211 results about "Microclimate" patented technology

The invention discloses a photovoltaic power generation power prediction method and system based on multi-source data fusion. The method comprises the steps of obtaining historical operation data of a target photovoltaic power station and historical meteorological data corresponding to the historical operation data; based on the historical operation data and the historical meteorological data, constructing and training a historical deviation mode correction downscaling model, and correcting future coarse resolution meteorological forecast data provided by a numerical weather forecast model to obtain refined meteorological forecast data of a target photovoltaic power station site scale; on the basis of the refined meteorological prediction data, utilizing a physical-statistical coupling prediction model to predict the future generation power of the target photovoltaic power station; according to the historical deviation mode correction downscaling model, a targeted correction function is established by analyzing a systematic deviation mode between a theoretical prediction value and an actual observation value in historical data, and conversion from coarse resolution prediction to site scale microscopic meteorology is realized, so that the photovoltaic power generation power prediction precision is improved.

The invention discloses a high-precision distributed photovoltaic output prediction method and system based on micrometeorology and feature hierarchical clustering, and relates to the technical field of distributed photovoltaic output prediction.The method comprises the steps that numerical weather forecast data are collected, an initial micrometeorological field is generated through space-time alignment and self-adaptive KNN interpolation, and the initial micrometeorological field is subjected to feature clustering; a WRF-LES system and a bidirectional LSTM are combined to establish cross-scale mapping, a dynamic residual correction field is fused to generate hectometer-level high-resolution micrometeorological data, and the problem of insufficient resolution of traditional numerical forecasting is solved. MIC and PA-DTW are used for jointly analyzing the characteristics of the power station, and dynamic clustering is achieved through a sliding time window and incremental spectral clustering. According to the method, a physical information graph network and causal expansion convolution are coupled to extract features, federal learning cross-power-station cooperative training is combined, the distributed photovoltaic output prediction precision and robustness are improved, and privacy security is considered.

The invention discloses an urban ventilation corridor construction method based on local climate region classification and remote sensing inversion, and belongs to the technical field of urban climate regulation and space optimization. According to the method, a multi-scale urban thermal environment analysis framework is constructed, a coupling mechanism of an urban form and a thermal effect is systematically identified from macroscopic, mesoscopic and microscopic levels, and fine modeling and regulation and control path identification of the thermal environment are realized. Meanwhile, in combination with machine learning and interpretability analysis methods, scientificity and transparency of thermal environment driving factor identification are enhanced. Through combination of remote sensing inversion, morphological factor construction and three-dimensional analogue simulation, a complete technical path of cold source identification, resistance modeling, path optimization and microclimate response evaluation is provided, and the aeration-cooling potential identification capability of blue-green infrastructures is effectively improved. The method is suitable for wind gallery planning and climate adaptation type update design of various urban spaces, and has wide popularization and application prospects.

The invention discloses a poplar degenerated forest stand accurate restoration method, and relates to the technical field of poplar degenerated forest stand restoration, and the method comprises the steps: obtaining a multi-temporal satellite remote sensing image and an unmanned plane multi-spectral image of a target area; in combination with soil moisture content, rhizosphere respiration rate and micrometeorological data collected by ground Internet of Things sensing nodes arranged in a forest stand, geographic coordinate registration and time sequence alignment are performed on the data to form a multi-source observation data set; the method comprises the following steps: extracting vegetation indexes, short-wave infrared reflectivity, soil moisture and rhizosphere physiological parameters based on a multi-source observation data set, constructing a degradation diagnosis index fusing spectral change, moisture stress and root activity, calculating the degradation degree of each pixel, and generating a degradation level spatial distribution diagram; the area with the degradation degree reaching a set threshold value is determined as a to-be-repaired area; and selecting representative poplar individuals in the to-be-repaired area, measuring the photosynthetic ability of the individuals, and calculating the individual competition intensity in combination with the three-dimensional point cloud data.

