31 results about "Geographic distribution" patented technology

The invention discloses a wave energy array development site selection method, which belongs to the field of wave energy development and utilization, and comprises the following steps of: 1) processing geographical distribution data by utilizing a GIS (Geographic Information System) spatial analysis method to obtain a limited development area graph layer; and 2) constructing an evaluation index system of wave energy array development site selection, and carrying out standardization processing to obtain a comprehensive evaluation result. And 3) calculating an offshore distance, and generating a refined developable range layer. And 4) carrying out wave direction statistical analysis in the developable range to obtain an array development range. And 5) on the basis of determining the array development range of the target sea area, determining a potential development site. 6, quantitative analysis and trend analysis of the array development capability are carried out with the potential development site as the center point, and the key development site is determined.According to the method, multi-dimensional evaluation indexes such as environment compatibility, resource endowment, technical feasibility and economic rationality are integrated, and a scientific basis is provided for array development site selection of the wave power station.

The invention discloses an event-driven architecture-oriented spatial-temporal feature extraction method and system for multi-type fault power failure events, and belongs to the field of power system fault diagnosis. According to the method, historical fault data, equipment operation data and external environment data are collected through event monitoring triggering and multi-source data fusion; an XGBoost model based on probability distribution is adopted to carry out precise cleaning and complementing on the data, and a comprehensive full-scene fault sample library is constructed; and further, a time sequence convolutional network and a graph convolutional neural network are utilized to deeply mine and fuse spatio-temporal characteristics such as periodicity, high-incidence time periods, geographical distribution rules and spatial relevance of fault events from a sample library. According to the method, spatio-temporal evolution law analysis and key influence factor identification of fault events can be efficiently and intelligently realized, the accuracy and timeliness of power grid fault research and judgment are remarkably improved, a scientific basis is provided for fault positioning and emergency disposal, and construction of a novel power system is assisted.

The invention provides a space and risk determination method and device for hidden danger objects of a distribution network line, and relates to the technical field of distribution network line management and control. The method comprises the steps of obtaining a distribution network line and multi-modal data of a hidden danger object which forms potential threats to the distribution network line, performing feature extraction on the multi-modal data, and determining multi-dimensional features of the hidden danger object. And then, inputting the multi-dimensional features into a multi-task fusion model, and predicting an event category to which the hidden danger object belongs based on the multi-task fusion model. And next, obtaining geographic position data of the hidden danger object, and mapping the geographic position data and the belonging event category to a target GIS platform to determine the geographic distribution condition of the hidden danger object. And finally, determining a risk score of the hidden danger object based on the event category and the geographical distribution condition, and determining a risk level of the hidden danger object based on the risk score. The geographic distribution condition and the risk level of the hidden danger object can be accurately determined.

The invention relates to an artificial cross breeding method for male epinephelus fuscoguttatus and female humpback perch, which belongs to the technical field of distant cross breeding and comprises the steps of parent selection of the epinephelus fuscoguttatus and the humpback perch, parent ripening cultivation, gamete collection, artificial insemination and incubation and fry cultivation. By means of reproductive regulation and distant hybridization technologies, two species of two genera of grouper family in different geographical distribution and different reproduction time are hybridized, namely cross-generic hybridization of grouper family breaks through the generic reproductive isolation, and therefore good varieties which grow fast and are high in survival rate are cultivated.

The invention discloses a carbapenemase OXA-58-like positive plasmid and a host bacterium propagation risk assessment method thereof, which are used for carrying out integrated assessment on the plasmid and the host bacterium in three dimensions of drug resistance, pathogenic potential and propagation potential, and carrying out comprehensive risk grading and classification by taking the OXA-58-like positive plasmid and the host bacterium thereof as a plasmid-host complex. The invention develops a set of OXA-58-like gene screening and systematic analysis process based on a public plasmid database aiming at the defects that the existing research of the OXA-58-like gene is mostly limited to a single species or a local sample and a standardized automatic analysis method is lacked. According to the method, all OXA-58-like gene positive plasmids in a database can be subjected to unified and efficient drug-resistant gene mining, the association rule between the drug-resistant genes and plasmid pedigree, host strains and geographical distribution is systematically disclosed, and important technical support is provided for drug resistance propagation monitoring and risk assessment.

