58 results about "Ecological modelling" patented technology

Use of scientific models to generate graphical virtual environments is described. In an embodiment at least two different scientific models are used. Input data which is representative of a real world environment is used by a first scientific model, such as a climate model, and data output by the first scientific model is then fed into a second, different, scientific model, such as an ecological model, in order to generate simulation data. The simulation data, which may, for example, detail the required population density of particular plant species and their size and age, is then used by a graphical simulation engine to generate a graphical virtual environment which may, for example, be used in a computer game such as a flight simulation game.

The invention relates to a method and system for regulating and controlling microbial communities in a circulating water body, and the method comprises the steps: deploying a network composed of a plurality of water quality sensors which can collect various key parameters of the water body in real time and upload the key parameters to a cloud server; processing the collected data by using a big data analysis platform, identifying main factors influencing the development of the microbial community, training a predictive ecological model by using a machine learning algorithm, simulating the change trend of the microbial community in different scenes, evaluating the influence of the change trend on the water quality, and the like. A self-adaptive control theory is introduced, a closed-loop feedback system is constructed to optimize a microbial community structure and functional performance thereof, a small ecological environment most beneficial to survival and reproduction of target microorganisms is created, a targeted inhibition control strategy is implemented in the face of emergencies, the stability and safety of a water body ecological system are guaranteed, and the water body ecological system is protected. According to the method, the capability of dealing with emergency situations is improved, and the risk of environmental pollution is reduced.

The invention discloses a water conservancy and hydropower project ecological scheduling optimization method, and relates to the technical field of water conservancy and hydropower ecological scheduling, and the method comprises the steps: carrying out the fine ecological region division of a river channel, and dividing the river channel into a plurality of regions with definite ecological functions through combining a plurality of factors. By monitoring the ecological water demand of different ecological regions in the river channel in real time, the actual demand condition of each ecological region is accurately mastered, so that the ecological scheduling scheme is individually formulated according to the characteristics of different ecological regions, the scheduling accuracy is improved, the ecological model comprehensively considers multiple factors such as hydrology, water quality, ecology and meteorology, and the ecological scheduling efficiency is improved. According to the method, the change trend of the ecological water demand of different ecological areas can be predicted, a suitable living environment is provided for various aquatic organisms by accurately meeting the ecological water demand of different ecological areas, protection of rare and endangered species is facilitated, stable development of biocenosis is promoted, and the biodiversity level of a whole river ecosystem is improved.

The invention discloses a waterfowl habitat ecological data analysis method and system, a medium and electronic equipment. The waterfowl habitat ecological data analysis method comprises the steps that S1, ecological data of a waterfowl habitat is acquired and preprocessed; s2, constructing a waterfowl habitat ecological model based on the preprocessed data; s3, judging whether the ecological condition of the habitat meets a preset suitability standard or not according to an output result of the ecological model; the system comprises a multi-source data acquisition module based on a system architecture, an intelligent preprocessing module, an ecological model construction module, a habitat suitability evaluation module and a visualization and report module. Compared with the prior art, the method has the advantages of comprehensiveness (2) accuracy; and practicability.

The invention relates to the technical field of agricultural ecological management, in particular to a farmland carbon and nitrogen cycle regulation and control method based on an ecological model, and the method comprises the following steps: S1, collecting ecological data of soil; s2, on the basis of the ecological data collected in the S1, constructing a carbon-nitrogen cycle regulation and control model by utilizing an ecological model coupled with a carbon-nitrogen cycle relationship; s3, performing carbon-nitrogen balance analysis by using the carbon-nitrogen cycle regulation and control model, and further determining a balance point between carbon-nitrogen input and loss; s4, formulating a carbon nitrogen regulation and control scheme according to a carbon nitrogen balance analysis result in S3; s5, performing specific operation according to the carbon nitrogen regulation and control scheme formulated in the S4; and S6, if the soil carbon and nitrogen content does not reach the set target, dynamically adjusting the carbon and nitrogen regulation and control scheme according to a feedback result. According to the invention, through combination of ecological data acquisition and a carbon nitrogen cycle model, dynamic balance regulation and control of farmland carbon nitrogen cycle are realized, the resource utilization efficiency is improved, the environmental pollution is reduced, and the sustainability of a soil ecological system is enhanced.