The invention discloses a method for constructing an evaluation model for the influence of climate change on biodiversity, and particularly relates to the technical field of ecological modeling and climate response analysis. The method comprises the following steps: generating a high-resolution characteristic grid based on microclimate disturbance data and a remote sensing image, extracting ecological plaques and establishing a heterogeneity spatial index model, constructing a connectivity map and a coupling response path library, extracting a typical species response mode by using nonlinear dimension reduction and spectral clustering, and performing dynamic fitting in combination with biological survey data. And finally, generating a diversity attenuation trend prediction curve and a risk thermodynamic diagram, identifying a biodiversity collapse critical point and outputting an intervention priority, and the method can be widely applied to regional ecological early warning and protection planning.

The invention discloses a farmland environment intelligent monitoring system and method based on multi-modal sensor fusion, and relates to the technical field of farmland environment monitoring, and the method comprises the steps: obtaining first integrated data in a farmland, and carrying out the preprocessing of the first integrated data; constructing a sound wave attenuation model based on the preprocessed first comprehensive data, and inverting the air humidity and the vegetation density through the sound wave attenuation model; conflict detection and resolution processing are carried out based on an inversion result; and constructing a three-dimensional microclimate field based on a conflict resolution result, and carrying out verification and iterative optimization by fusing a crop physiological model. According to the method, farmland space-time heterogeneity is adapted by means of a dynamic space-time weight coefficient, so that a three-dimensional microclimate field covering horizontal and vertical dimensions is constructed, and a'monitoring-verification-optimization 'closed loop is formed through crop physiological model association and iterative optimization; the problems of limitation of a single sensor, low inversion precision, poor data continuity, extensive monitoring and lack of decision association in the prior art are effectively broken through.

The invention relates to the technical field of power transmission line operation and maintenance, in particular to a power transmission conductor galloping prediction method based on an ice wind load coupling effect, and the method comprises the steps: collecting micrometeorological data, icing parameters, conductor tension, span and other multi-source monitoring data in real time; constructing a three-node cable unit model containing a torsional degree of freedom based on the icing parameters, and simulating an asymmetric icing form; constructing a spatial large rotating beam unit model of the transmission tower based on Beidou positioning and point cloud scanning data; coupling the models, inputting wind speed, wind direction and temperature parameters, and calculating a galloping amplitude, a galloping frequency and an alternating stress amplitude through a self-adaptive step size algorithm; dynamically generating an early warning threshold according to the voltage grade and the span; when the galloping amplitude exceeds a threshold value, triggering graded early warning and outputting an affected tower disposal suggestion; through precise modeling and multi-source data fusion, the galloping prediction precision and response speed are improved, dynamic and precise early warning is realized, and safe and stable operation of the power transmission line can be effectively guaranteed.

The invention discloses a landscaping landscape design method based on big data, and belongs to the technical field of landscape simulation design, and the method specifically comprises the steps: obtaining microclimate data of a target area and surrounding building environment data, and inputting the data into a dynamic microclimate simulation model to obtain a microclimate dynamic distribution diagram; identifying the position and the type of a microclimate discomfort area based on the distribution map, and generating a landscape design element set; carrying out overlay analysis on the element set and the distribution map, and adjusting the attribute and position of each element to form a preliminary design scheme; the preliminary scheme is input into a model to simulate microclimate distribution after implementation, and the difference degree of new and old distribution diagrams is calculated; and when the difference degree exceeds a preset range, iteratively adjusting the design elements and repeating the optimization process, and outputting a final scheme until the difference degree reaches the standard. According to the invention, dynamic coordination of landscape design and microclimate environment is realized.