The invention discloses a water injection wellhead injection pressure monitoring and evaluating method, which comprises the following steps of: realizing cross-well pressure data coupling by utilizing geographical distribution labels based on multi-point pressure real-time acquisition of a target and an adjacent water injection well, extracting pressure fluctuation characteristics after data missing correction, multi-stage noise reduction and normalization, and calculating the injection pressure of a water injection wellhead. Inputting an automatic induction dominant pressure mode of the self-evolution multi-label clustering model, and generating a reference template dynamically updated along with working conditions; the pressure fluctuation consistency is judged by comparing the real-time pressure trend with a reference template distribution label, collaborative anomaly traceability analysis is implemented for significant deviation, the anomaly cause type is recognized by combining historical drift and noise characteristics, a detection threshold value is automatically optimized, a machine-readable anomaly traceability report is generated, and an operation and maintenance decision is assisted; an online sample continuous learning mechanism ensures the adaptability and diagnosis accuracy of the model under different working conditions. According to the method, the intelligence, robustness and abnormal response efficiency of water injection well area pressure monitoring are improved.

The invention discloses a basin and peripheral area digital modeling method and system based on big data analysis, and relates to the technical field of digital modeling, and the method comprises the steps: connecting a GIS system, and obtaining the geographic distribution information of a target basin area; building a digital space, carrying out grid division on the digital space, and determining a digital grid; acquiring detection data of each exploration zone in the target basin area, performing data interpretation and preprocessing respectively, and determining geological feature information; based on the digital grids, in combination with the geological feature information, performing three-dimensional modeling on the digital grids in parallel, and respectively determining grid models; and splicing the grid models, determining a digital basin periphery model, performing macroscopic quantization, and generating a macroscopic digital basin periphery model. According to the method, the technical problem of low model building efficiency in linkage modeling of the basin combined peripheral mountain-building belt in the prior art is solved, and the technical effect of improving the efficiency and the accuracy of exploration and analysis of the basin and the peripheral area is achieved.

A method for estimating glacial meltwater runoff is disclosed, comprising the following steps: S1, obtaining glacier geographical distribution information and calculating driving data; S2, simulating glacier ablation; S3, calculating glacial meltwater runoff. A relatively accurate glacial meltwater runoff estimation model is established, solving the problem of significant uncertainty in existing meltwater runoff estimation methods, and is able to simulate the changing characteristics of each glacier.

The application discloses a wave energy array development site selection method, and belongs to the field of wave energy development and utilization, comprising the following steps: 1) processing geographic distribution data by using a spatial analysis method of GIS to obtain a restricted development area layer; 2) constructing an evaluation index system for wave energy array development site selection, and performing standardization processing to obtain a comprehensive evaluation result; 3) calculating an offshore distance to generate a refined developable range layer; 4) carrying out statistical analysis on a wave direction in the developable range to obtain an array development range; 5) determining a potential development site on the basis of the array development range of a target sea area; and 6) taking the potential development site as a center point to perform quantitative analysis and trend analysis on array development capacity, and determining a key development site. The application integrates multidimensional evaluation indexes such as environmental compatibility, resource endowment, technical feasibility and economic rationality, and provides a scientific basis for wave energy power station array development site selection.

The application discloses a bird chirp sound recognition method based on a combination of voiceprints and spatial distribution, and belongs to the technical field of intelligent sound classification and recognition. In view of the problems of ignoring geographical distribution prior knowledge and sample imbalance in the prior art, the application firstly constructs a voiceprint recognition model: a training data set is constructed by audio preprocessing, logarithmic mel spectrum and dynamic difference feature extraction, a model is trained based on DenseNet-121 by adopting a two-stage training strategy, and recognition confidence of each species is obtained; meanwhile, a spatial distribution model is constructed: based on public observation data, an average observer ability index is used to correct an original encounter rate, and spatial distribution probability of the species in a specific city is obtained; finally, a Sigmoid function is used to perform nonlinear fusion on the two, a joint recognition probability is calculated, and a classification result is output. The application introduces ecological spatial constraints into the recognition decision, effectively reduces false positive misjudgment, improves rare species monitoring capability, and makes the recognition result have ecological interpretability.

The present invention relates to "A process for the production of whitefish from Pátzcuaro (Chirostoma estor) and balanced diets for its growth and fattening." These diets have specific characteristics for this species, with a content of easily digestible protein ingredients that efficiently contribute to larval survival and the size and weight of the juveniles fed in aquaculture farms with the appropriate diet for each stage. These diets can enter the national and international markets due to their unique characteristics and the results obtained with stomachless fish. Additionally, these feeds can be used for the production of species at a lower level of the food chain, which do not require the use of fishmeal and fish oil, making the aquaculture of these species a more sustainable activity.These diets are the first developed specifically for the successful growth and fattening of the species C. estor, "Pátzcuaro whitefish", having the potential to impact its conservation and marketing in the region of geographic distribution.

