Research on the Prediction Model for the Security Situation of Metro Station Based on PSO/SVM

Security situation awareness is a new technology about security. This paper brings it to the assessment of security situation of metro station which serves as a new way to secure the security of passengers as well as the operation of the metro station. This paper sets up an index system for assessing the security situation awareness and makes a prediction model for the security situation of metro station based on PSO/SVM after doing lots of researches and analyses. Furthermore, through case studies, we find that the model has high accuracy and ability to accurately predict the security situation of metro station in the future and a certain practical value.

Intensifying Earthquake Prediction in the Light of Action of International Decade for Natural Disaster Reduction

This paper is a review on earthquake prediction and forecast research,progress in earthquake prediction work and pre-estimation of earthquake hazard degree in China in recent years.It indicates that China is the first country,the government of which has promoted and organized the state administration department on reduction of seismic hazards and ensured the socialization of earthquake prediction and forecast in the world.A program of earthquake prevention and protection and hazard reduction based on the results of research on earthquake occurrence regularities and prediction of earthquake preparation trend has been completed,and hence the socialization of results of earthquake prediction and forecast research can be expected to be in practice.The practical seismological works in last 20 years indicate that the earthquakes are not considered to be unpredictable,but it is a challenge remaining to be accepted.We are willing to cooperate with all friends who are engaged in earthquake prediction and

Current status and prospects of research on safety situation awareness of high speed railway operation environment

Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters,perimeter intrusion and external environmental hazards.The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.Design/methodology/approach–In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments,the research status is elaborated,and the latest research progress and achievements of the team are introduced.This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological,perimeter and external environmental situation perception methods for high-speed rail operation.Findings–Based on the technical route of“situational awareness evaluation warning active control,”a technical system for monitoring the safety of high-speed train operation environments has been formed.Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters,perimeter intrusion and the external environment on high-speed rail safety.These works strongly support the improvement of China’s railway environmental safety guarantee technology.Originality/value–With the operation of CR450 high-speed trains with a speed of 400 kmper hour and the application of high-speed train autonomous driving technology in the future,new and higher requirements have been put forward for the safety of high-speed rail operation environments.The following five aspects of work are urgently needed:(1)Research the single factor disaster mechanism of wind,rain,snow,lightning,etc.for high-speed railways with a speed of 400 kms per hour,and based on this,study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment,revealing the coupling disastermechanism ofmultiple influencing factors;(2)Research covers multi-source data fusion methods and associated features such as disaster monitoring data,meteorological information,route characteristics and terrain and landforms,studying the spatio-temporal evolution laws of meteorological disasters,perimeter intrusions and external environmental hazards;(3)In terms of meteorological disaster situation awareness,research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines;(4)In terms of perimeter intrusion,research amulti-modal fusion perception method for typical scenarios of high-speed rail operation in all time,all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and(5)In terms of external environment,based on the existing general network framework for change detection,we will carry out research on change detection and algorithms in the surrounding environment of highspeed rail.

RS and GIS-based Statistical Analysis of Secondary Geological Disasters after the 2008 Wenchuan Earthquake

Using RS and GIS means, this article analyzes the general geological characteristics and the structural belt distribution features in Wenchuan County, Sichuan province, P.R. China as well as the characteristics of the large-scale landslides, mud-rock flows, earthquake lakes, etc., after the earthquake on May 12, 2008. Based on the above work, comprehensive indoor and outdoor research is launched on disaster distribution characteristics and their relationship with earthquakes, terrains, strata, lithology, and structures. Weights of evidence method is utilized to quantitatively analyze and evaluate the spatial distribution of secondary geological disasters after the earthquake occurred. 3 remedying grades for secondary geological disasters are derived from the results of the weights of Evidence, followed by suggestions given to remedy earthquake secondary disasters.

System Architecture and Key Technologies of Network Security Situation Awareness System YHSAS

Network Security Situation Awareness System YHSAS acquires,understands and displays the security factors which cause changes of network situation,and predicts the future development trend of these security factors.YHSAS is developed for national backbone network,large network operators,large enterprises and other large-scale network.This paper describes its architecture and key technologies:Network Security Oriented Total Factor Information Collection and High-Dimensional Vector Space Analysis,Knowledge Representation and Management of Super Large-Scale Network Security,Multi-Level,Multi-Granularity and Multi-Dimensional Network Security Index Construction Method,Multi-Mode and Multi-Granularity Network Security Situation Prediction Technology,and so on.The performance tests show that YHSAS has high real-time performance and accuracy in security situation analysis and trend prediction.The system meets the demands of analysis and prediction for large-scale network security situation.

