32 results about "Climate index" patented technology

A system and method for providing multivariate climate change forecasting are provided that obtain, from one or more climate model datasets, simulated historical and future climate model data, and from one or more climate observational datasets, historical observed climate data. A statistical distribution, using a Bayesian model, is provided of extremes or climate indices for one or more variable climate features using the simulated climate model data and the observed climate data. One or more metrics are determined, including a prediction of a future climate variable for a determined future time period, a confidence bound of the prediction of the future climate variable for the determined future time period, and a prediction bound for the future climate variable for the determined future time period. The metrics can be transmitted to a variety of applications in a variety of formats.

The invention discloses a glacial lake burst early-warning method. Aiming at the defects that the adopted index is not reasonable, modification on observation data is over-simple in the existing glacial lake burst early-warning method, the invention provides the glacial lake burst early-warning method comprehensively considering the affects from an atmospheric temperature and the rainfall condition. According to the method, long-term observation data of temperature and rainfall in an observatory station is obtained and analyzed by a control center, a cumulative positive temperature daily increasing speed value TV in early days of a forecast date and a rainfall daily increasing speed value RV in early 30 days of the forecast date are calculated, and the TV value and the RV value are simultaneously subjected to double-index comparison with a burst warning curve RV=2.7214TV<-0.956> to judge the burst risks of the glacial lake, and an alarming system is started by the control center if necessary. According to the method, the corresponding relationship between two specific indexes of the cumulated temperature daily increasing speed value and the rainfall daily increasing speed value in early 30 days which are selected from numerous temperature and rainfall indexes and the glacial lake burst danger is determined, and the burst early-warning curve is determined. The forecast is carried out according to a more comprehensive and reasonable climate index, so the early-warning effectiveness is increased.

The invention provides a crop yield prediction method. The prediction method comprises the following steps: firstly, establishing a comprehensive yield assessment model containing an unknown coefficient based on a trend yield model, a comprehensive climate index model and a growth key period (EVI), and then solving the unknown coefficient in the comprehensive yield assessment model containing theunknown coefficient by utilizing historical data to obtain a comprehensive yield assessment model; and finally, obtaining meteorological data and EVI data of a target yield assessment year, inputtingthe meteorological data and the EVI data into the comprehensive yield assessment model, and predicting the yield of the target yield assessment year. The comprehensive yield estimation model based onthe trend yield, the comprehensive climate index and the growth key period EVI is constructed, so that the yield estimation of the winter wheat in the whole growth period is realized from a more comprehensive perspective, and the yield estimation precision of the winter wheat is improved.

The invention discloses a method for association rule mining of ocean-land climate events with combination of a climate subdivision thought. A Delaunay triangulation network of space data is established and an overall and local long-side constraint is exerted on the space data, so that a reasonable and stable space adjacent relation network is obtained, the similarity of a time series of space adjacent entities is measured, hierarchical clustering is conducted to obtain a hierarchical cluster result, and a good climate subdivision result is obtained on the basis of false-T statistical magnitude analysis; a prior knowledge constraint of a related field is brought in and interested climate events are extracted from ocean climate indexes and land climate zones respectively, so that effective association rules among the ocean-land climate events are mined through exertion of a time window width constraint, a time delay constraint and a sufficiency and necessity constraint. The multi-scale effect can be effectively considered in the mining process so that an effective climate zone can be obtained and high efficiency, pertinence and practicability can be achieved through multiple constraints when the association rules are mined.

The invention discloses a medium-and-long-term rainfall forecast modeling method based on whole-process coupling machine learning, and the method comprises the following steps: S1, data processing: collecting actually measured rainfall, 130 meteorological-climate indexes and other data, and determining a forecast structure; s2, factor screening: providing a factor screening method based on Laplacian fractional-recursive feature elimination, and obtaining a forecast factor set; s3, model construction: constructing a plurality of machine learning models, and solving a plurality of sets of sub-forecasting results by adopting the forecasting structure and the forecasting factor set; and S4, multi-model fusion: providing a multi-model fusion technology based on an improved stacking method, and outputting a final forecast result. According to the method, the latest research result of the machine learning theory is applied to each link of medium and long term rainfall forecasting, the theoretical basis is sufficient, the practical application is reasonable, and the accuracy and the reliability of month-season-year scale rainfall forecasting can be effectively improved.

