CN107610421A - A kind of geo-hazard early-warning analysis system and method - Google Patents

A kind of geo-hazard early-warning analysis system and method Download PDF

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Publication number
CN107610421A
CN107610421A CN201710846157.XA CN201710846157A CN107610421A CN 107610421 A CN107610421 A CN 107610421A CN 201710846157 A CN201710846157 A CN 201710846157A CN 107610421 A CN107610421 A CN 107610421A
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data
analysis
disaster
geo
algorithm
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赵其峰
黄铭铭
侯力峰
刘松
付强
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Hefei Yingze Mdt Infotech Ltd
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Hefei Yingze Mdt Infotech Ltd
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Abstract

The invention discloses a kind of geo-hazard early-warning analysis system and method, a kind of geo-hazard early-warning analysis system includes database, server, data analysis module, data acquisition module, siren;The data acquisition module is coupled by server with data analysis module, database;The data analysis module includes classification analysis unit, cluster analysis unit, Association Rule Analysis unit, regression analysis unit, vector similarity analytic unit, time series analysis unit;The database includes basic geographic database, geological disaster core thematic data base and dynamic monitoring data storehouse;The present invention can be realized by data analysis module effectively to be analyzed the geological information of disaster prone areas, the probability that current disaster may occur is drawn, if reach timely can send alarm and reminding staff by warning device to a certain degree;Easy to use, simple and fast of the invention, the effective analysis and early warning to geological disaster can be realized by the method in the present invention.

