Preliminary inquiry into the causes of anomaly increase of air temperature by an impending earthquake

In this paper, the causes of the occurrence of the temperature increase by an impending earthquake of low altitude atmosphere and on the ground surface have been preliminarily expounded through several simulative controlexperiments. Air polarized by the anomalous atmospheric static electric field is regarded as the primary factor tocreate air temperature increase to a large degree and over a large area in the sunlight. In addition, another causeis considered as the temperature increase effect of “polluted” air.

Short-term and imminent geomagnetic anomalies of the Wenchuan M_S8.0 earthquake and exploration on earthquake forecast

The diurnal variation of the geomagnetic vertical component is exhibited mainly by changes of phase and amplitude before strong earthquakes. Based on data recorded by the network of geomagnetic observatories in China for many years, the anomalous features of the appearance time of the minima of diurnal variations （i.e, low-point time） of the geo- magnetic vertical components and the variation of their spatial distribution （i.e, phenomena of low-point displacement） have been studied before the Wenchuan Ms8.0 earthquake. The strong aftershocks after two months＇ quiescence of M6 aftershocks of the Ms8.0 event were forecasted based on these studies. There are good correlativities between these geomagnetic anoma- lies and occurrences of earthquakes. It has been found that most earthquakes occur near the boundary line of sudden changes of the low-point time and generally within four days before or after the 27th or 41st day counting from the day of the appearance of the anomaly. In addition, the imminent anomalies in diurnal-variation amplitudes near the epicentral areas have also been studied before the Wenchuan earthquake.

POSSIBLE CONTRIBUTION OF A TROPICAL CYCLONE TO SHORT-TERM CLIMATE ANOMALIES IN EAST ASIA VIA SNOW COVER ON THE TIBETAN PLATEAU

Snow cover on the Tibetan Plateau(TP) has been shown to be essential for the East Asian summer monsoon.In this paper, we demonstrate that tropical cyclone(TC) 04B(1999) in the northern Indian Ocean, which made landfall during the autumn of 1999, may have contributed to climate anomalies over East Asia during the following spring and summer by increasing snow cover on the TP. Observations indicate that snow cover on the TP increased markedly after TC 04B(1999) made landfall in October of 1999. Sensitivity experiments, in which the TC was removed from a numerical model simulation of the initial field, verified that TC 04B(1999) affected the distribution as well as increased the amount of snow on the TP. In addition, the short-term numerical modeling of the climate over the region showed that the positive snow cover anomaly induced negative surface temperature, negative sensible heat flux, positive latent heat flux, and positive soil temperature anomalies over the central and southern TP during the following spring and summer. These climate anomalies over the TP were associated with positive(negative) summer precipitation anomalies over the Yangtze River valley(along the southeastern coast of China).

Device Anomaly Detection Algorithm Based on Enhanced Long Short-Term Memory Network

The problems in equipment fault detection include data dimension explosion,computational complexity,low detection accuracy,etc.To solve these problems,a device anomaly detection algorithm based on enhanced long short-term memory(LSTM)is proposed.The algorithm first reduces the dimensionality of the device sensor data by principal component analysis(PCA),extracts the strongly correlated variable data among the multidimensional sensor data with the lowest possible information loss,and then uses the enhanced stacked LSTM to predict the extracted temporal data,thus improving the accuracy of anomaly detection.To improve the efficiency of the anomaly detection,a genetic algorithm(GA)is used to adjust the magnitude of the enhancements made by the LSTM model.The validation of the actual data from the pumps shows that the algorithm has significantly improved the recall rate and the detection speed of device anomaly detection,with the recall rate of 97.07%,which indicates that the algorithm is effective and efficient for device anomaly detection in the actual production environment.