Disaster prediction of coal mine gas based on data mining

The technique of data mining was provided to predict gas disaster in view of the characteristics of coal mine gas disaster and feature knowledge based on gas disaster. The rough set theory was used to establish data mining model of gas disaster prediction, and rough set attributes relations was discussed in prediction model of gas disaster to supplement the shortages of rough intensive reduction method by using information en- tropy criteria.The effectiveness and practicality of data mining technology in the prediction of gas disaster is confirmed through practical application.

Longwall face roof disaster prediction algorithm based on data model driving

Hydraulic support is the primary equipment used for surrounding rock control at fully mechanized mining faces.The load,location,and attitude of the hydraulic support are important sets of basis data to predict roof disasters.This paper summarized and analyzed the status of coal mine safety accidents and the primary influencing factors of roof disasters.This work also proposed monitoring characteristic parameters of roof disasters based on support posture-load changes,such as the support location and support posture.The data feature decomposition method of the additive model was used with the monitoring load data of the hydraulic support in the Yanghuopan coal mine to effectively extract the trend,cycle period,and residuals,which provided the period weighting characteristics of the longwall face.The autoregressive,long-short term memory,and support vector regression algorithms were used to model and analyze the monitoring data to realize single-point predictions.The seasonal autoregressive integrated moving average(SARIMA)and autoregressive integrated moving average(ARIMA)models were adopted to predict the support cycle load of the hydraulic support.The SARIMA model is shown to be better than the ARIMA model for load predictions in one support cycle,but the prediction effect of these two algorithms over a fracture cycle is poor.Therefore,we proposed a hydraulic support load prediction method based on multiple data cutting and a hydraulic support load template library.The constructed technical framework of the roof disaster intelligent prediction platform is based on this method to perform predictions and early warnings of roof disasters based on the load and posture monitoring information from the hydraulic support.

The Study of Medium- and Short-term Prediction for Artux Earthquake (M_S=6.9) and Usunan Earthquake (M_S=5.8)

In this paper, the process of medium- and short-term prediction (submitted in special cards) of the Artux earthquake (MS=6.9) and the Usurian earthquake (MS=5.8) in Xinjiang area, is introduced. The imminent seismic risk regions are judged based on long- and medium-term seismic risk regions and annual seismic risk regions determined by national seismologic analysis, combined with large seismic situation analysis. We trace and analyze the seismic situation in large areas, and judge principal risk regions or belts of seismic activity in a year, by integrating the large area’s seismicity with geodetic deformation evolutional characteristics. As much as possible using information, we study synthetically observational information for long-medium- and short-term (time domain) and large-medium -small dimensions (space domain), and approach the forecast region of forthcoming earthquakes from the large to small magnitude. A better effect has been obtained. Some questions about earthquake prediction are discussed.

Adaptive Momentum-Backpropagation Algorithm for Flood Prediction and Management in the Internet of Things

Flooding is a hazardous natural calamity that causes significant damage to lives and infrastructure in the real world.Therefore,timely and accurate decision-making is essential for mitigating flood-related damages.The traditional flood prediction techniques often encounter challenges in accuracy,timeliness,complexity in handling dynamic flood patterns and leading to substandard flood management strategies.To address these challenges,there is a need for advanced machine learning models that can effectively analyze Internet of Things(IoT)-generated flood data and provide timely and accurate flood predictions.This paper proposes a novel approach-the Adaptive Momentum and Backpropagation(AM-BP)algorithm-for flood prediction and management in IoT networks.The AM-BP model combines the advantages of an adaptive momentum technique with the backpropagation algorithm to enhance flood prediction accuracy and efficiency.Real-world flood data is used for validation,demonstrating the superior performance of the AM-BP algorithm compared to traditional methods.In addition,multilayer high-end computing architecture(MLCA)is used to handle weather data such as rainfall,river water level,soil moisture,etc.The AM-BP’s real-time abilities enable proactive flood management,facilitating timely responses and effective disaster mitigation.Furthermore,the AM-BP algorithm can analyze large and complex datasets,integrating environmental and climatic factors for more accurate flood prediction.The evaluation result shows that the AM-BP algorithm outperforms traditional approaches with an accuracy rate of 96%,96.4%F1-Measure,97%Precision,and 95.9%Recall.The proposed AM-BP model presents a promising solution for flood prediction and management in IoT networks,contributing to more resilient and efficient flood control strategies,and ensuring the safety and well-being of communities at risk of flooding.