The invention provides a lake multi-water-source regulation and control method based on a hydrodynamic force-water quality-ecological model, which relates to the technical field of water source regulation and control and comprises the steps of acquiring data, clarifying the generation mechanism of spatial-temporal heterogeneity of a lake water environment, establishing a model, determining a water quality control threshold for maintaining ecological health of lake water and proposing an optimal multi-water-source regulation and control scheme. According to the invention, the BLOOM module is improved, the phytoplankton characterization type is incorporated into simulation of a lake phytoplankton competition mechanism, a hydrodynamic force-water quality-ecology comprehensive model suitable for lake water environment simulation is created, and the precision of lake water environment simulation is improved, so that a water quality control target of lake water environment health can be better and accurately determined; secondly, multiple water resources are utilized for multi-water-source comprehensive regulation and control, the lake water quality is improved, meanwhile, comprehensive utilization of regional water resources is improved, the result of the method provides scientific and technological support for water quality management of the Chi-dry lake, and meanwhile the requirement for practicing precise treatment of one lake and one strategy is met.

The invention relates to the technical field of marine monitoring and early warning, in particular to an early warning method for jellyfish disasters. The method comprises the following steps: establishing a jellyfish drift path prediction model: data collection and arrangement, meteorological mode research and development, marine physical mode research and development: adopting an ROMS ocean mode to simulate typical sea area hydrodynamic environment elements, jellyfish physical-ecological model research and development, and jellyfish drift path prediction model research and development; then establishing a jellyfish disaster risk level early warning method; then participating data integration and system construction, and researching and developing a jellyfish disaster drift early warning module; and finally carrying out demonstration operation. In the invention, a method based on ensemble forecasting is independently researched and developed, and life habits such as autonomous movement of jellyfish and an emergency drifting ensemble prediction model of foreign jellyfish are considered; the jellyfish disaster risk level early warning method is researched according to indexes such as the type of the disaster jellyfish, the toxicity of the jellyfish and the distribution density of the jellyfish.

The invention discloses a lake and reservoir inflow and outflow scheduling scheme optimization method and system based on a three-dimensional hydrodynamic force-water quality-water ecological model, and the method comprises the steps: firstly constructing a three-dimensional hydrodynamic force-water quality-water ecological model of a target lake and reservoir, setting a scheduling constraint, a scoring constraint, a scoring single item, and a comprehensive scoring weight by a decision maker, stratified sampling and one-dimensional uniform random sampling are carried out on each flow range of a water replenishing port, a flow outlet and a water suction pump station which can be regulated and controlled manually according to scheduling constraints set by a decision maker, and a plurality of inflow and outflow scheduling schemes are generated; and performing big data mining on the model calculation results of all the access flow scheduling schemes, performing comprehensive scoring according to the scoring single item and the comprehensive scoring weight, and selecting the access flow scheduling scheme with the highest comprehensive score as an optimal scheduling scheme for recommendation. The method has the advantages of high simulation precision, flexible decision support, multi-target comprehensive balance and the like, and a scientific and efficient technical solution can be provided for lake and reservoir inflow and outflow scheduling.

The invention provides a day-by-day enteromorpha green tide comprehensive coverage information fusion method based on satellite remote sensing and ecological model data, and belongs to the technical field of enteromorpha green tide monitoring. According to the invention, through radiation calibration and spectral consistency processing of multi-source satellite remote sensing data, reliability evaluation and dynamic weight configuration of satellite remote sensing and ecological model data, multi-dimensional deep fusion of a spectral consistency enhancement model, bidirectional buffering and weighted fusion processing and Douglas-Peucker boundary optimization, the spectral consistency enhancement model is optimized; a complete fusion process penetrating through data preprocessing, reliability evaluation, dynamic weight configuration, deep fusion and post-processing is formed, and the technical problems that due to the fact that multi-source satellite remote sensing data and ecological model data lack an effective fusion mechanism, enteromorpha green tide monitoring is insufficient in continuity and low in accuracy are solved.