The invention discloses a construction method of electricity market climate index, counting external economic factors. The construction method of electricity market climate index, counting external economic factors includes the steps: 1) collecting and arranging the electricity consumption and various economic data in the external environment, and screening the electricity consumption and variouseconomic data; 2) performing seasonal adjustment and standardization on each screened data sequence; 3) performing principal component analysis on the electricity consumption and each economic index,and constructing the preliminary market climate index; 4) performing a stationary test or co-integration test on the electricity consumption and each economic index, and performing Granger cause and effect relation examination; and 5) based on the Granger cause and effect relation examination result, correcting the coefficient of each economic index in the market economy indexes, and constructingthe final electricity market climate index. Based on the principal component analysis and co-integration theory, the construction method of electricity market climate index, counting external economicfactors provides an integrated construction method of electricity market climate index, and has important reference meaning for the influence degree of each economic factors on the electricity consumption and the development trend of the overall electricity market.

The invention discloses a screening and handling method for climate indexes. The screening and handling method comprises the steps that climate monitoring indexes in a cigarette raw material producing area are used as the basis, factors and correlation analysis are applied to determine a characteristic index of a climate evaluation factor, probability distribution and standard deviation method weight coefficients are adopted to obtain the evaluation standard for the characteristic index, K-means clustering and multi-accumulating stepwise discriminant analysis are used for building a discrimination function and inspecting accuracy of the discrimination function, finally, a base unit climate index comprehensive classification result is determined, and the cigarette industrial raw material base layout is optimized according to the result. According to the screening and handling method for the climate indexes, the climate indexes capable of accurately analyzing and evaluating the cigarette raw material base are screened out more systematically and more comprehensively from the climate indexes of a plurality of base units, the lateral linkage of the climate indexes is built, and redundant information among the climate evaluation indexes is avoided. The invention further provides an evaluation method for the cigarette raw material base, and the decision-making basis and theoretical supports can be effectively and rapidly provided for optimization of the cigarette industrial enterprise base unit layout.

The invention discloses a medium and long term runoff forecasting method based on an improved particle swarm optimization algorithm and a support vector machine, which comprises the following steps: selecting historical data of a plurality of climate indexes and historical runoff volume of a drainage basin to be forecasted, and selecting forecasting factors from the historical data of the plurality of climate indexes and processing the forecasting factors, combining with the historical runoff volume of the drainage basin to be forecasted to construct a model data set, and dividing the model data set into a training set and a test set; performing stretching operation on the particles falling into local optimum to obtain an improved particle swarm optimization algorithm; obtaining an optimal parameter combination of the SVR based on an improved particle swarm optimization algorithm to establish an SVR forecasting model based on the improved particle swarm optimization algorithm, and training the forecasting model by using the training set; and comparing an output result obtained by inputting the test set into the forecasting model with real runoff data in the test set, and evaluating a forecasting effect of the forecasting model. The method has the advantages that the forecasting precision and generalization ability of the medium-and-long-term forecasting method are improved, and the problems of low forecasting precision and the like caused by easy falling into local optimum can be effectively avoided.

The invention discloses a formulated fertilization method for a young oil tea forest and belongs to the field of formulated fertilization. The formulated fertilization method for the young oil tea forest is used for soil measurement based on influences of multiple factors including terrains, climates and soil. The fertilization method is adopted for measuring different terrain indexes, climate indexes, soil indexes and the corresponding growth amount of the young oil tea forest; a main component analysis method, a Delphi method and a Pearson correlational analysis method are adopted for screening out the terrain index, climate index and/or soil index which are correlated with the growth amount of the young oil tea forest in order to create a minimum data set; according to the minimum dataset, a nutrient benefit model is created, and different nutrient distribution proportions are calculated; the nutrient utilization efficiency is analyzed by means of data envelopment analysis; according to the nutrient distribution proportions and the nutrient utilization efficiency, the fertilization amount of the oil tea forest under different terrain conditions, different climate conditions anddifferent soil conditions is determined. The disclosed formulated fertilization method for the young oil tea forest is applicable to the different terrain conditions, the different climate conditionsand the different soil conditions, correspondingly input of fertilizer is reasonable, and the fertilizer utilization rate and the growth amount of the young oil tea forest are increased.