The invention relates to the field of agricultural yield prediction, and particularly discloses a crop yield prediction method and system based on artificial intelligence, and the method comprises the steps: S1, recognizing crop types through the spectral features of a remote sensing image and field sampling data, and dividing corresponding key growth stages; s2, collecting multi-source feature data for each key growth stage, wherein the multi-source feature data comprises remote sensing image data, an extracted normalized difference vegetation index NDVI, an enhanced vegetation index EVI and a topographic factor; acquiring hourly temperature, humidity, precipitation and illumination intensity of each sub-region through a distributed sensor according to micro-meteorological data; obtaining plant height, leaf area index and fruit development parameters through unmanned aerial vehicle three-dimensional imaging according to crop phenotype data; by adopting the technical scheme of the invention, the terrain, microclimate and crop dynamic growth characteristics can be accurately fused, and the problem of non-uniform sample distribution is solved, so that the accuracy and regional adaptability of yield prediction are improved.

The invention discloses a high-salinity desert region pioneer vegetation rapid planting method based on salinity gradient regulation and control, and relates to the technical field of vegetation planting. The method can effectively regulate and control gradient distribution of salinity in the high-salinity desert region, reduce salt stress of a root zone, improve the seed germination rate and the seedling survival rate of pioneer vegetation, effectively inhibit surface salinity accumulation and optimize moisture distribution, thereby promoting rapid field planting and healthy growth of vegetation; by constructing a stable salinity gradient and moisture regulation and control system, through a micro-irrigation system and a mixed matrix layer, the moisture utilization efficiency is optimized, the fresh water consumption is reduced, the vegetation coverage is improved, the soil erosion risk can be reduced, the stress resistance of an ecological system is enhanced, and the vegetation coverage is rapidly improved in a short time; finally, the desert region is promoted to succession towards a multi-layer and stable arbor-shrub-grass community structure, the soil fertility and the microclimate environment are improved, the stability and the wind erosion resistance of an ecological system are enhanced, and reliable technical support is provided for sustainable ecological restoration.

The invention relates to the technical field of indoor environment control, in particular to an energy efficiency optimization and intelligent energy-saving control method and device for an AI five-constant system, and provides the following scheme that indoor and outdoor environment parameters and personnel detection information obtained by a sensing module are combined with an indoor space three-dimensional geometric model, and an energy efficiency optimization and intelligent energy-saving control method and device for the AI five-constant system are obtained. An indoor space is dynamically divided into a target microclimate area and a non-target microclimate area which are formed around people. By respectively determining a five-constant control target parameter set and a differential allowable fluctuation range of the two types of regions, the regulation and control precision is concentrated in the region where the human body is located, and an energy consumption regulation space is reserved in a non-key region. And an energy consumption model is further utilized to construct an operation energy consumption target function, the five-constant-error constraint and the equipment operation constraint are jointly introduced into a multi-target optimization framework, target air supply parameters of the partitioned air supply structure and indoor unit operation parameters are solved, and coordinated regulation and control of the air temperature, humidity, cleanliness, oxygen content and noise are achieved.

The invention discloses a power transmission line icing analysis method and system influenced by microtopography and micrometeorology, and relates to the technical field of power transmission line risk prediction.The method comprises the steps that original meteorological data of an area where a power transmission line is located is collected and fused, and micrometeorological field variables are generated based on topographic parameters extracted by a DEM; on the basis of the fusion data and the micrometeorological field variables, three-dimensional micrometeorological field data are obtained through a fluid mechanics model, the three-dimensional micrometeorological field data are corrected through terrain parameters obtained through a DEM model, an exponential weighted moving average method is used for adjustment, and accurate three-dimensional micrometeorological field data are obtained; based on the accurate micrometeorological field data, the icing thickness is obtained by adopting a physical-empirical hybrid icing growth model, the output icing thickness is adjusted in real time through a dynamic correction algorithm, and a final icing simulation result is obtained. The accuracy of power transmission line icing disaster prediction and the flexibility of emergency response are improved.

