地震微观前兆预报网络系统设计研究(1)——地震模型
|
摘要
地震预报是一个极大挑战性的世界难题。为了准确地预报地震必须跟踪地震的整个孕育过程。例如利用基岩传感器网络收集地震微观前兆的各种信息,包括基岩应力、应变和破裂强度的变化、基岩振动状态的变化、引力波和冲击波强度的变化、地热温度分布的变化、电磁场的变化等。经过传感器数据融合和信号处理提取有用信息,然后由数据处理中心做出决策判断。提出了地震微观前兆预报网络系统设计的一整套详细方案,包括地震模型、基岩传感器网络和数据融合以及信号处理技术和网络系统设计。本文介绍地震模型的建立
Earthquake prediction is a very difficult problem all over the world. It is necessary to track the whole forming process for correct earthquake forecast . For example, bedrock sensor network is used to collect the information of earthquake precursors, including changes of bedrock stress, strain and bursting strength, bedrock vibration status, gravitational wave strength, shock wave strength, terrestrial heat temperature distribution and electromagnetic field strength, etc. After data fusion and signal processing , the useful information is pick-up and is sent to data process center for giving correct judgment. A study of design of the network system for earthquake micro precursor forecast is presented in detail in this serial papers, which include model of earthquake, signal acquisition methods, bedrock sensor network and data fusion, signal processing, design of network system. The emphases is put on how to build the model of earthquake in this paper. The correlation theories and statistical method are introduced too.
Earthquake prediction is a very difficult problem all over the world. It is necessary to track the whole forming process for correct earthquake forecast . For example, bedrock sensor network is used to collect the information of earthquake precursors, including changes of bedrock stress, strain and bursting strength, bedrock vibration status, gravitational wave strength, shock wave strength, terrestrial heat temperature distribution and electromagnetic field strength, etc. After data fusion and signal processing , the useful information is pick-up and is sent to data process center for giving correct judgment. A study of design of the network system for earthquake micro precursor forecast is presented in detail in this serial papers, which include model of earthquake, signal acquisition methods, bedrock sensor network and data fusion, signal processing, design of network system. The emphases is put on how to build the model of earthquake in this paper. The correlation theories and statistical method are introduced too.
引文
[1]Vere-Jones D,Earthquake prediction–A statistician’s views[J]J.Phys.Earth,1978;26:129-146.
[2]Vere-Jones D and Ozaki T,some examples of statistical inference applied to earthquake data[J].Ann.Inst.Stat.Math,1982;34:189-207.
[3]Rubin I,Regular point processes and their detection[J].IEEE Trans.Inform.Theory,1972;IT18:547-557.
[4]Isham V and Westcott M,A self-correcting point process[J].Stoch,Proc,Appl,1979;8:335-347.
[5]Basawa IV and Scott DJ,Asymptotic Inference for Non-ergodic Models[C].1983,Berlin.
[6]Kutoyants YnA,Local asymptotic normality for processes of Poisson type.Izvest.Akad Arm.Nauk.Ser.Matermatika,1979;14(1):3-20.
[7]Billingsley P,Convergence of probability measures[M].New York:Wiley.
[8]Daley DJ and Vere-Jones D,A summary of the theory of point process in stochastic point processes[M].PAW Lewis:Wiley,1979.
[9]Lipster RS and Shiryaes AN,Statics of Random processes[M].Berlin:Springer,1978
[10]Cinlar E,Introduction to stochastic processes[M].Englewood Cliffs:Prentice-Hall,1975.
[11]Arjas E and Speed TP,Symmetric Wiener-Hopf factorization in Markov additive processes[J].Z.Wahrsd.Verw.Geb,1973;26:105-118.
[12]Kaspi H,On the Wiener-Hopf factorization for generators of Markov additive processes[J].Z.Wakrsch,Verw,Geb,1982;59:179-186.
[13]Gantmacher FR,Applications of the theory of matrices[M],New York:Interscience,1959.