Seismic characteristics near the epicenter of the 1303 Hongtong M=8 earthquake, Shanxi Province and its implication

In this paper, we calculated the seismic pattern of instrumental recorded small and moderate earthquakes near the epicenter of the 1303 Hongtong M=8 earthquake, Shanxi Province. According to the spatial distribution of small and moderate earthquakes, 6 seismic dense zones are delineated. Temporal distribution of ML2 earthquakes since 1970 in each seismic dense zone has been analyzed. Based on temporal distribution characteristics and historical earthquake activity, three types of seismicities are proposed. The relationship between seismic types and crustal medium is analyzed. The mechanism of three types is discussed. Finity of strong earthquake recurrence is pro-posed. Seismic hazard in mid-long term and diversity of earthquake disaster in Shanxi seismic belt are discussed.

Seismic characteristics near the epicenter of the 1303 Hongtong M=8 earthquake, Shanxi Province and its implication

In this paper, we calculated the seismic pattern of instrumental recorded small and moderate earthquakes near the epicenter of the 1303 Hongtong M=8 earthquake, Shanxi Province. According to the spatial distribution of small and moderate earthquakes, 6 seismic dense zones are delineated. Temporal distribution of ML2 earthquakes since 1970 in each seismic dense zone has been analyzed. Based on temporal distribution characteristics and historical earthquake activity, three types of seismicities are proposed. The relationship between seismic types and crustal medium is analyzed. The mechanism of three types is discussed. Finity of strong earthquake recurrence is pro-posed. Seismic hazard in mid-long term and diversity of earthquake disaster in Shanxi seismic belt are discussed.

An efficient framework for ensemble of natural disaster simulations as a service

Calculations of risk from natural disasters may require ensembles of hundreds of thousands of simulations to accurately quantify the complex relationships between the outcome of a disaster and its contributing factors.Such large ensembles cannot typically be run on a single computer due to the limited computational resources available.Cloud Computing offers an attractive alternative,with an almost unlimited capacity for computation,storage,and network bandwidth.However,there are no clear mechanisms that define how to implement these complex natural disaster ensembles on the Cloud with minimal time and resources.As such,this paper proposes a system framework with two phases of cost optimization to run the ensembles as a service over Cloud.The cost is minimized through efficient distribution of the simulations among the cost-efficient instances and intelligent choice of the instances based on pricing models.We validate the proposed framework using real Cloud environment with real wildfire ensemble scenarios under different user requirements.The experimental results give an edge to the proposed system over the bag-of-task type execution on the Clouds with less cost and better flexibility.

Support principles of NPR bolt/cable and control techniques of large-deformation disasters

Deep mining has been paid much more attention because of the depletion of shallow mining resources.Traditional bolts could be invalid to accommodate large displacement and deformation in geomaterials.Consequently, alternative support and reinforcement bolts need to be studied and their constitutive models also need to be developed to help understanding for the complex stress-strain responses of rock masses under loadings. The effect of Negative Poisson's Ratio(NPR) that is attributed to the swelling phenomenon along the lateral direction may appear in metal materials under tensional loadings. Thence NPR materials often have an advantage over NPR ones in mechanical behavior such as impact resistance, antishearing, and energy absorbed. From the characteristics of NPR materials, a series of bolt and cable supports with the effect of NPR and constant-resistance have been recently developed. We here firstly introduce the structural features of NPR support. Then the constitutive model of NPR support is presented and its corresponding equation of energy equilibrium. Its basic principle interacted on rock masses is further discussed. Finally, NPR cables are employed to support the slope of an open-pit mine. The applications show that NPR cables can ease failure within the slope and play an important role in predicting and providing early warning of slope failure, together with a monitoring system of slope stability.

Study of Simulation of Earth-Fissures Development and Prediction Based on GIS

Earth-Fissure in Linfen city is dominated by many factors. In this paper, every factor is analyzed in detail and each coverage of them is established. After that, reciprocal relationship between them is determined by using AHP method. With the strong spatial-operation fuuction or GIS, the advanced GIS models of earth-fissure simulation and multi-source forecast are built. On the basis of this, asatisfied prediction has provided extremely important science bases for the city future plans.