Description

A kind of geo-hazard early-warning analysis system and method
Technical field
The invention belongs to big data storage and excavation applications, it is related to a kind of addressing context information, specifically a kind of geology calamity Evil prewarning analysis system and method.
Background technology
Natural calamity of the geological disaster using geology motor activity or geological environment anomalous variation as main reason.In the earth Under power, outer power or artificial geology dynamic action, incorrect energy release, the motion of matter, Rock And Soil deformation displacement occur for the earth And environmental abnormality change etc., endanger human life's property, life and economic activity or destroy the mankind and depend on for existence and development Resource, the phenomenon of environment or process.Bad geological phenomenon is generally termed geological disaster, refers to Natural geologic process and mankind's activity Caused by deteriorate geological environment, reduce environmental quality, directly or indirectly endanger human security, and made to society and economic construction Into the geologic event of loss.Geological disaster refers to, is formed in the presence of nature or human factor, to human life's wealth The geologic process (phenomenon) that production, environment are damaged and lost.And accomplishing the timely early warning of geological disaster can meet people To the loss that lives and properties can be reduced during geological disaster, but instantly for geological disaster prediction be also a lack of it is certain accurate Property and reliability, for solve drawbacks described above, a kind of scheme is now provided.
The content of the invention
It is an object of the invention to provide a kind of geo-hazard early-warning analysis system and method.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of geo-hazard early-warning analysis system, including database, server, data analysis module, data acquisition module, Siren;
The data acquisition module is coupled by server with data analysis module, database;The siren is connected in On server;
The data analysis module includes classification analysis unit, cluster analysis unit, Association Rule Analysis unit, recurrence point Analyse unit, vector similarity analytic unit, time series analysis unit;
The database includes basic geographic database, geological disaster core thematic data base and dynamic monitoring data storehouse;
Further, the data acquisition module is included in geological disaster hotspots laying disaster monitoring point, passes through prison Terminal, sensor, the first-class equipment of shooting are surveyed, using technologies such as GPS, embedded software hardware, sensor, multimedias to Monitoring Data It is acquired, the content of Monitoring Data includes surface displacement, deep displacement, crack displacement, rainfall, water level, stress, osmotic pressure ( Lower water) and video surveillance monitoring data, in addition to mass presdiction and disaster prevention Monitoring Data and inspection report.
Further, the basic geographic database mainly include the whole province 4D basic surveying and mapping products data, image data, Manage solid data, place name geologic data, three-dimensional modeling data, map publishing slice of data, geographical national conditions the Data of General Survey with And other geo-spatial datas;
The address disaster core database mainly include Geological Hazards Investigation data, geological disaster mass presdiction and disaster prevention data, It is dangerous that harnessing project data, resettlement avoid data, calamity dangerous situation management data, emergent investigation and inspection, investigation data, geological disaster Property assessment, plan for prevention and control of geological disaster, professional monitoring data, geological vestige core data, underground water core data;
The dynamic monitoring data storehouse includes the whole province hybrid satellite positioning service system (YNCORS) real time dynamic measurement number According to, geological disaster point dynamic monitoring data.
Further, universal classification algorithm of the classification analysis unit based on bayesian algorithm etc., is mainly used in pre- Survey and differentiate.For example, can be analyzed by sorting algorithm one group of geographical spatial data, predict that mud-rock flow occurs for certain panel region Probability, or genetic analysis and prediction are carried out to mud-rock flow by contrasting data.
Further, general clustering algorithm of the cluster analysis unit based on K-Means etc., available for decision-making point Analysis.For example, cluster analysis can be carried out to the various influence factors of disaster by clustering algorithm, the population characteristic of disaster is distinguished.
Further, generic associative rule-based algorithm of the Association Rule Analysis unit based on FP-Growth etc., mainly For analyzing similarity and correlation rule between different pieces of information collection.For example, certain piece can be analyzed by association rules mining algorithm Correlation rule between the rule of mud-rock flow and rainfall record occurs for region.
Further, general regression algorithm of the regression analysis unit based on linear regression etc., is mainly used in decision-making Analysis.For example, it can help to analyse the origin cause of formation on mud-rock flow or landslide scientifically by regression algorithm.
Further, general vector similarity operator of the vector similarity analytic unit between vector based on distance etc. Method, it is mainly used in the incidence relation excavated between data.For example, incidence relation that can be by vector similarity algorithm to two groups of data Excavation comparison is carried out, excavates the incidence relation between rainfall changing rule and mud-rock flow pests occurrence rule.
Further, the time series analysis unit is based on ARMA model (or mixed model) etc. Generalized time sequence analysis algorithm, it is mainly used in analysis prediction.For example, based on recent meteorological record prediction following a period of time Changes in weather, or changing rule prediction mud-rock flow possibility occurrence from now on is found based on mud-rock flow historical data.
Further, methods described comprises the steps of:
The first step:Data acquisition module is carried out by laying disaster monitoring point in geological disaster hotspots, passes through monitoring Terminal, sensor, the first-class equipment of shooting, are entered using technologies such as GPS, embedded software hardware, sensor, multimedias to Monitoring Data Row collection, the content of Monitoring Data include surface displacement, deep displacement, crack displacement, rainfall, water level, stress, osmotic pressure (underground Water) and video surveillance monitoring data, in addition to the system in mass presdiction and disaster prevention Monitoring Data and inspection report acquisition place to be measured Row related data.
Second step:By surface displacement, deep displacement, crack displacement, rainfall, water level, stress, osmotic pressure (underground water) and regard The monitoring data of frequency monitoring, in addition to mass presdiction and disaster prevention Monitoring Data and inspection report step on data and pass through server transport to data point Dynamic monitoring data storehouse in analysis module analysis and database is stored;
3rd step:The probability of geological disaster may be occurred by analyzing the place by data analysis module, and probability is sent To server;
4th step:, can be by a probability being set with server internal when server receives the probable value of disaster generation Value is compared, and when more than setting probable value, server can control alarm to send alarm.