The invention discloses a multi-species crop agroclimate regionalization method. The method comprises the steps that according to the climate indexes of regionalization crop sowing and maturation, and under 80% climate assurance rate, the spatial distribution of climate growth period length of a crop is calculated; then classification marking is carried out according to a certain time interval to obtain a climate growth period length regionalization map of the crop. According to the method, the regionalization and the classification are carried out by taking the climate growth period length as parameters, the number of days of climate growth period length at a place with insufficient climatic resources is lower, the number of days of climate growth period length at a place with abundant climatic resources is higher, and therefore each species is planted in a region with the corresponding climate growth period length according to the own growth period length attribute. The climate resources are fully utilized, the quality potential and the production increase potential of each species are fully exerted, the planting area is effectively enlarged, and meanwhile, the harm of the meteorological disasters can be effectively reduced by the 80% assurance rate.

The invention discloses a method for selecting and verifying the planting regions of foreign flue-cured tobacco varieties. The cosine value of an included angle between the same climate indexes of domestic selected tobacco regions and a foreign target tobacco region based on years of climate monitoring data of high-quality tobacco regions at home and abroad in order to evaluate the climate similarity among different tobacco planting regions, and the similarity is high if the value is close to 1; and the Euclidean distance value among the tobacco leaf quality indexes is calculated based on thedetection data of the appearance quality, the conventional chemical composition and the sensory quality of flue-cured tobacco leaves in the tobacco regions to evaluate the tobacco leaf quality similarity among different tobacco regions and verify the tobacco leaf quality similarity between the selected domestic tobacco regions and the foreign target tobacco region, the similarity is low if the distance value is large, and two algorithms are combined to finally determine a domestic tobacco planting region most close to the foreign target tobacco region in climate and quality styles. In the method of the embodiment of the invention, the Zimbabwe tobacco region is used as the foreign target tobacco region.

The invention discloses a fertilization method for an adult tea-oil tree forest formula, and belongs to the field of formula fertilization. The soil measurement formula tea-oil tree forest fertilization method is based on terrain, climate and soil multi-factor influences. The fertilization method comprises the steps that different terrain indexes, climate indexes, soil indexes and corresponding tea-oil tree yields are measured; principal component analysis, the Delphi method and the Pearson related analysis method are adopted, terrain indexes, climate indexes and/or soil indexes with relevancewith the tea-oil tree yield are screened out to form a minimum data set; according to the minimum data set, a nutrient benefit model is built, and the distribution proportion of different nutrients is calculated; the nutrient utilization efficiency is analyzed through data envelopment; according to the different-nutrient distribution proportion and the nutrient utilization efficiency, the tea-oiltree forest fertilization amount under different terrain, climate and soil conditions can be determined. The adult tea-oil tree forest formula fertilization method is applicable to different terrain,climate and soil conditions, so that the fertilizer input is reasonable, the fertilizer utilization rate is increased, and the adult tea-oil tree forest yield is increased.

The invention discloses an accurate and economical method for mobile measurement of a street thermal environment. The method comprises the steps: selecting representative spaces in a to-be-measured region as measurement point spaces, and measuring an outdoor thermal environment; calculating a general thermal climate index of each measuring point space; classifying the measuring point spaces based on the sky view angle factors, and calculating average values of general thermal climate indexes of different types of measuring point spaces at different moments; determining the accuracy of the general thermal climate indexes of each measuring point space at each moment; establishing a platform about the accuracy of measuring point spaces, time and general thermal climate indexes; calculating all continuous paths giving consideration to all moments in the platform; by adopting a multi-objective optimization algorithm, and by taking the accuracy and the space number of the measuring points as objectives, screening out an optimized path; and performing mobile observation of the urban thermal environment along the optimized path. According to the invention, the limitation of street thermal environment measurement in the prior art is solved, and the purpose of improving the accuracy and economical efficiency of outdoor thermal environment measurement is achieved.

The intelligent maintenance management system provided by the embodiment of the invention can realize real-time change of agricultural climate indexes and soil indexes. A user can know the factor change of the environment of the current park or greening project in real time through the intelligent maintenance management system, and manage and configure the irrigation time of the greening area; according to the automatic irrigation mode, when the environment changes, a sensor reports data, and an electromagnetic valve actively links a water valve switch according to the data change under a preset rule; an operator can use an intelligent irrigation system of the system to control a greening purpose water valve to be opened and closed, and the water valve is automatically opened and closed according to rules set by the rule engine; an operator can check early warning information, manage greening projects in real time and check daily, weekly, monthly, seasonal and annual maintenance reports. A manager can manage greening projects, including area division, equipment access, rule setting, early warning setting and the like, and system management operation can be carried out conveniently.