The invention provides a mining area ecological restoration intelligent decision-making system based on multivariate data integration, which comprises a mining area data acquisition module, a data fusion modeling module, an intelligent decision-making analysis module and a scheme simulation evaluation module, the data fusion modeling module is used for fusing collected multi-source data and establishing an ecological model, the intelligent decision analysis module is used for analyzing the ecological model and generating a restoration scheme, and the scheme simulation evaluation module is used for simulating and operating the restoration scheme and performing evaluation based on an operation result; according to the system, a new-generation digital solution is provided for mine ecological restoration through a technical closed loop of data intelligent fusion, scheme dynamic optimization and effect accurate pre-judgment.

The invention provides a blue carbon market adaptive accounting method based on multi-source data and Bayesian updating, and belongs to the technical field of natural resource planning and ecological management. The method comprises the following steps: firstly, constructing a standardized multi-source fusion data set through a systematic process, and then preprocessing collected data to generate a standardized blue carbon multi-source fusion data set; then, through a Bayesian-based carbon reserve estimation model, outputting a monitoring point carbon reserve prior value, fusing a monitoring point carbon reserve mean value with a spatial prior value, and updating monitoring point carbon reserve distribution; and finally, constructing a carbon credit risk index system, calculating risk indexes of the plot layer and the region layer, updating a plot layer carbon reserve mean value by using the updated monitoring point carbon reserve distribution, and generating a blue carbon project reference transaction price according to the carbon reserve mean value and the risk indexes. According to the invention, a full-chain blue carbon intelligent accounting system is constructed, and interdisciplinary fusion of an ecological model, deep learning and a carbon market mechanism is realized.

The invention relates to the technical field of ecological restoration, in particular to a plateau lake ecological restoration monitoring method and system. The method comprises the following steps: acquiring a target plateau lake image and spectral image data, and performing water storage and environment analysis on the acquired image data and spectral image data; constructing a target plateau lake ecological model according to the water storage capacity and a water area analysis result after environment analysis, segmenting the ecological model according to water areas, and performing ecological assessment on different water areas; combining evaluation results, displaying the combined evaluation results in a grade form, dividing the combined evaluation results into four grades from high to low, setting a restoration threshold value, highlighting and marking the water area with the evaluation grade lower than the restoration threshold value, and displaying the ecological problem and the restoration method of the water area; the system comprises an image acquisition module, an ecological evaluation module and a restoration determination module. According to the method, the ecological difference of different areas in the lake can be revealed, a clear direction is provided for making a restoration plan, the actual restoration work can be guided, and the restoration efficiency and effect are improved.

The invention discloses a farmland carbon and nitrogen cycle adjusting system based on an ecological model and an implementation method of the farmland carbon and nitrogen cycle adjusting system, and relates to the technical field of ecological adjustment. The system comprises a farmland information database, a visual circulating system and an adjusting system. The farmland information database comprises fertilization amount, climate conditions, soil characteristics and farmland management; the visual circulating system is used for simulating element migration among soil, plants and atmosphere, emission of greenhouse gases, organic matter analysis, CO2 generated by root respiration and dynamic behaviors of a soil carbon library and a nitrogen library; the system comprises a carbon nitrogen cycle adjustment analyzer and an early warning module. Soil data is collected in real time and imported into the mixed neural network model for carbon nitrogen cycle adjustment analysis, the optimal fertilizer usage amount and irrigation amount of the corresponding soil are calculated, the adjustment scheme is generated according to the analysis result, and the accuracy and efficiency of ecological system carbon nitrogen cycle monitoring are improved.

The invention relates to a coastal wetland ecological restoration effect evaluation method and system fusing acoustic detection and an ecological model, and relates to the technical field of environmental monitoring. According to the method, an acoustic sensing network is arranged to collect wetland multi-band acoustic signals, and low-frequency, intermediate-frequency and high-frequency voiceprint features are divided; hydrological fluctuation, vegetation coverage and biodiversity parameters are associated respectively, and a dynamic coupling mechanism of acoustic features and an ecological model is constructed; model parameters are calibrated in real time based on a Bayesian network, an acoustic biological activity index (SBAI) and an ecological system toughness score (ERS) are generated, and the restoration effect is dynamically evaluated; data lightweight processing is realized through edge calculation, weight distribution is optimized in combination with a cloud model engine, and a targeted repair strategy is generated. The system comprises an acoustic sensing network, a data fusion engine and a decision support module, and supports'monitoring-evaluation-execution 'closed-loop management. The method breaks through the limitation of traditional static assessment, realizes collaborative analysis of biological activities and habitat factors, and remarkably improves the response efficiency and decision-making scientificity of repair engineering.

