Altun fault is regarded as a large\|scale sinistral strike\|slip fault, it is composed of several faults with the different character, and there is a special geological structure in the fault belt, and they constitute...Altun fault is regarded as a large\|scale sinistral strike\|slip fault, it is composed of several faults with the different character, and there is a special geological structure in the fault belt, and they constitute the northwestern margin fault belt of the Qinghai\|Tibetan plateau. In order to investigate the deep crust structure in the Altun region, layers which Tarim lithosphere subducted beneath the Qinghai\|Tibetan plateau, the forward structure of the subduction plate and the scale of the plate subduction, a deep seismic reflection profile was designed. Data collection work of the deep seismic reflection profile across Altun fault was completed during 24/8/1999 to 25/9/1999. The profile locates in Qiemo county, Xinjiang Uygur Autonomous Region, the southern end of the profile stretches into Altun Mountains, the northern end locates in the Tarim desert margin. The profile is nearly SN trending and crosses the main Altun fault. The profile totally is 145km long, time record is 30 seconds, the smallest explosive amount is 72～100kg, the biggest explosive amount reaches 200～300kg, the explosive distance is 800m, and detectors are laid at a 50m distance.展开更多
Fault diagnosis on large-scale and complex networks is a challenging task, as it requires efficient and accurate inference from huge data volumes. Active probing is a cost-efficient tool for fault diagnosis. However a...Fault diagnosis on large-scale and complex networks is a challenging task, as it requires efficient and accurate inference from huge data volumes. Active probing is a cost-efficient tool for fault diagnosis. However almost all existing probing-based techniques face the following problems: 1) performing inaccurately in noisy networks; 2) generating additional traffic to the network; 3) high cost computation. To address these problems, we propose an efficient probe selection algorithm for fault diagnosis based on Bayesian network. Moreover, two approaches which could significantly reduce the computational complexity of the probe selection process are provided. Finally, we implement the new proposed algorithm and a former representative probing-based algorithm (BPEA algorithm) on different settings of networks. The results show that, the new algorithm performs much faster than BPEA does without sacrificing the diagnostic quality, especially in large, noisy and multiple-fault networks.展开更多
文摘Altun fault is regarded as a large\|scale sinistral strike\|slip fault, it is composed of several faults with the different character, and there is a special geological structure in the fault belt, and they constitute the northwestern margin fault belt of the Qinghai\|Tibetan plateau. In order to investigate the deep crust structure in the Altun region, layers which Tarim lithosphere subducted beneath the Qinghai\|Tibetan plateau, the forward structure of the subduction plate and the scale of the plate subduction, a deep seismic reflection profile was designed. Data collection work of the deep seismic reflection profile across Altun fault was completed during 24/8/1999 to 25/9/1999. The profile locates in Qiemo county, Xinjiang Uygur Autonomous Region, the southern end of the profile stretches into Altun Mountains, the northern end locates in the Tarim desert margin. The profile is nearly SN trending and crosses the main Altun fault. The profile totally is 145km long, time record is 30 seconds, the smallest explosive amount is 72～100kg, the biggest explosive amount reaches 200～300kg, the explosive distance is 800m, and detectors are laid at a 50m distance.
基金supported by National Key Basic Research Program of China (973 program) under Grant No.2007CB310703Funds for Creative Research Groups of China under Grant No.60821001+1 种基金National Natural Science Foundation of China under Grant No. 60973108National S&T Major Project under Grant No.2011ZX03005-004-02
文摘Fault diagnosis on large-scale and complex networks is a challenging task, as it requires efficient and accurate inference from huge data volumes. Active probing is a cost-efficient tool for fault diagnosis. However almost all existing probing-based techniques face the following problems: 1) performing inaccurately in noisy networks; 2) generating additional traffic to the network; 3) high cost computation. To address these problems, we propose an efficient probe selection algorithm for fault diagnosis based on Bayesian network. Moreover, two approaches which could significantly reduce the computational complexity of the probe selection process are provided. Finally, we implement the new proposed algorithm and a former representative probing-based algorithm (BPEA algorithm) on different settings of networks. The results show that, the new algorithm performs much faster than BPEA does without sacrificing the diagnostic quality, especially in large, noisy and multiple-fault networks.