According to the fine correction method for the icing microtopography and microclimate of the long-span power transmission line provided by the invention, the icing mass growth model is established, and the liquid water content and the water drop median diameter in meteorological data are determined according to the actually measured icing mass; and establishing a corresponding computational domain and boundary conditions on the basis of the strain tower of the power transmission line so as to train the physical information neural network, then predicting the meteorological distribution state of the power transmission lines on the two sides of the canyon only by using meteorological parameters near the strain tower, and then calculating the icing state according to the distribution state. Therefore, accurate correction of icing prediction is completed, the hypothesis of a uniform meteorological field in the traditional technology is effectively avoided, the accuracy of an icing prediction result is effectively ensured, and the actual working condition is better met.

The invention discloses a coastal wetland blue carbon reserve measurement method based on habitat perception and missing codes. The method comprises the following steps: obtaining habitat category labels and micrometeorological parameters of a target area; generating a sensor scheduling instruction and a scheduling state code according to the habitat category label and the micrometeorological parameter; active compensation is executed according to the pod attitude change, and a data confidence mark is generated; constructing feature vectors of the grid units; constructing a structural deficiency indication code, jointly inputting the structural deficiency indication code and the feature vector into an inversion model, and outputting a blue carbon reserve prediction value of the target area and a corresponding uncertainty index; when the uncertainty index exceeds a preset threshold value, a recovery strategy is generated, and subsequent flight planning parameters are dynamically corrected; and after the recovery data is updated, repeatedly executing the processes of feature construction, inversion and uncertainty evaluation until the global uncertainty meets a preset requirement. According to the method and the system, the stability and the reliability of a blue carbon reserve space inversion result in a complex coastal wetland environment are improved.

The invention discloses a multi-source heterogeneous meteorological data adaptive fusion photovoltaic power prediction method, and belongs to the technical field of photovoltaic power generation prediction and meteorological data processing. The method comprises the following steps: acquiring regional meteorological data, site micro-meteorological data and wind cloud satellite secondary cloud picture data, and carrying out preprocessing and feature screening on the regional meteorological data, the site micro-meteorological data and the wind cloud satellite secondary cloud picture data; defining a coupling coefficient vector; calculating fusion temperature, wind speed and irradiance based on the coupling coefficient, and constructing an input feature vector; performing preliminary power prediction by using a time sequence prediction photovoltaic short-term power model and the input feature vector; optimizing a coupling coefficient by adopting a genetic algorithm; and performing final power prediction based on the global optimal coupling coefficient and the time sequence prediction photovoltaic short-term power model. According to the invention, through an adaptive weight optimization mechanism, the problem of insufficient adaptability of fixed weight fusion under different meteorological conditions is effectively overcome, and the engineering landing performance is high.

The invention discloses a fan blade icing monitoring method based on mechanism analysis, and the method comprises the steps: 1, constructing a dynamic mechanism model of "pneumatic-thermal-quality" three-phase strong coupling, local micrometeorological conditions and water drop impact characteristics of each airfoil section and feedback effects of icing growth on aerodynamic configuration and subsequent icing in the blade rotation process are calculated in real time; 2, performing icing prediction based on the constructed dynamic mechanism model, wherein the icing prediction comprises local microenvironment calculation, dynamic icing growth calculation and pneumatic feedback calculation; step 3, judging an icing state; step 4, outputting an icing state and early warning information; the problems that a data-based driving method needs to depend on a large amount of high-quality annotation data, when the data size is insufficient or data distribution changes, the generalization ability and prediction precision of a prediction model can be greatly reduced, the internal mechanism of icing cannot be explained, and the reliability requirement in engineering application is difficult to meet are solved.