The invention discloses a grassland original ecology safety dynamic evaluation and early warning system, belongs to the field of grassland safety monitoring, and aims to solve the problem that an existing dynamic evaluation and early warning system is difficult to monitor and early warn the self-restoration capacity of a grassland. Through the vegetation monitoring unit, the soil monitoring unit, the livestock monitoring unit and the restoring force monitoring unit, and through a multi-scene simulation platform establishment module of the restoring force monitoring unit, interference scenes of drought and overload grazing are preset and visually displayed based on a vegetation productivity model; a dynamic ecological model is constructed in combination with vegetation, soil and livestock grazing data collected in real time, and deduction of the self-recovery state after grassland degradation is achieved; cA-Markov is utilized to dynamically simulate variation trends of vegetation productivity, grazing intensity and the like, critical threshold values of key indexes such as livestock carrying rate and the like are accurately identified, and the anti-interference capability of an ecological system is quantified; and the decision support module integrates the DPSIR model to generate a grazing forbidding strategy, and forms a whole-process restoration force evaluation chain.

The invention belongs to the field of reservoir erosion and deposition scheduling, and particularly relates to a sediment-carrying reservoir power generation-erosion and deposition dynamic optimization scheduling model construction method. The invention discloses a sediment-carrying reservoir power generation-erosion and deposition dynamic optimization scheduling model construction method. The method comprises the following steps of S10, collecting reservoir terrain scanning data, hydrological monitoring data and ecological space data; the ecological space data comprises a spawning site elevation threshold distribution map and a benthic organism habitat substrate type partition map; superposing the data into a three-dimensional geographic ecological model through the acquisition positions of the data; s20, based on historical erosion and deposition operation records, erosion and deposition equipment scheduling parameters and corresponding geographic ecological models before and after erosion and deposition are extracted, and an erosion and deposition reduction model is established; and calculating the siltation reduction amount according to the geographic ecological model before and after erosion and siltation. According to the scheme, the problem that the reservoir ecology is destroyed due to extensive scouring and silting scheduling in the prior art is solved, the dynamic prediction, intelligent scheduling and closed-loop management capabilities are achieved, and the scouring and silting precision, efficiency and benefits are remarkably improved.

The invention discloses an island ecosystem current situation evaluation and development prediction method based on an Ecospace model. Firstly, an Ecopath model is used for fitting a current island ecosystem energy flow mode, ecological evaluation is conducted on an island ecosystem according to output parameters of the model, and meanwhile according to fishery fishing data, the regional distribution change situation of all organisms in the ecosystem is simulated through an Ecospace model. Evaluation is carried out on the basis of the ecological model, and an ecological system can be describedfrom the perspectives of food net structure integrity, nutrition function diversity, energy transfer effectiveness and the like. And after the evaluation is completed, the ecosystem is simulated by using the fishing yield, and the future development condition of the island ecosystem is predicted. According to the method, new thought reference and technical support are provided for evaluation andprediction of an island ecosystem at present from the perspectives of ecology quantity and energy science, and the method has guiding significance for management of the island ecosystem.

The invention belongs to the field of ocean monitoring, and discloses a method for evaluating an ecological risk safety threshold of toxic microalgae. the method comprises the steps of: culturing target toxic microalgae in different sea areas and acquiring toxicity data; determining toxicity values of toxic algae LC50 or LC30 and the like according to a toxicity research result; adopting an ecological model evaluation method of a species sensitivity distribution curve method to evaluate the ecological risk of the toxic microalgae; determining an acceptable effect level end point (HC5) according to the toxicity equivalent of the toxic microalgae and the toxicity value of each experimental organism; evaluating the water ecological species sensitivity risk of the toxic microalgae with different densities; providing a model for 95% species reliability assurance of the system, and quantitatively explaining the regional ecological risk of the toxic microalgae. The method fills the blank at home and abroad, the universal toxic microalgae ecological risk safety evaluation method is not affected by algal biovariability, different water areas can be subjected to modeling for evaluation frominitial separation and cultivation, evaluation is precise, local conditions are adapted, universality is high, operation is easy, and the application range is wide.