ADS-B Anomaly Data Detection Model Based on Deep Learning and Difference of Gaussian Approach

Due to the influence of terrain structure,meteorological conditions and various factors,there are anomalous data in automatic dependent surveillance-broadcast(ADS-B)message.The ADS-B equipment can be used for positioning of general aviation aircraft.Aim to acquire the accurate position information of aircraft and detect anomaly data,the ADS-B anomaly data detection model based on deep learning and difference of Gaussian(DoG)approach is proposed.First,according to the characteristic of ADS-B data,the ADS-B position data are transformed into the coordinate system.And the origin of the coordinate system is set up as the take-off point.Then,based on the kinematic principle,the ADS-B anomaly data can be removed.Moreover,the details of the ADS-B position data can be got by the DoG approach.Finally,the long short-term memory(LSTM)neural network is used to optimize the recurrent neural network(RNN)with severe gradient reduction for processing ADS-B data.The position data of ADS-B are reconstructed by the sequence to sequence(seq2seq)model which is composed of LSTM neural network,and the reconstruction error is used to detect the anomalous data.Based on the real flight data of general aviation aircraft,the simulation results show that the anomaly data can be detected effectively by the proposed method of reconstructing ADS-B data with the seq2seq model,and its running time is reduced.Compared with the RNN,the accuracy of anomaly detection is increased by 2.7%.The performance of the proposed model is better than that of the traditional anomaly detection models.

Anomalies of Precursory Group and Grouped Strong Earthquakes in the Sichuan-Yunnan Region

Three methods of extracting the information of anomalies of a precursory group are put forward, i.e., the mathematical analyses of the synthetic information of earthquake precursors (S), the inhomogeneous degree of precursory groups (ID) and the values of short-term and impending anomaly in near-source area (NS). Using these methods, we calculate the observational data of deformation, underground fluid and hydrochemical constituents obtained from different seismic stations in the Sichuan-Yunnan region and conclude that the synthetic precursory anomalies of a single strong earthquake with M S6.0 differ greatly from those of the grouped strong earthquakes, for the anomalous information of precursory groups are more abundant. The three methods of extracting the synthetic precursory anomaly and the related numerical results can be applied into the practice of prediction to the grouped strong earthquakes in the Sichuan-Yunnan region. Inhomogeneous degree (ID) of synthetic precursory anomaly can be identified automatically because it takes the threshold of distributive characteristics of the anomalies of precursory group as its criterion for anomaly.

An Aircraft Trajectory Anomaly Detection Method Based on Deep Mixture Density Network

The timely and accurately detection of abnormal aircraft trajectory is critical to improving flight safety.However,the existing anomaly detection methods based on machine learning cannot well characterize the features of aircraft trajectories.Low anomaly detection accuracy still exists due to the high-dimensionality,heterogeneity and temporality of flight trajectory data.To this end,this paper proposes an abnormal trajectory detection method based on the deep mixture density network(DMDN)to detect flights with unusual data patterns and evaluate flight trajectory safety.The technique consists of two components:Utilization of the deep long short-term memory(LSTM)network to encode features of flight trajectories effectively,and parameterization of the statistical properties of flight trajectory using the Gaussian mixture model(GMM).Experiment results on Guangzhou Baiyun International Airport terminal airspace show that the proposed method can effectively capture the statistical patterns of aircraft trajectories.The model can detect abnormal flights with elevated risks and its performance is superior to two mainstream methods.The proposed model can be used as an assistant decision-making tool for air traffic controllers.

An Efficient Correlation-Aware Anomaly Detection Framework in Cellular Network

Nowadays,the fifth-generation(5G)mobile communication system has obtained prosperous development and deployment,reshaping our daily lives.However,anomalies of cell outages and congestion in 5G critically influence the quality of experience and significantly increase operational expenditures.Although several big data and artificial intelligencebased anomaly detection methods have been proposed for wireless cellular systems,they change distributions of the data and ignore the relevance among user activities,causing anomaly detection ineffective for some cells.In this paper,we propose a highly effective and accurate anomaly detection framework by utilizing generative adversarial networks(GAN)and long short-term memory(LSTM)neural networks.The framework expands the original dataset while simultaneously keeping the distribution of data unchanged,and explores the relevance among user activities to further improve the system performance.The results demonstrate that our framework can achieve 97.16%accuracy and 2.30%false positive rate by utilizing the correlation of user activities and data expansion.

