There are many parameters influencing mining induced surface subsidence. These parameters usually interact with one another and some of them have the characteristic of fuzziness. Current approaches to predicting the s...There are many parameters influencing mining induced surface subsidence. These parameters usually interact with one another and some of them have the characteristic of fuzziness. Current approaches to predicting the subsidence cannot take into account of such interactions and fuzziness. In order to overcome this disadvantage, many mining induced surface subsidence cases were accumulated, and an artificial neuro fuzzy inference system(ANFIS) was used to set up 4 ANFIS models to predict the rise angle, dip angle, center angle and the maximum subsidence, respectively. The fitting and generalization prediction capabilities of the models were tested. The test results show that the models have very good fitting and generalization prediction capabilities and the approach can be applied to predict the mining induced surface subsidence.展开更多
2001年1月在布季发生的矩震级7．7的地震是印度有历史记载的最具破坏性的地震之一。尽管其断层面没有使地表破裂，但此次地震在约15000km^2范围内造成了地面破坏，包括形成喷沙坑、沙层裂缝和地下沉积层出现液化迹象(Tuttl et al，2002...2001年1月在布季发生的矩震级7．7的地震是印度有历史记载的最具破坏性的地震之一。尽管其断层面没有使地表破裂，但此次地震在约15000km^2范围内造成了地面破坏，包括形成喷沙坑、沙层裂缝和地下沉积层出现液化迹象(Tuttl et al，2002)。在此我们对该地震期间形成的两个较大的干爆发坑进行了勘察，并对从坑中喷出的碎屑物的轨迹进行了分析，估算了当时的地下压力。我们认为，这些干坑可能是由于砂土液化的延迟效应导致地面爆发式变形而形成的。展开更多
基金Project(50274043) supported by the National Natural Science Foundation of China project (01JJY1004) supported bythe Natural Science Foundation of Hunan Province project (01A015) supported by the Natural Science Foundation of Hunan ProvincialEducation Committee
文摘There are many parameters influencing mining induced surface subsidence. These parameters usually interact with one another and some of them have the characteristic of fuzziness. Current approaches to predicting the subsidence cannot take into account of such interactions and fuzziness. In order to overcome this disadvantage, many mining induced surface subsidence cases were accumulated, and an artificial neuro fuzzy inference system(ANFIS) was used to set up 4 ANFIS models to predict the rise angle, dip angle, center angle and the maximum subsidence, respectively. The fitting and generalization prediction capabilities of the models were tested. The test results show that the models have very good fitting and generalization prediction capabilities and the approach can be applied to predict the mining induced surface subsidence.
文摘2001年1月在布季发生的矩震级7．7的地震是印度有历史记载的最具破坏性的地震之一。尽管其断层面没有使地表破裂，但此次地震在约15000km^2范围内造成了地面破坏，包括形成喷沙坑、沙层裂缝和地下沉积层出现液化迹象(Tuttl et al，2002)。在此我们对该地震期间形成的两个较大的干爆发坑进行了勘察，并对从坑中喷出的碎屑物的轨迹进行了分析，估算了当时的地下压力。我们认为，这些干坑可能是由于砂土液化的延迟效应导致地面爆发式变形而形成的。