The present invention provides a method for regulating multiple water sources in a lake based on a hydrodynamic-water quality-ecological model, which relates to the field of water source regulation technology, including steps of obtaining data, clarifying the occurrence mechanism of spatiotemporal heterogeneity of lake water environment, establishing a model, determining the water quality control threshold for maintaining the health of lake water ecology, and proposing the best multi-water source regulation scheme. The present invention, by improving the BLOOM module, incorporates the phytoplankton characterization into the simulation of the competition mechanism of lake phytoplankton, creates a hydrodynamic-water quality-ecological comprehensive model suitable for lake water environment simulation, improves the accuracy of lake water environment simulation, and thus can better accurately determine the water quality control target of lake water environment health; secondly, by using a variety of water resources for comprehensive regulation of multiple water sources, the water quality of the lake is improved while also improving the comprehensive utilization of regional water resources. The results of the present invention provide scientific and technological support for the water quality management of Chagan Lake, and are also the requirements for implementing the "one lake, one policy" precise governance.

The application discloses a facies intertidal zone sessile organism investigation method based on visual modeling, first, the low tide period of spring tide day is determined in combination with the data of the tidal station, the orthographic image and three-dimensional model of the investigation area are acquired by using the RTK unmanned aerial vehicle, the accurate investigation range is demarcated and the entry and exit paths are planned through the geographic information system processing. The slope parameters are calculated by using the digital land surface model and the personnel equipment configuration is optimized, the ground control points are laid on the site, and the geodetic coordinate system reference is established. The double route oblique photography mode is adopted, the image shooting sampling is carried out at a 45-degree visual angle, a 0.4m object distance and a 70% image overlap rate, the high-precision three-dimensional ecological model is generated through the point cloud reconstruction in combination with the morphological identification result of the species, and the parameters such as the habitat density, interspecific competition and light adaptability of the sessile organism are efficiently investigated.

A cross-chain architecture design and performance analysis method for large-scale Internet of Things based on IOTA blockchain, a multi-field, large-scale distributed Internet of Things, trusted, multi-chain, intelligent and efficient blockchain architecture is designed based on IOTA, which realizes low-cost trusted interconnection of blockchains in different fields and establishes a safe shared ecological model. The delay of one-hop transmission is derived using stochastic calculus theory. From the aspects of consensus time, throughput, security and cross-chain interaction efficiency, the performance of the new architecture is analyzed, providing a theoretical basis for the landing of blockchain. At the same time, in order to speed up information dissemination and reduce network overhead, a directional propagation method is proposed to replace the rumor algorithm of IOTA, reducing network overhead.

The present invention relates to a biological control method and system, a computer program product and a computer-readable storage medium relating to a given area, preferably a given agricultural area, wherein the aim of the invention is to determine the number of biocontrol agents to be introduced into the given area, the frequency with which the biocontrol agents are to be introduced into the given area, and the period during which the biocontrol agents are to be introduced into the given area, by means of a model equation, the model equation applying a mathematical relationship to at least one item of biological modelling data and to at least one item of ecological modelling data, the implementation thereof comprising the use of at least one item of user data.

The invention discloses an early warning method and system based on ecological data processing, and particularly relates to the field of ecological data early warning. According to the method, the value of the missing data point can be predicted more accurately by improving the data interpolation method, and the adaptability prediction capability of ecological meteorology is improved by reflecting the dynamic nature and complexity of an ecological system by adopting a more complex ecological model.

The present application provides a feasibility analysis and dynamic optimization method for interbreeding applied to harbors, comprising: according to harbor climate characteristic data, using a machine learning algorithm to obtain a combination of species suitable for breeding under different climatic conditions, and forming a climate-breeding species adaptability matrix; comprehensively considering water quality parameters and climatic conditions, using an optimization algorithm, determining the optimal breeding species combination plan under the current harbor environment, so as to achieve a balance between breeding feasibility and output; using an ecological model simulation unit to virtually repair the impacted breeding areas, and obtain key control points and regulation parameters for restoring the ecological balance of breeding, so as to guide the implementation of actual restoration work; within the breeding area, obtaining gradient data of each key ecological position, and judging the ecological health status of different areas by analyzing the efficiency of material circulation and energy flow in the gradient data.