Earthquake-related anomalies recorded by two borehole bulk-strain meters

This paper gives a report on borehole bulk-strain data recorded at the seismostation Nanton$ in Jiangsu Province from January 1 , 2003 to December 31 , 2008. While the data at Nantong showed much noise possibly due to site instability and no earthquake-related changes, the data at Liuhe showed anomalous changes that began one to several weeks before three earthquakes of magnitude 4.0 to 6.0 at eplcentral distances up to 400 kin.

Characteristics of a Short-Term and Imminent Earthquake Precursor Field in the Northern Part of North China and Numerical Simulation of Source Process

According to studies of more than 20 earthquakes with MS≥5.0 in North China, seven features of the short-term and imminent earthquake precursors have been summarized in this paper. At the same time, taking the short-term and imminent earthquake stage as the physical process of a source’s medium softening and fault creep, we calculated temporal variation of mean stress, maximum shear stress, body strain, and pore pressure in some certain points (supposed stations) in the source area and its adjacent area by using an anisotropic and nonlinear source model and a finite element method. According to an analysis of these theoretical curves, we conclude that the short-term and imminent earthquake precursors have such characteristics as complex shapes, exponential growth of the precursor number with tune, and precursors’ migration from the outside area to the source area, which to a certain extent reveal the cause of the characteristics of the short-term and imminent earthquake precursor field.

The Anomaly Field of Subsurface Fluids and Its Formation and Evolution Mechanism Before Three Strong Earthquakes in the Northern North China Area

The data of pre-seismic subsurface fluid anomalies of such earthquakes as Datong-YanggaoM_s6.1 event on Oct.19,1989,western Baotou M_s6.4 event on May 3,1996 and Zhangbei-Shangyi M_s6.2 event on Jan.10,1998 are systematically collected and arranged.Then thefeatures of patterns,spatial distribution,time variation and time-spatial evolution of theseanomalies are compared and comprehensively analyzed.Then the formation and evolutionmechanism of medium-and short-term anomaly field of subsurface fluids in the northernNorth China area is proposed.The results show that the medium-term anomaly field is causedby regional tectonic activities,which further strengthen the local tectonic activities andpromote the formation and evolution of the seismic source body.The enhancement of loealtectonic activities causes the formation of anomaly field of short-term subsurface fluids,andthe evolution of source body engenders the source-precursor anomalies of subsurface fluids inthe epicenters at imminent stage.

Study on the Method of Short-Term Synthetic Earthquake Prediction in the North China Region

Based on the extraction and calculation of the short-term seismic precursory information magnitude from the 114 major precursory observations in the North China region, and together with consideration of factors such as geological structure, seismicity, crustal thickness, and in particular, the current geodynamics of the region, the authors studied the time-space evolution characteristics of the short-term earthquake precursory information magnitude and its relationship with earthquakes and proposed the index and method for the short-term synthetic prediction of earthquakes with M S≥5.0 in the North China region. The inspection through R-value shows that the method is effective to a certain extent for earthquake prediction.

2019年老挝M_(S)6.0地震临震射出长波辐射变化研究

计算2019年11月21日老挝M_(S)6.0地震前后(2019年10月16日—12月15日)震中位置(19.50°N,101.35°E)的潮汐变化。发震时刻引潮力处于高相位点附近,显示引潮力的诱震作用属于典型正断层走滑作用类型。以此引潮力变化周期的各低相位点时间(10月28日、11月13日、11月27日)分别为背景,计算研究区(13°N~23°N,99°E~109°E)范围内,NOAA射出长波辐射数据产品(OLR)各引潮力周期时段长波辐射异常分布及变化。结果显示,无震时的引潮力变化的A、C周期,震中附近无OLR变化;发震的引潮力变化B周期,该地区震前OLR仅震中发生了显著而连续异常变化过程:在空间上OLR异常分布在老挝北部NE-SW走向的奠边府断裂带上,且与震中位置高度吻合,经历了起始增强—异常增强—峰值—减弱—发震—平静的演化过程,与岩石应力加载破裂演化即初始微动破裂—扩张破裂—应力闭锁—地震暴发—平静各阶段力学过程相同;表明天体引潮力对达到临界状态的活跃断层有触发作用,OLR异常则是地震构造应力应变活动过程的辐射表征。