The invention discloses a wetland carbon sink monitoring system and a carbon sink evaluation method, and the wetland carbon sink monitoring system is designed based on open circuit / closed circuit vorticity. Detection equipment of the wetland carbon sink monitoring system comprises a carbon dioxide analyzer, a three-dimensional ultrasonic anemorumbometer, a methane analyzer, sunlight-induced chlorophyll fluorescence observation equipment and micrometeorological monitoring equipment, and a carbon sink model is constructed based on the wetland carbon sink monitoring system. Main greenhouse gases are monitored in real time, high-frequency continuous atmosphere-vegetation interface and atmosphere-water body interface carbon income and expenditure data are obtained, wetland and water body ecological system carbon sink time change characteristics are revealed, a carbon sink model is constructed in combination with micrometeorological monitoring and environmental data, the Hongze lake wetland carbon sink pattern and influence factors are clarified, and the wetland carbon sink time change characteristics are analyzed. And estimating the wetland carbon sink potential of the Hongze lake.

The invention relates to the technical field of artificial intelligence, and further relates to a northern greenhouse tropical fruit microclimate adaptive control system based on reinforcement learning. The system comprises a data acquisition module configured to be used for acquiring multi-channel sensor data according to a preset sampling period; the open-loop trajectory optimization module is configured to establish a neural ODE environment model based on the state vector, and perform open-loop trajectory optimization by adopting Pontryagin approximation to generate a control trajectory; the strategy fine tuning module is configured to configure a strategy network, and the strategy network performs training by simulating the action of the first time period of the learning control track and performs online fine tuning based on the deviation score of the whole window and the sensitivity of the energy consumption of the whole window; and the instruction execution module is configured to preferentially adopt the control track to generate an executable message sequence and issue the executable message sequence to the controlled equipment. According to the invention, control precision and stability can be maintained under different weather and crop conditions.

The invention discloses a vehicle-mounted micrometeorological monitoring and camping site disaster early warning system and method, and belongs to the technical field of vehicle-mounted meteorological monitoring, and the system comprises a data collection and preprocessing module which is used for obtaining and calibrating multi-source meteorological and geographic data; the microclimate modeling module is used for generating a microclimate grid with a real-time weather predicted value by taking local microclimate data as a benchmark and fusing cloud and geographic data; the disaster risk assessment module performs quantitative risk assessment on camping disasters such as flood, tree smashing, landslide and thunderstorm based on the data of the microclimate grid; and the early warning generation module generates visual early warning information including a disaster icon, a risk level, time information and a risk avoiding instruction according to the quantitative risk assessment result. According to the invention, by optimizing the layout of the sensors and introducing a terrain correction interpolation algorithm and scene disaster assessment, the meteorological monitoring precision in a mobile environment is improved, and timely early warning of camping field micro-scale disasters is realized.

One aspect is a system including a bed having a mattress, a temperature sensor attached to the mattress, the temperature sensor configured to sense temperature and transmit temperature readings to computing hardware, and a temperature modulating unit configured to adjust a microclimate temperature of a microclimate of the bed. The computing hardware can be configured to receive a stream of temperature readings from the temperature sensor, calculate an estimated environmental temperature based on the stream of temperature readings, wherein when the computing hardware determines that a user is present in the bed, the estimated environmental temperature is calculated using at least one temperature reading in the stream of temperature readings detected before the user was determined to enter the bed, determine a temperature adjustment setting based on the estimated environmental temperature reading and activate the temperature modulating unit to adjust the microclimate temperature according to the temperature adjustment setting.

The invention provides a micro-topography and micro-meteorological power transmission line icing reanalysis database construction method and system, and relates to the technical field of power system disaster prevention and reduction and power grid meteorological application. The method comprises the following steps: carrying out space-time alignment on original DEM data and original reanalysis meteorological data of a complex mountain region to obtain a basic data set; carrying out dynamic downscaling simulation by taking re-analyzed meteorological data in the basic data set as a large-scale background field and boundary conditions and taking DEM data of the basic data set as a terrain forced field; performing vertical gradient correction for the actual height of the power transmission line based on a boundary layer theory; extracting a microtopographic factor of the power transmission line corridor area; carrying out local micro-scale terrain effect correction by utilizing the micro-terrain factors; and constructing a power transmission line icing reanalysis database based on the microtopographic factors and the high temporal-spatial resolution reanalysis meteorological data. The problem that the icing prediction accuracy and precision of an existing complex mountain region are low is solved.