Beneficial effects of the present invention:The present invention can be accomplished to disaster prone areas geological information by data acquisition unit Real-time collection;It can be realized by data analysis module and the geological information of disaster prone areas is effectively analyzed, drawn The probability that current disaster may occur, if reach timely can send alarm and reminding work people by warning device to a certain degree Member;Geological information when each disaster can be occurred by the setting of database by the present invention is stored the analysis in case in the future Use;Easy to use, simple and fast of the invention, by the method in the present invention can realize effective analysis to geological disaster and Early warning.
Brief description of the drawings
For the ease of it will be appreciated by those skilled in the art that the present invention is further illustrated below in conjunction with the accompanying drawings.
Fig. 1 is the system block diagram of the present invention.
Embodiment
As illustrated, a kind of geo-hazard early-warning analysis system, including database, server, data analysis module, data Acquisition module, siren;
The data acquisition module is coupled by server with data analysis module, database;The siren is connected in On server;
The data analysis module includes classification analysis unit, cluster analysis unit, Association Rule Analysis unit, recurrence point Analyse unit, vector similarity analytic unit, time series analysis unit;
The database includes basic geographic database, geological disaster core thematic data base and dynamic monitoring data storehouse;
Further, the data acquisition module is included in geological disaster hotspots laying disaster monitoring point, passes through prison Terminal, sensor, the first-class equipment of shooting are surveyed, using technologies such as GPS, embedded software hardware, sensor, multimedias to Monitoring Data It is acquired, the content of Monitoring Data includes surface displacement, deep displacement, crack displacement, rainfall, water level, stress, osmotic pressure ( Lower water) and video surveillance monitoring data, in addition to mass presdiction and disaster prevention Monitoring Data and inspection report.
Further, the basic geographic database mainly include the whole province 4D basic surveying and mapping products data, image data, Manage solid data, place name geologic data, three-dimensional modeling data, map publishing slice of data, geographical national conditions the Data of General Survey with And other geo-spatial datas;
The address disaster core database mainly include Geological Hazards Investigation data, geological disaster mass presdiction and disaster prevention data, It is dangerous that harnessing project data, resettlement avoid data, calamity dangerous situation management data, emergent investigation and inspection, investigation data, geological disaster Property assessment, plan for prevention and control of geological disaster, professional monitoring data, geological vestige core data, underground water core data;
The dynamic monitoring data storehouse includes the whole province hybrid satellite positioning service system (YNCORS) real time dynamic measurement number According to, geological disaster point dynamic monitoring data.
Further, universal classification algorithm of the classification analysis unit based on bayesian algorithm etc., is mainly used in pre- Survey and differentiate.For example, can be analyzed by sorting algorithm one group of geographical spatial data, predict that mud-rock flow occurs for certain panel region Probability, or genetic analysis and prediction are carried out to mud-rock flow by contrasting data.
Further, general clustering algorithm of the cluster analysis unit based on K-Means etc., available for decision-making point Analysis.For example, cluster analysis can be carried out to the various influence factors of disaster by clustering algorithm, the population characteristic of disaster is distinguished.
Further, generic associative rule-based algorithm of the Association Rule Analysis unit based on FP-Growth etc., mainly For analyzing similarity and correlation rule between different pieces of information collection.For example, certain piece can be analyzed by association rules mining algorithm Correlation rule between the rule of mud-rock flow and rainfall record occurs for region.
Further, general regression algorithm of the regression analysis unit based on linear regression etc., is mainly used in decision-making Analysis.For example, it can help to analyse the origin cause of formation on mud-rock flow or landslide scientifically by regression algorithm.
Further, general vector similarity operator of the vector similarity analytic unit between vector based on distance etc. Method, it is mainly used in the incidence relation excavated between data.For example, incidence relation that can be by vector similarity algorithm to two groups of data Excavation comparison is carried out, excavates the incidence relation between rainfall changing rule and mud-rock flow pests occurrence rule.
Further, the time series analysis unit is based on ARMA model (or mixed model) etc. Generalized time sequence analysis algorithm, it is mainly used in analysis prediction.For example, based on recent meteorological record prediction following a period of time Changes in weather, or changing rule prediction mud-rock flow possibility occurrence from now on is found based on mud-rock flow historical data.
Further, methods described comprises the steps of:
The first step:Data acquisition module is carried out by laying disaster monitoring point in geological disaster hotspots, passes through monitoring Terminal, sensor, the first-class equipment of shooting, are entered using technologies such as GPS, embedded software hardware, sensor, multimedias to Monitoring Data Row collection, the content of Monitoring Data include surface displacement, deep displacement, crack displacement, rainfall, water level, stress, osmotic pressure (underground Water) and video surveillance monitoring data, in addition to the system in mass presdiction and disaster prevention Monitoring Data and inspection report acquisition place to be measured Row related data.
Second step:By surface displacement, deep displacement, crack displacement, rainfall, water level, stress, osmotic pressure (underground water) and regard The monitoring data of frequency monitoring, in addition to mass presdiction and disaster prevention Monitoring Data and inspection report step on data and pass through server transport to data point Dynamic monitoring data storehouse in analysis module analysis and database is stored;
3rd step:The probability of geological disaster may be occurred by analyzing the place by data analysis module, and probability is sent To server;
4th step:, can be by a probability being set with server internal when server receives the probable value of disaster generation Value is compared, and when more than setting probable value, server can control alarm to send alarm.
The present invention can accomplish the real-time collection to disaster prone areas geological information by data acquisition unit;Pass through number It can be realized according to analysis module and the geological information of disaster prone areas is effectively analyzed, draw what current disaster may occur Probability, if reach timely can send alarm and reminding staff by warning device to a certain degree;The present invention passes through data Geological information when each disaster can occur for the setting in storehouse is stored in case analysis in the future uses;User of the present invention Just, simple and fast, the effective analysis and early warning to geological disaster can be realized by the method in the present invention.
Above content is only to structure example of the present invention and explanation, affiliated those skilled in the art couple Described specific embodiment is made various modifications or supplement or substituted using similar mode, without departing from invention Structure surmounts scope defined in the claims, all should belong to protection scope of the present invention.