Method of expected earthquake losses estimation based on the frequency of seismic site intensity

During a given period,a site will suffer the attack from earthquake several times.But this effect is neglected in the currently used model of loss estimation from earthquake When calculating the occurrence rate of the affected intensity,the difference of the exceeding probability is used.Such treatment will underestimate the earthquake loss,especially when the exposure period is long.To overcome the shortcomings of the model currently used,a new frame of earthquake loss estimation is provided from the logic sense:during the given period,the expected earthquake loss responding to the specific affected intensity is equal to the expected number of the intensity multiplying the expected loss under the condition of such an affected intensity,and the total expected loss is equal to the effects of all the possible intensities.On the basis of the seismicity model used in compiling the 'Chinese Seismic Intensity Zoning Map(1990) ',a new formula of expected loss evaluation and the variance of the evaluation are provided.It is inferred from the example and the comparison with the currently used method that the new method is applicable and necessary.These results will lay a scientific foundation for the estimation of earthquake loss,insurance and disaster prevention.

Research on Prediction Methods of Prevalence Perception under Information Exposure

With the rapid development of information technology,the explosive growth of data information has become a common challenge and opportunity.Social network services represented by WeChat,Weibo and Twitter,drive a large amount of information due to the continuous spread,evolution and emergence of users through these platforms.The dynamic modeling,analysis,and network information prediction,has very important research and application value,and plays a very important role in the discovery of popular events,personalized information recommendation,and early warning of bad information.For these reasons,this paper proposes an adaptive prediction algorithm for network information transmission.A popularity prediction algorithm is designed to control the transmission trend based on the gray Verhulst model to analyze the law of development and capture popular trends.Experimental simulations show that the proposed perceptual prediction model in this paper has a better fitting effect than the existing models.

A Preliminary Study on the Probabilistic Estimation of Deaths from Future Earthquakes in North China

During the period from 1800 to 1989,the degree of fatalities(?from earthquakes in North China(Lat.34.0°-42.0°N,Long.107.5°-125.0°E)varied exponentially with the frequency of earthquake events(N),namely:N=37.71 exp(-0.72?(E-logD,D:deaths).For the periods from 1988 to 1998 and from 1999 to 2009,the probabilities for earthquakes to cause one thousand or more deaths in North China are estimated to be 0.37 and 0.50,respectively,by using the Gumbel’s extreme value theory.

New Seismic Zoning Map of Chin a and Its Application in Earthquake Disaster Mitigation

The New Seismic Zoning Map of China was prepared from 1987 to 1990 and officially promulgated in 1991.In comparison with the previous two seismic zoning maps prepared in 1957 and 1977,some new methods were applied to upgrade the method currently used for seismic hazard analysis.First,a probabilistic method was used instead of the deterministic analysis was used for previous mapping.Second,by taking advantages of the long history of historical seismic data in China,the nonhomogeneity of seismicity both in space and in time has been fully considered and hence the over-and/or underestimation of seismic hazard could be avoided.Third,the results of middle-and long-term earthquake prediction based on tectonic evidence have been incorporated into seismic hazard analysis.In addition,the attenuation laws for both intensity and peak acceleration of strong motion as the mapping parameters are also presented.Finally,an evaluation of the New Seismic Map and its effect on engineering application,such as aseismic

TrueType Font Symbol Library for Cartography of Emergency Situations

This contribution deals with the process of creation of symbol libraries for emergency situations cartography. The libraries were created as a TrueType font files. Two symbol libraries were created. The first one is a set of symbols for description of map orientation （compass roses and north arrows） with correct national （in this case Czech） description. The second one is a set of symbols for description of CBRN （chemical, biological, radiological, and nuclear） threats and another CBRN issues. The TrueType font files are used as symbol libraries in various ESRI products. The font libraries created in this form are easily transferable between various operating systems and GIS programs and also can be easily converted into various different vector graphics formats. The whole process of font creation has taken place under Linux environment. Fortunately main programs used in this process are multiplatform and could be used under Linux, MS Windows and other various computer operating was part of Ubuntu repository and it was obtained free of charge. systems. All software used during the process of font creation

A Review of the Study on the Uncertainty of Earthquake Loss Estimation

In this paper,the types of research methods that contain uncertainty are first introduced,and then the description is concentrated on the progress of study on different types of uncertainties in seismic disaster and loss estimation. The main methods applied to uncertainty study are reviewed. Preliminary discussion of the problems currently existing in estimation is also made.