The Kaapvaal Craton in South Africa hosts one of the largest gold placer deposits in the world. Mining in the Witwatersrand Basin here has been the source of about one third to one half of the gold ever produced in th...The Kaapvaal Craton in South Africa hosts one of the largest gold placer deposits in the world. Mining in the Witwatersrand Basin here has been the source of about one third to one half of the gold ever produced in the world. Gold was discovered in the Johannesburg area in 1886 and after 120 years of continuous operation, mining is currently approaching depths of 4 000 m. In spite of the challenges and risks that the industry has had to deal with including rock temperature, ventilation and water, one of the most feared hazards in the basin has been the threat from the ongoing occurrence of seismicity and rockbursts. The problem first manifested itself by way of the occurrence of tremors roughly twenty years after the commencement of mining operations. This paper traces the history of the approach to rockbursts and seismicity during the 120 year history of mining in the basin. It portrays a picture of the mining seismicity in terms of monitoring phases, mechanisms and mitigation strategies. The work of research organizations over the years is highlighted with a brief mention of current regulation strategies on the part of the mining inspectorate.展开更多
The determination of seismic attenuation （s） （dB/cm） is a challenging task in earthquake science. This article employs genetic programming （GP） and minimax probability machine regression （MPMR） for prediction ...The determination of seismic attenuation （s） （dB/cm） is a challenging task in earthquake science. This article employs genetic programming （GP） and minimax probability machine regression （MPMR） for prediction of s. GP is developed based on genetic algo- rithm. MPMR maximizes the minimum probability of future predictions being within some bound of the true regression function. Porosity （n） （%）, permeability （k） （millidarcy）, grain size （d） （μm）, and clay content （c） （%） have been considered as inputs of GP and MPMR. The output of GP and MPMR is s. The developed GP gives an equation for prediction of s. The results of GP and MPMR have been compared with the artificial neural net- work. This article gives robust models based on GP and MPMR for prediction of s.展开更多
This article adopts three soft computing techniques including support vector machine(SVM), least square support vector machine(LSSVM) and relevance vector machine(RVM) for prediction of status of epimetemorphic rock s...This article adopts three soft computing techniques including support vector machine(SVM), least square support vector machine(LSSVM) and relevance vector machine(RVM) for prediction of status of epimetemorphic rock slope. The input variables of SVM, LSSVM and RVM are bulk density, height, inclination, cohesion and internal friction angle. There are 53 datasets which have been used to develop the SVM, LSSVM and RVM models. The developed SVM, LSSVM and RVM give equations for prediction of status of epimetemorphic rock slope. The performance of SVM, LSSVM and RVM is 100%. A comparative study has been presented between the developed SVM, LSSVM and RVM. The results confirm that the developed SVM, LSSVM and RVM are effective tools for prediction of status of epimetemorphic rock slope.展开更多
文摘The Kaapvaal Craton in South Africa hosts one of the largest gold placer deposits in the world. Mining in the Witwatersrand Basin here has been the source of about one third to one half of the gold ever produced in the world. Gold was discovered in the Johannesburg area in 1886 and after 120 years of continuous operation, mining is currently approaching depths of 4 000 m. In spite of the challenges and risks that the industry has had to deal with including rock temperature, ventilation and water, one of the most feared hazards in the basin has been the threat from the ongoing occurrence of seismicity and rockbursts. The problem first manifested itself by way of the occurrence of tremors roughly twenty years after the commencement of mining operations. This paper traces the history of the approach to rockbursts and seismicity during the 120 year history of mining in the basin. It portrays a picture of the mining seismicity in terms of monitoring phases, mechanisms and mitigation strategies. The work of research organizations over the years is highlighted with a brief mention of current regulation strategies on the part of the mining inspectorate.
文摘The determination of seismic attenuation （s） （dB/cm） is a challenging task in earthquake science. This article employs genetic programming （GP） and minimax probability machine regression （MPMR） for prediction of s. GP is developed based on genetic algo- rithm. MPMR maximizes the minimum probability of future predictions being within some bound of the true regression function. Porosity （n） （%）, permeability （k） （millidarcy）, grain size （d） （μm）, and clay content （c） （%） have been considered as inputs of GP and MPMR. The output of GP and MPMR is s. The developed GP gives an equation for prediction of s. The results of GP and MPMR have been compared with the artificial neural net- work. This article gives robust models based on GP and MPMR for prediction of s.
文摘This article adopts three soft computing techniques including support vector machine(SVM), least square support vector machine(LSSVM) and relevance vector machine(RVM) for prediction of status of epimetemorphic rock slope. The input variables of SVM, LSSVM and RVM are bulk density, height, inclination, cohesion and internal friction angle. There are 53 datasets which have been used to develop the SVM, LSSVM and RVM models. The developed SVM, LSSVM and RVM give equations for prediction of status of epimetemorphic rock slope. The performance of SVM, LSSVM and RVM is 100%. A comparative study has been presented between the developed SVM, LSSVM and RVM. The results confirm that the developed SVM, LSSVM and RVM are effective tools for prediction of status of epimetemorphic rock slope.