The invention discloses an in-operation OPGW icing tension monitoring method based on a micrometeorological temperature demodulation BOTDR. The method comprises the following steps: measuring through a Brillouin optical time domain reflectometer to obtain OPGW Brillouin frequency shift data; calibrating a Brillouin frequency shift temperature sensitivity coefficient and a Brillouin frequency shift tension sensitivity coefficient of the OPGW by using the data of the microclimate icing monitoring terminal; according to the Brillouin scattering principle, all Brillouin frequency shifts are converted into Brillouin equivalent temperatures; the external environment temperature of the OPGW is measured through the micro-meteorological icing monitoring terminal and is defined as temperature data of the micro-meteorological icing monitoring terminal; calculating a difference value between the Brillouin equivalent temperature and the temperature data of the microclimate icing monitoring terminal; and when the temperature difference value is greater than or equal to the temperature measurement precision of the Brillouin optical time domain reflectometer, the icing tension is calculated. According to the invention, the Brillouin frequency shift temperature sensitivity coefficient and the Brillouin frequency shift tension sensitivity coefficient can be directly calibrated on line, and the calibration result and the icing tension monitoring result are more accurate.

The application relates to the technical field of soil gas collection, and particularly discloses an in-situ soil profile gas collection device which comprises an inner pipe, a pipe body and a strip-shaped belt. The pipe body comprises an exposed end and an inserted end, the inner pipe is located in the inner cavity of the pipe body, one end of the inner pipe is detachably connected with the inner wall of the pipe body close to the inserted end, the inner wall of the inner pipe is connected with one end of a supporting rod, the outer circumferential side of the strip-shaped belt is equidistantly provided with not less than three elastic rings, the inner diameter of the strip-shaped belt is larger than the outer diameter of the inner pipe, the strip-shaped belt is sleeved on the inner pipe, each elastic ring is clamped on the outer circumferential side of the inner pipe, and the pipe body is provided with a pulling assembly for driving one end of the strip-shaped belt to move. The technical scheme of the example of the application realizes in-situ collection of soil profile nitrous oxide gas, is suitable for long-time measurement of nitrous oxide, and has smaller interference with the surface microclimate.

This invention relates to the field of image sensing data processing and discloses a method for diagnosing the thermal environment of blue-green spaces in cold-region cities based on multispectral remote sensing. The method includes the following steps: acquiring multispectral remote sensing images, three-dimensional building elevations, and solar apparent shape parameters; calculating the illumination shading coefficient of blue-green space pixels to form a three-dimensional dynamic shadow mask; constructing a microscopic phase transition evolution operator using the sensitivity gradient of radiation intensity in different polarization directions and mid-infrared reflectivity; inputting the mask and operator into the thermal infrared radiation measurement equation to reconstruct the dynamic surface temperature; solving the surface energy balance equation based on the dynamic surface temperature, separating the latent heat storage of phase transition energy, and constructing a latent heat buffer index; and performing a comprehensive diagnosis of the thermal environment health based on this index. This invention effectively overcomes the temperature measurement errors caused by complex shading and phase state interweaving, accurately isolates the latent heat energy of phase transition, and achieves precise positioning and objective quantitative diagnosis of microclimate anomalies in cold-region cities.

The present invention relates to a method and system for controlling the temperature of an indoor space. The space may be provided with a conventional heating system and a heater matrix comprising a plurality of heater pixels embedded in surfaces contained within the space. Each heater pixel comprises a resistance heater element. The conventional heating system is used to maintain a base temperature in the space, which is lower than a comfortable room temperature. The operation of the heater matrix is ​​selectively controlled to create one or more areas within the space that have a microclimate with a comfortable temperature higher than the base temperature.

