Uncertainty in determining optimum conjunctive water use lies not only on variability of hydrological cycle and climate but also on lack of adequate data and perfect knowledge about groundwater-surface water system in...Uncertainty in determining optimum conjunctive water use lies not only on variability of hydrological cycle and climate but also on lack of adequate data and perfect knowledge about groundwater-surface water system interactions, errors in historic data and inherent variability of system parameters both in space and time. Simulation-optimization models are used for conjunctive water use management under uncertain conditions. However, direct application of such approach whereby all realizations are considered at every-iteration of the optimization process leads to a highly computational time-consuming optimization problem as the number of realizations increases. Hence, this study proposes a novel approach—a Retrospective Optimization Approximation (ROA) approach. In this approach, a simulation model was used to determine aquifer system responses (draw-downs) which were assembled as response matrices and incorporated in the optimization model (procedure) as coefficients in the constraints. The sample optimization sub-problems generated, were solved and analyzed through ROA-Active-Set procedure implemented under MATLAB code. The ROA-Active Set procedure solves and evaluates a sequence of sample path optimization sub-problems in an increasing number of realizations. The methodology was applied to a real-world conjunctive water use management problem found in Great Letaba River basin, South Africa. In the River basin, surface water source contributes 87% of the existing un-optimized total conjunctive water use withdrawal rate (6512.04 m<sup>3</sup>/day) and the remaining 13% is contributed by groundwater source. Through ROA approach, results indicate that the optimum percentages contribution of the surface and subsurface sources to the total water demand are 58% and 42% respectively. This implies that the existing percentage contribution can be increased or reduced by ±29% that is groundwater source can be increased by 29% while the surface water source contribution can be reduced by 29%. This reveals that the existing conjunctive water use practice is unsustainable wherein surface water system is overstressed while groundwater system is under-utilized. Through k-means sampling technique ROA-Active Set procedure was able to attain a converged maximum expected total optimum conjunctive water use withdrawal rate of 4.35 × 10<sup>4</sup> m<sup>3</sup>/day within a relatively few numbers of iterations (6 to 8 iterations) in about 2.30 Hrs. In conclusion, results demonstrated that ROA approach is capable of managing real-world regional aquifers sustainable conjunctive water use practice under hydro-geological uncertainty conditions.展开更多
Reserve estimation is a key to find the correct NPV in a mining project. The most important factor in reserve estimation is the metal price. Metal price fluctuations in recent years were exaggerated, and imposed a hig...Reserve estimation is a key to find the correct NPV in a mining project. The most important factor in reserve estimation is the metal price. Metal price fluctuations in recent years were exaggerated, and imposed a high degree of uncertainty to the reserve estimation, and in consequence to the whole mine planning procedure. Real option approach is an efficient method of decision making in the uncertain conditions. This approach has been used for evaluation of defined natural resources projects until now. This study considering the metal price uncertainty used real option approach to prepare a methodology for reserve estimation in open pit mines. This study was done on a copper cylindrical deposit, but the achieved methodology can be adjusted for all kinds of deposits. This methodology was comprehensively described through the examples in such a manner that can be used by the mine planners.展开更多
为解决传统均值比(ratio of average,ROA)算子检测SAR(synthetic aperture radar,SAR)图像边缘时出现的受噪声影响大和边缘定位精度低等问题,结合平稳小波变换的优点,提出一种平稳小波去噪和改进ROA算法的SAR图像边缘检测方法。首先,利...为解决传统均值比(ratio of average,ROA)算子检测SAR(synthetic aperture radar,SAR)图像边缘时出现的受噪声影响大和边缘定位精度低等问题,结合平稳小波变换的优点,提出一种平稳小波去噪和改进ROA算法的SAR图像边缘检测方法。首先,利用平稳小波进行去噪预处理,减少相干斑噪声。然后,通过把传统ROA算子的4个检测方向增加为8个,以及利用非极值抑制进行边缘定位,在检测方向和定位精度两个方面改进ROA算法。实验结果表明,该方法的去噪性能和边缘检测效果较好。研究结论对传统ROA算法做了改进,使其更好地适用于SAR图像边缘检测。展开更多
文摘Uncertainty in determining optimum conjunctive water use lies not only on variability of hydrological cycle and climate but also on lack of adequate data and perfect knowledge about groundwater-surface water system interactions, errors in historic data and inherent variability of system parameters both in space and time. Simulation-optimization models are used for conjunctive water use management under uncertain conditions. However, direct application of such approach whereby all realizations are considered at every-iteration of the optimization process leads to a highly computational time-consuming optimization problem as the number of realizations increases. Hence, this study proposes a novel approach—a Retrospective Optimization Approximation (ROA) approach. In this approach, a simulation model was used to determine aquifer system responses (draw-downs) which were assembled as response matrices and incorporated in the optimization model (procedure) as coefficients in the constraints. The sample optimization sub-problems generated, were solved and analyzed through ROA-Active-Set procedure implemented under MATLAB code. The ROA-Active Set procedure solves and evaluates a sequence of sample path optimization sub-problems in an increasing number of realizations. The methodology was applied to a real-world conjunctive water use management problem found in Great Letaba River basin, South Africa. In the River basin, surface water source contributes 87% of the existing un-optimized total conjunctive water use withdrawal rate (6512.04 m<sup>3</sup>/day) and the remaining 13% is contributed by groundwater source. Through ROA approach, results indicate that the optimum percentages contribution of the surface and subsurface sources to the total water demand are 58% and 42% respectively. This implies that the existing percentage contribution can be increased or reduced by ±29% that is groundwater source can be increased by 29% while the surface water source contribution can be reduced by 29%. This reveals that the existing conjunctive water use practice is unsustainable wherein surface water system is overstressed while groundwater system is under-utilized. Through k-means sampling technique ROA-Active Set procedure was able to attain a converged maximum expected total optimum conjunctive water use withdrawal rate of 4.35 × 10<sup>4</sup> m<sup>3</sup>/day within a relatively few numbers of iterations (6 to 8 iterations) in about 2.30 Hrs. In conclusion, results demonstrated that ROA approach is capable of managing real-world regional aquifers sustainable conjunctive water use practice under hydro-geological uncertainty conditions.
文摘Reserve estimation is a key to find the correct NPV in a mining project. The most important factor in reserve estimation is the metal price. Metal price fluctuations in recent years were exaggerated, and imposed a high degree of uncertainty to the reserve estimation, and in consequence to the whole mine planning procedure. Real option approach is an efficient method of decision making in the uncertain conditions. This approach has been used for evaluation of defined natural resources projects until now. This study considering the metal price uncertainty used real option approach to prepare a methodology for reserve estimation in open pit mines. This study was done on a copper cylindrical deposit, but the achieved methodology can be adjusted for all kinds of deposits. This methodology was comprehensively described through the examples in such a manner that can be used by the mine planners.
文摘为解决传统均值比(ratio of average,ROA)算子检测SAR(synthetic aperture radar,SAR)图像边缘时出现的受噪声影响大和边缘定位精度低等问题,结合平稳小波变换的优点,提出一种平稳小波去噪和改进ROA算法的SAR图像边缘检测方法。首先,利用平稳小波进行去噪预处理,减少相干斑噪声。然后,通过把传统ROA算子的4个检测方向增加为8个,以及利用非极值抑制进行边缘定位,在检测方向和定位精度两个方面改进ROA算法。实验结果表明,该方法的去噪性能和边缘检测效果较好。研究结论对传统ROA算法做了改进,使其更好地适用于SAR图像边缘检测。