The invention discloses a forest fire monitoring method based on a wireless sensor network. The number of sensors needing to be arranged in a forest of a unit area is determined by adopting a Bayesianclassifier; a sensor network is arranged, the four measured basic weather condition parameters are substituted into a pre-established closed form equation of dependence of a fine fuel humidity specification and a fire climate index on weather conditions; the threat degree representing possible fire disasters is calculated, the influence of sensor distribution on the FFMC and the FWI can be quantified, the needed precision is achieved in the FFMC and the FWI, accurate prediction of the forest fire disasters is achieved, meanwhile, the lowest cost is guaranteed, and the method is easy to implement and does not need any specific node deployment scheme. Thus, the nodes may be deployed in a unified manner, such as throwing them from an aircraft. Therefore, node deployment in real life is greatly facilitated.

A method for detect economic prosperity index comprises that follow steps: establishing a hierarchical dynamic factor model; establishing a corresponding hierarchical dynamic factor model of economicprosperity index accord to various consumption quantities corresponding to hierarchical and administrative level zoning of electric power system; setting up a hierarchical dynamic factor model of economic prosperity index according to various consumption quantities corresponding to administrative level zoning; estimating the parameters of the model; estimating the parameters of the model based onthe hierarchical dynamic factor model of economic prosperity index according to the hierarchy of the power system and the consumption corresponding to the administrative level zoning; adjusting the economic climate index; adjusting the corresponding economic climate index according to the hierarchy of the power system and the corresponding economic indicators of the administrative level zoning. The present invention relates to an electronic device and a readable storage medium for performing an economic prosperity index detection method. The invention can fully describe the correlation difference between different regions and industries and the electric power boom index by introducing the structural evaluation, and can correct the difference according to the structural evaluation and the industrial structure coefficient.

An analysis method of economic climate index based on regional electricity characteristics, in which economic indicators and electricity consumption indicators to be used in the calculation of the economic climate index are selected based on the economic data and power consumption data of the region to be tested and then the clustering method and lag correlation method are applied to said economic indicators and power consumption indicators to obtain leading indicator, coincident indicator and lagging indicator, and after that the composite index method is used to get the economic climate index of the region to be tested,thus allowing for accurate test of the economic climate index based on the power consumption characteristics of the region tested.

The embodiment of the invention discloses a crop climate risk identification method and device and computer equipment, and relates to the technical field of risk assessment, and the method comprises the steps: obtaining climate index data and crop disaster data, and generating a climate risk general survey data matrix; rearranging the climate index data according to the ascending or descending sequence of each piece of climate index data to obtain a single climate index data matrix; according to the single climate index data matrix, judging whether the climate index is a primary climate risk index or not by adopting a given technical method; and carrying out independence test on all the primarily selected climate risk indexes by adopting a given analysis method to obtain climate risk factors. The technical scheme provided by the invention is extremely easy to realize through a computer program, passes actual measurement and inspection, has universality, objectively and quantitatively obtains a result, and is convenient for further manual analysis.

The invention discloses an agricultural product supply early warning system for natural disaster influence. The agricultural product supply early warning system comprises a meteorological information acquisition module, an information type distinguishing module, an information database platform, a quartered graph model evaluation module, an early warning issuing module, a differentiation emergency response module and an information feedback module. The quartered graph evaluation model comprises a'region-climate 'double-index threshold value, and data judgment is performed on the region index database and the climate index database according to the threshold value. According to the invention, regional meteorological disaster early warning signals can be received in real time, meteorological data and corresponding geographic location data are comprehensively integrated and analyzed, accurate forecasting and timely evaluation are carried out, an information basis is provided for agricultural product supply strategy selection under the influence of natural disasters, and preparations are made for in-disaster resistance and rescue; the response speed of government functional departments to emergencies is improved, so that the supply capacity of agricultural products is guaranteed as much as possible, and the loss of natural disasters is reduced to the minimum.

The invention discloses a composite extreme climate event identification method and system, which are different from an identification method of a single climate index threshold value, the method combines various climate index types to identify the composite extreme climate of a to-be-identified area, and the influence range of the composite extreme climate is identified more comprehensively. Furthermore, the method can also identify the moving track of the central grid point of each composite extreme climate sub-type in the composite extreme climate area. The influence change of the compound extreme climate is further vividly displayed, so that technicians can conveniently analyze the climate change and the influence brought by the compound climate.