The application discloses a mountain and hilly biomass collection, storage and transportation collaborative scheduling method and system based on multi-agent game, relates to the technical field of wisdom agriculture and supply chain collaboration, and aims to solve the problems of unbalanced benefit distribution, ignored terrain constraints and rigid collaborative mechanism in the prior art. The application first acquires static attribute data, dynamic operation data of the collection and storage nodes, and geographical distribution and resource quantity of all resource points of the biomass to be collected and transported; determines the dispersion degree of the geographical distribution of all resource points, the balance degree of the resource quantity, and the difference degree of the appeals of the benefit related parties; takes the dispersion degree, the balance degree, the static attribute data of each collection and storage node and the difference degree of the appeals as judgment indexes, determines the collaborative mode of the benefit related parties according to a preset judgment mechanism, executes collaborative planning, and completes dynamic planning of the collection path and the corresponding resources; and finally realizes dynamic allocation of resources.

The invention provides a comprehensive pipe gallery underground water level risk early warning method and system, and relates to the technical field of risk early warning, and the method comprises the steps: collecting the pipe gallery geographical position distribution of a target comprehensive pipe gallery, and constructing a comprehensive pipe gallery distribution network; subarea risk analysis of the underground water level is executed, and each pipe gallery subarea and an underground water level risk list of each subarea are generated; monitoring underground water level data of the located area in real time; and inputting an underground water level risk list of each subarea, executing early warning triggering of each pipe gallery subarea, and generating underground water level risk early warning information. The technical problem that in the prior art, due to the fact that underground water level risk early warning mostly adopts a simple static model and a unified water level threshold value to judge the safety of the pipe gallery, consideration of geographical distribution of the pipe gallery is lacked, and risk early warning is not accurate is solved, the geographical distribution network of the comprehensive pipe gallery is established, and the risk early warning accuracy is improved. Regional analysis of the underground water level risk is realized, and the accuracy of underground water level risk early warning is improved.

The invention discloses a model for exploring the influence of an environment on plant distribution and application. The plant refers to gentiana dahurica fisch. Based on geographical distribution of gentiana dahurica fisch and ecological factors influencing growth of gentiana dahurica fisch, which are determined by literatures and field investigation, an ecological suitable area of gentiana dahurica fisch is modeled by adopting an enhanced regression tree (BRT). And establishing a relationship between the content of each active component in the Inner Mongolia plant and an ecological factor by adopting a linear regression method. The invention discloses a model for exploring the influence of the environment on the distribution of gentiana dahurica fisch, and discusses the influence of the environment on the growth of gentiana dahurica fisch and the content of active ingredients. The model provides guidance for coordinated development of medicinal plant science.

An example method comprises receiving first historical meso-scale numerical weather predictions (NWP) and power flow information for a geographic distribution area, correcting for overfitting of the historical NWP predictions, reducing parameters in the first historical NWP predictions, training first power flow models using the first reduced, corrected historical NWP predictions and the historical power flow information for all or parts of the first geographic distribution area, receiving current NWP predictions for the first geographic distribution area, applying any number of first power flow models to the current NWP predictions to generate any number of power flow predictions, comparing one or more of the any number of power flow predictions to one or more first thresholds to determine significance of reverse power flows, and generating a first report including at least one prediction of the reverse power flow and identifying the first geographic distribution area.

The invention discloses an earthquake fortification management and disaster analysis system based on unmanned aerial vehicle brain-like real-time calculation, which relates to the field of disaster analysis and comprises an image set acquisition unit used for acquiring a time sequence image set, a feature map extraction unit used for outputting corresponding N convolution feature maps, a group classification unit used for acquiring feature groups and a feature map fusion unit. The fusion feature map obtaining unit is used for obtaining a fusion feature map, the feature arrangement unit is used for generating a feature geographic distribution map, and the disaster detection unit is used for obtaining a disaster feature geographic distribution map; wherein the disaster feature geographic distribution map represents multi-view fusion disaster features of all geographic grids in the time window. The evolution graph construction unit is used for constructing a disaster feature space-time evolution graph; the disaster feature geographic distribution map finally formed by the method can accurately reflect the spatial distribution and evolution process of the damage state of the disaster area, and provides structured disaster data for earthquake fortification management and disaster analysis.

