature representations of the target parameter on multiple different time scales according to the sample trajectory data; determining initial values of slow variables and initial values of fast variables corresponding to the target parameter according to the multiple feature representations; and training the target system according to the initial values of the slow variables, the initial values of the fast variables, a neural ordinary differential equation corresponding to the slow variables, and a neural ordinary differential equation corresponding to the fast variables. The application can model a complex system (the target system) with significant multi-time scale characteristics, so that the target system can accurately predict the state of the system.

1. The name of the design product: climate system simulation comprehensive test bench. 2. The use of the design product: for temperature, humidity, low pressure, vibration coupling environment reliability test system. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view. 5. The bottom of the design product is not easy to see or not visible during use, omit the top view.

A closed-loop climate system including a 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 present invention discloses a statistical correction method for terrestrial water resource availability simulation data, belonging to the field of climate data analysis technology. A spatiotemporal distribution simulation capability assessment model is constructed to screen global climate system models with good simulation effects, determine historical simulation data #imgabs0# and future simulation data #imgabs1#; establish a cumulative distribution function to quantify the amount and rate of change from historical simulation data #imgabs2# at the same quantile to future simulation data #imgabs3#; select a model simulation trend preservation method, and use the quantile mapping method to obtain bias-corrected future simulation data #imgabs4#; sort the bias-corrected future simulation data #imgabs5# to obtain time-series-based future simulation data #imgabs6#, and perform bias correction on multi-period simulation data to form a complete historical simulation data set and future simulation data set. The present invention uses WA as the correction target variable to fundamentally improve the WA simulation accuracy, analyzes the statistical correction effect of the quantile mapping method on the WA variable, and meets the needs of most climate-scale research.

The invention discloses a CF3CH2OCF3 based gas composition and a use method of the CF3CH2OCF3 based gas composition. In the invention, in the aspect of environmental friendliness, the global warming potential value is obviously reduced, and the greenhouse gas emission pressure in the semiconductor manufacturing process can be greatly reduced. As an alternative scheme of a traditional high-GWP gas, the application of the gas composition helps enterprises to meet increasingly strict requirements of environmental protection laws and regulations, promotes the electronic manufacturing industry to transform to a green and low-carbon direction and reduces negative effects on a global climate system, and in the aspect of process suitability, the gas composition has good gas-phase stability, and has good application prospects. And compatibility with existing gas delivery and control equipment can be realized. The gas can be directly introduced without large-scale transformation of a production line, the technical threshold and cost input of process switching are reduced, meanwhile, the safety and controllability of the gas in the transmission and storage process are guaranteed, the method is suitable for industrial continuous production scenes, the quality risk of subsequent processes is reduced, and the production yield of semiconductor devices is increased.

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.

Disclosed are climate systems and methods for control the climate systems. A climate system includes a refrigerant circuit, a first compressor, a second compressor, a first refrigerant-to-air heat exchanger, a second refrigerant-to-air heat exchanger, and a controller communicatively coupled to the first and second compressors. Respective outlets of the first and second compressors are fluidically coupled to the first refrigerant-to-air heat exchanger, the first refrigerant-to-air heat exchanger is fluidically coupled to the second refrigerant-to-air heat exchanger, and the second refrigerant-to-air heat exchanger is fluidically coupled with respective inlets of the first and second compressors. The fluidic connection between the second refrigerant-to-air heat exchanger and the first and second compressors includes a vertical split that is configured to mitigate or reduce the amount of compressor oil that migrates to dormant components.

The invention discloses a dynamic game modeling method for a regional environment-climate-economy system, and relates to the technical field of environment-climate-economy coupling modeling. According to the method, a dynamic game model is constructed, Nash equilibrium is solved, the emission reduction effects of regional cooperation and non-cooperation games are quantitatively compared, the optimal path of carbon emission reduction and pollution emission reduction of each region is described, an economic module, a climate module and an environment module are included, and the pollution reduction and carbon reduction synergistic effect and the like are considered. Under the cooperation strategy, all regions cooperate, and the welfare maximization of the whole society is pursued. And under the non-cooperative strategy, the regions do not cooperate, and the social welfare maximization of each region is pursued. The model comprises five sub-models which interact with each other. CO2 and pollutants are generated at the same time through economic activities in all regions; cO2 is discharged to a climate system, and global temperature rise and income loss are caused; pollutants are discharged to an environmental system for regional diffusion and transfer, heterogeneity influence is caused on health of people, and then labor loss is caused; meanwhile, economic cost is generated by carbon emission reduction and pollution emission reduction measures in each region; finally, climate damage, health damage, carbon emission reduction cost and pollution emission reduction cost jointly act on an economic system; and emission synergy and cost synergy of CO2 and pollutants are also considered, so that global carbon emission and pollutant emission of each region under a cooperative situation and a non-cooperative situation can be accurately predicted.