Claims (10)

1. a kind of geo-hazard early-warning analysis system, it is characterised in that including database, server, data analysis module, data Acquisition module, siren;
The data acquisition module is coupled by server with data analysis module, database;The siren is connected in service On device;
The data analysis module includes classification analysis unit, cluster analysis unit, Association Rule Analysis unit, regression analysis list Member, vector similarity analytic unit, time series analysis unit;
The database includes basic geographic database, geological disaster core thematic data base and dynamic monitoring data storehouse.
A kind of 2. geo-hazard early-warning analysis system according to claim 1, it is characterised in that the data acquisition module It is included in geological disaster hotspots and lays disaster monitoring point, by monitoring terminal, sensor, the first-class equipment of shooting, uses The technologies such as GPS, embedded software hardware, sensor, multimedia are acquired to Monitoring Data, and the content of Monitoring Data includes earth's surface Displacement, deep displacement, crack displacement, rainfall, water level, stress, the monitoring data of osmotic pressure (underground water) and video surveillance, are also wrapped Include mass presdiction and disaster prevention Monitoring Data and inspection report.
A kind of 3. geo-hazard early-warning analysis system according to claim 1, it is characterised in that the geo-spatial data Storehouse mainly includes the whole province 4D basic surveying and mapping products data, image data, geographical entity data, place name geologic data, threedimensional model Data, map publishing slice of data, geographical national conditions the Data of General Survey and other geo-spatial datas;
The address disaster core database mainly includes Geological Hazards Investigation data, geological disaster mass presdiction and disaster prevention data, administered Project data, resettlement avoid data, calamity dangerous situation management data, emergent investigation and inspection, investigation data, geological hazard dangerous and commented Estimate, plan for prevention and control of geological disaster, professional monitoring data, geological vestige core data, underground water core data;
The dynamic monitoring data storehouse include the whole province's hybrid satellite positioning service system (YNCORS) real time dynamic measurement data, Matter disaster point dynamic monitoring data.
A kind of 4. geo-hazard early-warning analysis system according to claim 1, it is characterised in that the classification analysis unit Universal classification algorithm based on bayesian algorithm etc., is mainly used in predicting and differentiates.For example, can be by sorting algorithm to one group Geographical spatial data is analyzed, and predicts that the probability of mud-rock flow occurs for certain panel region, or mudstone is flowed into by contrasting data Row genetic analysis and prediction.
A kind of 5. geo-hazard early-warning analysis system according to claim 1, it is characterised in that the cluster analysis unit General clustering algorithm based on K-Means etc., available for Analysis of Policy Making.For example, can be by clustering algorithm to the various of disaster Influence factor carries out cluster analysis, distinguishes the population characteristic of disaster.
A kind of 6. geo-hazard early-warning analysis system according to claim 1, it is characterised in that the Association Rule Analysis Generic associative rule-based algorithm of the unit based on FP-Growth etc., be mainly used in analyze different pieces of information collection between similarity and Correlation rule.For example, can be by association rules mining algorithm, the rule for analyzing certain panel region generation mud-rock flow records it with rainfall Between correlation rule.
A kind of 7. geo-hazard early-warning analysis system according to claim 1, it is characterised in that the regression analysis unit General regression algorithm based on linear regression etc., is mainly used in Analysis of Policy Making.For example, science can be helped by regression algorithm Analyze the origin cause of formation on mud-rock flow or landslide.
A kind of 8. geo-hazard early-warning analysis system according to claim 1, it is characterised in that the vector similarity point General vector similarity algorithm of the unit between vector based on distance etc. is analysed, is mainly used in the incidence relation excavated between data.Example Such as, can carry out excavation comparison to the incidence relation of two groups of data by vector similarity algorithm, excavate rainfall changing rule with Incidence relation between mud-rock flow pests occurrence rule.
A kind of 9. geo-hazard early-warning analysis system according to claim 1, it is characterised in that the time series analysis Generalized time sequence analysis algorithm of the unit based on ARMA model (or mixed model) etc., is mainly used in analyzing Prediction.For example, the Changes in weather of following a period of time is predicted based on recent meteorological record, or based on mud-rock flow historical data It was found that the mud-rock flow possibility occurrence of changing rule prediction from now on.
10. a kind of geo-hazard early-warning method according to claim 1, it is characterised in that methods described includes following step Suddenly:
The first step:Carry out data acquisition module by laying disaster monitoring point in geological disaster hotspots, by monitoring terminal, Sensor, the first-class equipment of shooting, are adopted using technologies such as GPS, embedded software hardware, sensor, multimedias to Monitoring Data Collection, the content of Monitoring Data include surface displacement, deep displacement, crack displacement, rainfall, water level, stress, osmotic pressure (underground water) with And the monitoring data of video surveillance, in addition to mass presdiction and disaster prevention Monitoring Data and a series of correlations in inspection report acquisition place to be measured Data.
Second step:Surface displacement, deep displacement, crack displacement, rainfall, water level, stress, osmotic pressure (underground water) and video are supervised The monitoring data of survey, in addition to mass presdiction and disaster prevention Monitoring Data and inspection report step on data and pass through server transport to data analysis mould Dynamic monitoring data storehouse in block analysis and database is stored;
3rd step:The probability of geological disaster may be occurred by analyzing the place by data analysis module, and probability is sent into clothes Business device;
4th step:When server receives the probable value of disaster generation, it can be entered by the probable value set with server internal Row compares, and when more than setting probable value, server can control alarm to send alarm.
CN201710846157.XA 2017-09-19 2017-09-19 A kind of geo-hazard early-warning analysis system and method Pending CN107610421A (en)