The invention discloses a biomass collection, storage and transportation intelligent networking method and system based on geographic information, and relates to the technical field of intelligent agriculture, and the method comprises the steps: obtaining the static attribute data and dynamic state data of each collection and storage station in a network, and the geographic distribution and resource quantity information of resource points to be collected and transported; based on the static attribute data of the storage station, the topology centrality is analyzed, and the real-time function state level is evaluated; based on the geographic dispersion, the resource quantity balance degree and the road network connectivity of the resource point cluster to be collected and transported, task decoupling performance judgment is carried out; if the task is determined to be a highly decoupled task, decoupling the resource point cluster into a plurality of geographically adjacent sub-clusters, and planning an independent parallel collection path and an integration point for each sub-cluster; if the task is determined to be a low decoupling task, a centralized cyclic collection path is planned; and according to the real-time function state level of the storage station, dynamically allocating resources corresponding to the planned collection path to the storage station matched with the function state.

The invention discloses a land asset data analysis method and system, and belongs to the technical field of land resource management. The method aims at solving the problem that in the prior art, due to the fact that a global regression model is adopted, analysis results cover spatial heterogeneity. The method comprises the following steps: acquiring geographic elements in a target space range selected by a user and specified dependent variable and independent variable records; generating spatialization analysis data fused with geographic information and variable data; generating and executing an analysis script for calling a geographic weighted regression model function, and calculating a localized regression coefficient representing local influence intensity for each geographic element; and rendering the localized regression coefficient corresponding to the specified independent variable into a color-graded thematic map on a GIS map, and presenting a visual geographical distribution rule. According to the method, the localization coefficient is calculated for each space unit, the action intensity difference of the influence factors at different geographic positions can be revealed, and therefore data support is provided for fine management and partition decision making of land assets.

This invention discloses an intelligent self-rescue system for marine jellyfish stings, relating to the field of first aid technology for biological injuries. This invention establishes a basic concept popular science system by integrating information on the species, habits, geographical distribution, and hazards of marine organisms to prevent marine organism injuries. It also integrates the clinical manifestations and treatment plans for injuries caused by venomous marine organisms, establishing a training system for treatment skills to aid in the preliminary identification of injury types and improve treatment skills. Furthermore, it integrates relevant data to compile a first aid guidebook and presents relevant medicines and equipment in a modular format for on-site emergency treatment. This effectively addresses the shortcomings and deficiencies in current marine organism injury treatment. Based on the epidemiological characteristics and treatment consensus of marine jellyfish stings, it improves the awareness, treatment skills, and on-site emergency treatment efficiency of potentially high-risk groups and medical personnel regarding marine jellyfish stings, reducing the risk of aggravated injury and mortality from jellyfish stings.

The invention relates to a method for detecting eDNA of a species complex of euphorbia helioscopia and application thereof, in particular to a method, a primer and a kit for detecting DNA of an environment of Luphorbia helioscopia based on a specific bar code sequence and application of the method, the primer and the kit. Specifically, the invention relates to the technical field of environmental DNA (eDNA) extraction and molecular detection, in particular to a fluorescent quantitative PCR (qPCR) method designed based on species specific variation sites of mitochondrial ND1 gene of a complex of a euphorbia helioscopia species, and the method can specifically detect geographical distribution of complex populations of the euphorbia helioscopia species. And population abundance of different populations is detected and compared. More specifically, the invention relates to a specific primer, a detection method, a detection kit and construction and use of a related system. The method can be used for multiple scenes such as biodiversity evaluation, species protection and ecological research.

The application discloses a kind of based on GIS and MaxEnt prediction plant disease and insect pest suitable area method, comprising the following steps: S1: the natural geographical distribution point data of the target disease and insect pest is obtained;S2: the environmental climate dataset under current and future climate conditions is obtained;S3: the biological climate variable screened in environmental climate dataset is obtained;S4: the main biological climate variable that influences the target disease and insect pest distribution is calculated and analyzed using MaxEnt model;S5: using ArcGIS software obtains the suitable area prediction graph of the target disease and insect pest under current and future climate scenarios;The beneficial effects of the application are to provide a kind of comprehensive prediction method combining modern GIS technology and advanced MaxEnt model;Second, it can better understand and predict the distribution change of disease and insect pest under different climate scenarios;Three is, the application of the application helps to improve agricultural production efficiency, reduce the loss caused by disease and insect pest.

The invention relates to application of rice self-regulation haplotypes (SRHs) in indica-japonica subspecies differentiation, seed size steady state and yield trait improvement. According to the invention, three genes for controlling grain length change in rice and natural variation of the three genes are analyzed and identified through GWAS, and a molecular mechanism for regulating expression of the OsGRX8-(OsbZIP47)-OsbZIP08-OsGRX8 through negative feedback and regulating size stability of indica-japonica subspecies seeds is analyzed. The self-regulation haplotype (SRHs) formed by the negative feedback loop shows unique geographical distribution, indica-japonica differentiation and difference in seed size and yield, and the genetic contribution to the rice yield and the seed size is far higher than the individual contribution of a single component. Based on the key SRHs, directional improvement of the size and the yield of the rice seeds can be achieved, a new strategy is provided for rice breeding, and a theoretical basis is provided for analysis of indica-japonica character differences and research on cereal crop breeding.