The invention discloses a climate prediction method and equipment based on observation constraint and a multi-aging sliding window. The method comprises the following steps: acquiring first climate data of current and historical years predicted by a specified climate system model; for each month in a historical year, taking the first climate data of the month and a preset number of months as an input feature, taking the actual climate data of the month as a label, generating a sample pair of the month, and putting the sample pair into a training sample library; using the training sample library to train a pre-constructed climate prediction model with minimum joint loss as a target, the joint loss including a root-mean-square error representing model prediction performance, a spatial anomaly correlation coefficient and a prediction score; and for any to-be-predicted month in the current year, inputting the first climate data of the to-be-predicted month and a set number of previous months into the trained climate prediction model, and outputting a climate prediction result of the to-be-predicted month. According to the invention, the reliability and fine temporal-spatial resolution of climate prediction are improved.

Disclosed are systems and methods that provide a novel framework for a decision intelligence (DI)-based computerized framework for computationally controlling and outputting displayed climate information within a smart thermostat in a dynamic, real-time manner. The disclosed framework can be implemented, executed in association thereof and / or integrated into the operation of a smart thermostat enabling the deployment of a user-friendly interface (e.g., a user interface (UI)) that facilitates seamless scrolling through a wealth of data, providing users with comprehensive insights into its features, collected data, and controls. The thermostat interface enables swift compilation, consumption and adjustment of temperature settings, scheduling preferences and operational modes, empowering users to tailor their climate system operation to their exact preferences and lifestyle needs. This, among other benefits, ensures that users can delve into pertinent information and exercise precise control over their indoor climate management with unparalleled ease and efficiency.

Disclosed are climate systems and methods for control the climate systems. A climate system includes a refrigerant circuit, a first compressor, a second compressor, a first refrigerant-to-air heat exchanger, a second refrigerant-to-air heat exchanger, and a controller communicatively coupled to the first and second compressors. Respective outlets of the first and second compressors are fluidically coupled to the first refrigerant-to-air heat exchanger, the first refrigerant-to-air heat exchanger is fluidically coupled to the second refrigerant-to-air heat exchanger, and the second refrigerant-to-air heat exchanger is fluidically coupled with respective inlets of the first and second compressors. The fluidic connection between the second refrigerant-to-air heat exchanger and the first and second compressors includes a vertical split that is configured to mitigate or reduce the amount of compressor oil that migrates to dormant components.

The invention discloses a rainfall dynamic distribution modeling method and system. The method comprises the following steps: S1, grading rainfall according to magnitude; s2, respectively identifying climate driving factors for different grades of rainfall; s3, establishing a time-varying cumulative distribution function of different levels of rainfall and climate driving factor sequences; and S4, based on the time-varying cumulative distribution function, establishing a deep learning fusion model, and predicting future rainfall. According to the method, the credibility of climate system prediction factors can be improved, different levels of rainfall climate driving factors and response rules thereof are disclosed, and the rainfall prediction capability and accuracy are greatly improved.

A control system for dynamic control of a climate system of a vehicle in a pre-conditioning operation mode. The climate system comprises a vent having adjustable flow-direction control, an actuator for adjusting the flow-direction of the vent and a controller. The control is configured to receive an input signal indicative of a request for a pre-conditioning operation mode and determine a dynamic vent control scheme in response to the request. The dynamic vent control scheme defines a plurality of vent flow-directions which are output as actuator control signals to adjust the vent flow-direction in accordance with the dynamic vent control scheme.

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.

Disclosed are systems and methods that provide a novel framework for automatically and dynamically controlling and managing a climate system at a location based on past, present and / or predicted spatial, temporal, logical and / or user / device data at the location. The disclosed framework can maximize the capabilities of an implemented control system (e.g., climate and / or security) to leverage AI / ML and / or LLM predictions via novel mechanisms to understand the current and / or future needs of a user(s) within such location. The framework can enable automated notifications and / or responses to control a current environment of a location, as well as the desired environment of a user at and / or within the location, such that framework can provide, in concert with the control system at the location, a dynamically adaptive, automated system that can leverage generative software to control how climate and / or security systems control an environment tied to the comfort and protection of a locations' occupants.

The present application relates to a kind of greenhouse gas influence temperature seasonality elasticity index method of evaluating, steps include: 1) determining research area, research time, obtain human radiation forcing index, meteorological element index and climate system index and carry out pretreatment;2) determine the spatio-temporal variation of temperature seasonality in research time;3) using human radiation forcing index, meteorological element index and climate system index to the spatio-temporal variation of temperature seasonality is attributed;4) using human radiation forcing index, meteorological element index and climate system index to the contribution of temperature seasonality assesses the influence of greenhouse gas on temperature seasonality.This method can effectively solve the limitation that human radiation forcing and natural factors are not considered in the commonly used temperature seasonality attribution method, cannot be used to research and judge how temperature seasonality changes with greenhouse gas emissions, has wide application in vegetation phenology, livable temperature and ecosystem service and the like.

Climate control system for a vehicle (1, 1'), comprising: - a climate bus (41); - an air conditioning system (30), in particular a heater (30); - a control element (2) for setting a target temperature value of the air conditioning system (30); - a gateway device (60) which is connected to the climate control device (30) via the climate bus (41), where The gateway device (60) is configured to communicate as a master on the climate bus (41) and includes a control device (66) for controlling the climate control device (30), and the gateway device (60) generates control commands that are sent via the climate bus (41) to the climate control device (30) in order to control the climate control device (30) in such a way that the temperature in the vehicle interior corresponds to the set temperature value.