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Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108595658A (en) * 2018-04-28 2018-09-28 尚谷科技(天津)有限公司 A kind of weather knowledge base detection method based on multimedia content
CN108765880A (en) * 2018-07-13 2018-11-06 夏璐 Geological disaster monitors in real time and early warning system
CN108961688A (en) * 2018-07-13 2018-12-07 福建特力惠信息科技股份有限公司 A kind of big data support under Geological Hazards Monitoring and method for early warning
CN109448327A (en) * 2018-12-04 2019-03-08 辽宁工程技术大学 A kind of geo-hazard early-warning device and method
CN109637088A (en) * 2018-12-29 2019-04-16 宁波中数云创信息技术有限公司 A kind of real time early warning method based on big concurrent incremental data
CN109887240A (en) * 2019-03-22 2019-06-14 福州大学 A kind of landslide disaster safety monitoring and method for early warning based on artificial intelligence
CN109920202A (en) * 2018-02-06 2019-06-21 四川省泰龙建设集团有限公司 A kind of real-time security monitoring early-warning system and monitoring and early warning method
CN110008301A (en) * 2019-04-12 2019-07-12 杭州鲁尔物联科技有限公司 Regional susceptibility of geological hazards prediction technique and device based on machine learning
CN110211336A (en) * 2019-05-16 2019-09-06 西南交通大学 The method of sensor-based landslide data intelligence processing
CN110473385A (en) * 2019-07-30 2019-11-19 中石化石油工程技术服务有限公司 Oil-gas pipeline Geological Hazards Monitoring early warning system
CN111429698A (en) * 2020-03-24 2020-07-17 东华理工大学 Geological disaster early warning system