[14]Billman B,Antle CE,and Ban LJ,Statistical inferences from censored Weibull samples[J].Technometrics,1972;14:831-840.
[15]Kao JHK,Computer methods for estimating Weibull parameters in reliability studies[J].IRE Transactions reliability and quality control[J].PGPQC,1958;13:15-22.
[16]Kaebfleisch JD and Prentice RL,Statistical analysis of failure time data[M].New York:John wiley,1980.
[17]Nelson WB,Theory and applications of hazard plotting for censored failure data[J]Techno meters,1972;14:945-965.
[18]Breslow NE and Crowley J,A large sample study of the life table and product eimit estimates under random censorship[J].Annals of statistics,1974;435-453.
[19]Lawless JF and Singhal K,Analysis of data from life test experiments under an exponential made[J].Naval Research logistics Quarterly,1980;27:323-334.
[20]Nelson WB,Applied life data analysis[M].,New York:John Wiley,1982.
[21]Altschuler A,Theory for the measurement of competing risks in animal experiments[J].Mathematical Biosciences,1970;6:1-11.
[22]Cox DR and Miller HD,The theory of stochastic processes[M].London:Metheun,1965
[2]Vere-Jones D and Ozaki T,some examples of statistical inference applied to earthquake data[J].Ann.Inst.Stat.Math,1982;34:189-207.
[3]Rubin I,Regular point processes and their detection[J].IEEE Trans.Inform.Theory,1972;IT18:547-557.
[4]Isham V and Westcott M,A self-correcting point process[J].Stoch,Proc,Appl,1979;8:335-347.
[5]Basawa IV and Scott DJ,Asymptotic Inference for Non-ergodic Models[C].1983,Berlin.
[6]Kutoyants YnA,Local asymptotic normality for processes of Poisson type.Izvest.Akad Arm.Nauk.Ser.Matermatika,1979;14(1):3-20.
[7]Billingsley P,Convergence of probability measures[M].New York:Wiley.
[8]Daley DJ and Vere-Jones D,A summary of the theory of point process in stochastic point processes[M].PAW Lewis:Wiley,1979.
[9]Lipster RS and Shiryaes AN,Statics of Random processes[M].Berlin:Springer,1978
[10]Cinlar E,Introduction to stochastic processes[M].Englewood Cliffs:Prentice-Hall,1975.
[11]Arjas E and Speed TP,Symmetric Wiener-Hopf factorization in Markov additive processes[J].Z.Wahrsd.Verw.Geb,1973;26:105-118.
[12]Kaspi H,On the Wiener-Hopf factorization for generators of Markov additive processes[J].Z.Wakrsch,Verw,Geb,1982;59:179-186.
[13]Gantmacher FR,Applications of the theory of matrices[M],New York:Interscience,1959.
[14]Billman B,Antle CE,and Ban LJ,Statistical inferences from censored Weibull samples[J].Technometrics,1972;14:831-840.
[15]Kao JHK,Computer methods for estimating Weibull parameters in reliability studies[J].IRE Transactions reliability and quality control[J].PGPQC,1958;13:15-22.
[16]Kaebfleisch JD and Prentice RL,Statistical analysis of failure time data[M].New York:John wiley,1980.
[17]Nelson WB,Theory and applications of hazard plotting for censored failure data[J]Techno meters,1972;14:945-965.
[18]Breslow NE and Crowley J,A large sample study of the life table and product eimit estimates under random censorship[J].Annals of statistics,1974;435-453.
[19]Lawless JF and Singhal K,Analysis of data from life test experiments under an exponential made[J].Naval Research logistics Quarterly,1980;27:323-334.
[20]Nelson WB,Applied life data analysis[M].,New York:John Wiley,1982.
[21]Altschuler A,Theory for the measurement of competing risks in animal experiments[J].Mathematical Biosciences,1970;6:1-11.
[22]Cox DR and Miller HD,The theory of stochastic processes[M].London:Metheun,1965
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心