The invention relates to the technical field of power system fault prediction, and discloses a grid division-based power distribution network fault short-term, medium-term and long-term prediction method, which comprises the following steps of: based on a geographic distribution range of a power distribution network, carrying out region division, extracting a current change value and a voltage fluctuation value, classifying power load characteristics and combining meteorological parameters, and obtaining grid multi-dimensional time sequence characteristic data. According to the invention, by dividing the geographic area of the distribution power grid and improving the multi-source data association analysis capability, the accurate capture of regional fault characteristics is realized, and through the point-by-point comparison detection of current fluctuation and meteorological change in a short time, the fault early warning and data association mining are strengthened, the time range is middle, and the equipment state and environment change rule analysis is enhanced. Through cross-time-scale combination of a meteorological cycle and equipment operation characteristics, abnormal trigger factors are determined, dynamic weighted analysis of a high-risk area is carried out, grid prediction and risk assessment are optimized, and the fault early warning capability and the system reliability guarantee are comprehensively improved.

This invention relates to a method for artificial hybridization breeding of male brown-spotted grouper and female humpback bass. The method belongs to the field of distant hybridization breeding technology. It includes the selection of brown-spotted grouper and humpback bass parents, parent maturation cultivation, gamete collection, artificial insemination and hatching, and seedling cultivation. This invention uses reproductive regulation and distant hybridization technology to hybridize two species belonging to two genera within the grouper family with different geographical distributions and different breeding times, that is, intergeneric hybridization within the grouper family, which breaks through the reproductive isolation between genera, thereby cultivating superior varieties with fast growth and high survival rates.

The invention discloses a micrometeorological data prediction method and system based on map interaction and a related product, and belongs to the technical field of meteorological data processing. According to the micrometeorological data prediction method based on map interaction provided by the invention, different micrometeorological sensors are configured in different areas of the wind-solar power storage station, and the micrometeorological data with geographic coordinate labels are acquired in real time, so that deep fusion of the micrometeorological data and geographic distribution is realized; operation and maintenance personnel can intuitively master the micro-meteorological difference of different regions; a future time period micrometeorological prediction result with a geographic coordinate label is output through a neural network model, and in combination with map visualization, operation and maintenance personnel can conveniently judge micrometeorological changes in all areas of the wind and light storage power station; the operation and maintenance decision instruction with the geographic coordinate label is generated, the priority list is overlaid on the map processing interface, reasonable allocation of resources is facilitated, the equipment maintenance and power generation strategy is optimized, and the operation and maintenance efficiency and the intelligent level of the wind and light storage power station are comprehensively improved.

The application discloses a method and system for extracting space-time characteristics of multi-type fault outage events for an event-driven architecture, and belongs to the field of power system fault diagnosis. The method collects historical fault data, equipment operation data and external environment data through event monitoring triggering and multi-source data fusion. An XGBoost model based on probability distribution is used to accurately clean and complete the data, and a comprehensive all-scenario fault sample library is constructed. Then, the time series convolution network and the graph convolution neural network are used to deeply mine and fuse the space-time characteristics of the fault events, such as periodicity, high-incidence period, geographical distribution rule and spatial correlation. The application can efficiently and intelligently realize the analysis of the space-time evolution rule of the fault events and the identification of the key influence factors, significantly improve the accuracy and timeliness of the power grid fault research and judgment, provide a scientific basis for fault positioning and emergency disposal, and help the construction of a new type of power system.

The invention relates to a nuclear power plant site assessment method, device and equipment and a storage medium. The target data of the to-be-selected plant site area of the nuclear power plant in the preset historical time period can be acquired, wherein the target data comprises one or more of the target topographic data, the target meteorological data, the target geological data, the target hydrological data and the target geographical distribution data; inputting the target data into a preset target deep learning model, and performing environmental risk analysis on the target data based on the target deep learning model to obtain target environmental risk data of the to-be-selected factory site area; and based on the target environment risk data of the to-be-selected plant site area, determining the feasibility level of nuclear power plant construction in the to-be-selected plant site area. According to the method, manual data analysis is not needed, the participation of manual plant site evaluation is greatly reduced, the plant site evaluation time is greatly shortened, and the accuracy and the evaluation efficiency of nuclear power plant site evaluation can be improved.