Short-Impending Earthquake Anomaly Index Extraction of GNSS Continuous Observation Data in Yunnan,Southwestern China

This paper presents a comprehensive area expansion prediction index method to apply GNSS for short-impending prediction of earthquakes. Based on continuous GNSS observation data from Yunnan Province, a displacement field was detected after data cycle-slip repair using precision data processing software and geophysical field effect model correction. The Yunnan area was divided into 56 grid cells for displacement field interpolation to obtain a more uniform displacement field and a strain field variation time series. The pre-earthquake response of each grid-cell expansion time series was evaluated and synthesized to extract a short-impending earthquake anomaly identification index. The results show that this index indicated occurrence times and hypocenter for earthquakes of magnitude M≥5. Fourteen earthquakes were predicted accurately, and there were five false reports. This index can therefore be used for the short-impending prediction of earthquakes.

IMPENDING-EARTHQUAKE SATELLITE THERMAL INFRARED AND GROUND TEMPERATUREINCREASE ANOMALIES

This note mainly discusses the relation of the impending-earthquake satellite thermal infrared anomaly with the ground temperature-increase anomaly, namely, expounds the problem if the satellite thermal infrared anomaly is the reflection of the surficial temperatureincrease anomaly caused by seismic activities on the basis of previous works about the rela-

THERMAL INFRARED ANOMALY PRECURSOR OF IMPENDING EARTHQUAKES

People have already recognized the temperature-increase anomaly before earthquakes and studies have been made on this phenomenon. With the method of fixed-point network observation, only the timing temperature data limited to some sites can be obtained instead of dynamic evolution data of the temperature in a large area within the seismogenic range.

地电前兆中期向短临过渡的综合判据

通过分析唐山、大同、海城等强震的地电前兆,提出判断地震前兆的主要标准:直接或间接反映应变积累的信息可定为地震前兆。论证唐山地震前2—3年区域电阻率下降是该区震前应变积累的反映,即唐山震前地电区域下降是地震的中期前兆。地电中期前兆具有震中区幅度较大,外围较小,前兆从震中向外围传播等规律。地电前兆中期向短临过渡的判据有:加速、回返、各向异性及触发等。

张北6.2级地震前的卫星热红外异常

利用张北地震前 1个月华北北部 (37～ 42°N,1 1 3～ 1 1 9°E)的气象卫星 NOAA/ AVHRR热红外遥感资料 ,提取震前热红外温度异常 ,研究其时空变化的过程和特征 ,并对热红外温度异常与地震的关系进行初步的探讨。结果表明 ,在张北地震前 1 3天沿张家口 -渤海断裂带确有显著的热红外温度异常出现。异常区域呈条带状 ,且与 NW向地质构造一致 ;温度异常的动态变化可大致分为初始、平缓发展和临震加速 3个阶段。

地震前异常的阶段性及其空间分布特征

将岩石变形曲线到达强度点以前比拟为地震前异常的中长期阶段，强度点至失稳点之间定义为短临阶段。在中长期阶段异常是由驱动力的增强或区域应力场的调整引起，前者引起的应力扰动场与原来的方向一致，强烈扰动区与原来的应力集中区一致，后者引起的应力扰动场应力方向可以发生变化，应力扰动对平均应力影响较大，强烈扰动区位于断层错列部位。二者的强烈扰动场均与未来的震源区无必然联系。在短临阶段异常是由局部断层扩展或弱化引起，与之相伴的是平均应力扰动场的四象限分布和最大剪应力扰动场的八瓣式分布。

云南地区地震宏观异常特征研究

经历史震例及近几年地震震前短临跟踪预报实践 ,对宏观异常进行深入剖析 ,认为 :宏观异常内容和数量多少与震级有关 ;宏观异常不只是短临和临震异常信息 ,也有不少是中短期、短期异常信息 ;宏观异常分布在震中及附近地区 ;最早出现的宏观异常地点对未来地震震中有一定指示意义。