The application relates to an IWIND-LR model-based COD index space-time simulation method and system, and belongs to the technical field of water resource management.The method comprises the following steps: based on an IWIND-LR hydrodynamic water quality-ecology model, a grid-discretized hydrodynamic water quality-ecology model of a target water body is built; based on the dynamic change of the carbon cycle process in the water body, a COD index simulation module is developed; the developed COD simulation module equation is coupled with the grid-discretized hydrodynamic water quality-ecology model in an algorithm, and a grid-discretized COD simulation model of the target water body is established; the result of water quality COD space-time simulation analysis is expressed, and a COD time sequence and a two-dimensional and three-dimensional visual layer are output. By adopting the method described in the application, the deficiency of the existing water environment model in expressing the carbon cycle process in the water body can be supplemented, and a calculation platform is provided for the simulation of the COD index of the water body.

The invention discloses a lithofacies intertidal zone fixation organism investigation method based on visual modeling, which comprises the following steps of: firstly, determining a large tide daily low tide period by combining tide station data, acquiring an orthoimage and a three-dimensional model of an investigation area by utilizing an RTK unmanned aerial vehicle, delimiting an accurate investigation range through processing of a geographic information system, and planning an entrance path and an exit path; gradient parameters are calculated through a digital earth surface model, personnel and equipment configuration is optimized, ground control points are arranged on site, and a geodetic coordinate system reference is established; according to the method, a double-route oblique photography mode is adopted, image shooting and sampling are carried out at the view angle of 45 degrees, the object distance of 0.4 m and the image overlapping rate of 70%, a high-precision three-dimensional ecological model is generated through point cloud reconstruction in combination with species morphological identification results, and parameters such as inhabitation density, interspecific competition and light adaptability of fixed organisms are efficiently investigated.

The invention discloses a scattered radiation prediction correction method based on an ANN neural network algorithm, and belongs to the field of atmospheric environment monitoring and ecological meteorological modeling, and the method comprises the following steps: S1, data collection and preprocessing; s2, constructing a model training set; s3, constructing and training an ANN model; s4, model verification and performance evaluation; s5, calculation and correction of scattered radiation fractions; the method aims at solving the problems that scattered radiation fraction (Kd) data in an existing observation network is missing and a traditional empirical model is large in prediction error. Through constructing a trained neural network model, scattered radiation reconstruction of an unobserved site is realized, and high-quality input is further provided for an ecological model.

The application provides a vegetation restoration method for mining wasteland, and relates to the technical field of mining wasteland restoration.The vegetation restoration method for mining wasteland specifically comprises the following steps: S1, data collection;S2, establishment of an ecological model;S3, preparation of a nanometer particle material;S4, synthesis of a nanometer particle;S5, application of a nanometer particle;S6, design of a biomimetic ecological substrate;S7, application of microorganisms;S8, VR restoration simulation.The nanometer particle has efficient adsorption and slow-release functions, can penetrate into the interior of soil, completely remove pollutants, and will not cause secondary pollution.The method provides long-term stable soil improvement effects and persistent support for plant growth through the slow-release function of the nanometer particle and the application of the biomimetic substrate.Real-time data analysis and feedback of an AI system can dynamically adjust the restoration strategy, realize a precise and efficient restoration process, and greatly improve the restoration success rate.

The application provides a kind of blue carbon market self-adaptive accounting method based on multi-source data and bayesian update, belongs to natural resource planning and ecological management technical field;First, the standardized multi-source fusion data set is constructed through the systematic process, then the collected data is preprocessed, and the standardized blue carbon multi-source fusion data set is generated;Then, through the carbon storage estimation model based on bayesian, the prior value of the monitoring point carbon storage is output, the mean value of the monitoring point carbon storage is fused with the spatial prior value, and the distribution of the monitoring point carbon storage is updated;Finally, a carbon credit risk index system is constructed, the risk index of plot layer and regional layer is calculated, the updated monitoring point carbon storage distribution is used to update the mean value of plot layer carbon storage, and the reference transaction price of blue carbon project is generated according to the mean value of carbon storage and risk index.The application constructs a whole-chain blue carbon intelligent accounting system, realizes the interdisciplinary integration of ecological model, deep learning and carbon market mechanism.