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101354757A (en) * 2008-09-08 2009-01-28 中国科学院地理科学与资源研究所 Method for predicting dynamic risk and vulnerability under fine dimension
CN102013150A (en) * 2010-09-28 2011-04-13 浙江工业大学 System for predicting geologic hazard based on rainfall intensity, moisture content of slope soil and deformation
CN102354431A (en) * 2011-08-06 2012-02-15 河北省第一测绘院 Monitoring and prewarning system and method for geological disasters
CN102610059A (en) * 2012-03-01 2012-07-25 河海大学 Monitoring and prewarning system for sudden flood in mountainous area and establishing method thereof
CN103017709A (en) * 2012-12-20 2013-04-03 青岛理工大学 Method for measuring geological landslide displacement by using rainfall
CN103559775A (en) * 2013-11-12 2014-02-05 武汉大学 Urban flood disaster early warning system and method
CN103646513A (en) * 2013-11-27 2014-03-19 武汉地大信息工程股份有限公司 Geological disaster early warning system and early warning method
JP2016211243A (en) * 2015-05-11 2016-12-15 有限会社秋山調査設計 Slope face stabilization analysis method

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101354757A (en) * 2008-09-08 2009-01-28 中国科学院地理科学与资源研究所 Method for predicting dynamic risk and vulnerability under fine dimension
CN102013150A (en) * 2010-09-28 2011-04-13 浙江工业大学 System for predicting geologic hazard based on rainfall intensity, moisture content of slope soil and deformation
CN102354431A (en) * 2011-08-06 2012-02-15 河北省第一测绘院 Monitoring and prewarning system and method for geological disasters
CN102610059A (en) * 2012-03-01 2012-07-25 河海大学 Monitoring and prewarning system for sudden flood in mountainous area and establishing method thereof
CN103017709A (en) * 2012-12-20 2013-04-03 青岛理工大学 Method for measuring geological landslide displacement by using rainfall
CN103559775A (en) * 2013-11-12 2014-02-05 武汉大学 Urban flood disaster early warning system and method
CN103646513A (en) * 2013-11-27 2014-03-19 武汉地大信息工程股份有限公司 Geological disaster early warning system and early warning method
JP2016211243A (en) * 2015-05-11 2016-12-15 有限会社秋山調査設計 Slope face stabilization analysis method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
王滨等: "基于因子-聚类分析的泥石流危险性评价研究-以重庆市北碚区为例", 《现代地质》 *
蔡立乾: "地质灾害数据采集系统的研究与分析", 《中国优秀硕士学位论文全文数据库信息科技辑》 *

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109920202A (en) * 2018-02-06 2019-06-21 四川省泰龙建设集团有限公司 A kind of real-time security monitoring early-warning system and monitoring and early warning method
CN108595658A (en) * 2018-04-28 2018-09-28 尚谷科技(天津)有限公司 A kind of weather knowledge base detection method based on multimedia content
CN108765880A (en) * 2018-07-13 2018-11-06 夏璐 Geological disaster monitors in real time and early warning system
CN108961688A (en) * 2018-07-13 2018-12-07 福建特力惠信息科技股份有限公司 A kind of big data support under Geological Hazards Monitoring and method for early warning
CN109448327A (en) * 2018-12-04 2019-03-08 辽宁工程技术大学 A kind of geo-hazard early-warning device and method
CN109637088A (en) * 2018-12-29 2019-04-16 宁波中数云创信息技术有限公司 A kind of real time early warning method based on big concurrent incremental data
CN109887240A (en) * 2019-03-22 2019-06-14 福州大学 A kind of landslide disaster safety monitoring and method for early warning based on artificial intelligence
CN110008301A (en) * 2019-04-12 2019-07-12 杭州鲁尔物联科技有限公司 Regional susceptibility of geological hazards prediction technique and device based on machine learning
CN110211336A (en) * 2019-05-16 2019-09-06 西南交通大学 The method of sensor-based landslide data intelligence processing
CN110473385A (en) * 2019-07-30 2019-11-19 中石化石油工程技术服务有限公司 Oil-gas pipeline Geological Hazards Monitoring early warning system
CN111429698A (en) * 2020-03-24 2020-07-17 东华理工大学 Geological disaster early warning system

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Application publication date: 20180119