The invention discloses an ecological system productivity estimation method for predicting the optimal vegetation temperature based on LSTM, and relates to the technical field of ecological information, and the method comprises the steps: obtaining historical weather, terrain and future climate data; constructing a spatial neighborhood of a target pixel, quantifying climate connectivity cost based on terrain and a wind field, and generating anisotropic spatial features; resolving a dynamic space-time confidence factor representing the microclimate complexity; inputting the anisotropic spatial features and the historical temperature into a long short-term memory network, regulating and controlling fusion weight through a dynamic gating mechanism by using confidence factors, and predicting the optimal vegetation temperature; constructing a decoupling model containing thermal kinetic energy and nonlinear thermal stress terms, and calculating productivity based on a predicted value and future temperature; according to the method, the microclimate heterogeneity and the vegetation thermal adaptation mechanism can be accurately depicted, and the estimation precision of the productivity of the ecological system under the complex climate scene is effectively improved.

The invention discloses a smart agricultural variable fertilization control system and method based on image recognition, and relates to the technical field of smart agriculture, and the method comprises the steps: collecting an orchard multi-source image and laser radar data through an unmanned aerial vehicle, and dividing an orchard into different microclimate management units according to topographic features; extracting the vein mesophyll color difference ratio of the citrus leaves from the visible light image, correcting the traditional spectral index, and eliminating the interference of light environment difference on nutrition diagnosis; based on the corrected spectral index, establishing a nitrogen demand model in combination with terrain and tree body parameters, and generating a single-plant personalized variable fertilization prescription map; and importing the prescription map into the intelligent fertilizer applicator, and controlling fertilizer discharge to execute variable-rate fertilizer application operation by locating and inquiring the fertilizer application amount in real time. According to the method, the dynamic compensation model based on the vein and mesophyll color difference ratio is constructed, the leaf morphological characteristics and the spectral information are cooperatively processed, the traditional vegetation index is dynamically corrected, and the spectral response deviation caused by the light environment difference under the complex terrain can be reduced.

The application discloses a kind of based on agent model's air bag template ice shell building weatherability optimization design method, it is related to building design technical field.The problems that existing technology lacks the quantitative evaluation index of ice shell building weatherability and lacks the construction of universal agent model are solved, including: S1 stage is established microclimate response agent model, through orthogonal experimental design to generate ice shell case set, extract morphological characteristics and spatial characteristics, obtain wind snow distribution label by combining CFD simulation, construct neural network agent model;S2 stage is fused multiple tools to realize performance optimization, utilize Grasshopper parametric modeling to extract features, call agent model to predict surface snow wind distribution, obtain radiation data jointly by Ladybug, combine sublimation rate to calculate initial and later strain energy and weatherability index, finally, morphological parameters are multi-objective optimized by NSGA-II algorithm, it has application prospect in the field of ice shell building structure optimization.

This invention provides a construction method for an ecological open channel system in urban streets and alleys, including steps such as constructing a sedimentation and filtration system, constructing a rainwater and sewage diversion system, and constructing a water resource collection system. This invention can achieve multiple benefits, including reducing urban flooding, improving the urban microclimate, and enhancing the urban landscape.

The invention provides a wind power deviation correction method, and relates to the field of wind power deviation correction, and the method comprises the following steps: obtaining five-element microclimate operation data of a wind power plant, and constructing a five-element feature vector; a microclimate state vector is generated through a microclimate state encoder, and the fusion weight of the LSTM and the Self-Attention is dynamically calculated; respectively processing short-term, medium-term and long-term time sequence dependency relationships, and generating a global dependency feature vector; embedding a wind energy conversion physical law into a loss function, and constructing a physical constraint reinforcement learning framework; dynamically adjusting the weight of each microclimate factor to generate a weighted feature vector; and generating a final wind power deviation correction result through the decoder network. According to the method, through microclimate adaptive model fusion, multi-scale time sequence modeling, physical constraint enhancement and dynamic feature optimization, the accuracy of wind power deviation correction and the adaptability to different meteorological conditions are improved.