کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
506798 865040 2016 10 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
Comparison of particle swarm optimization and simulated annealing for locating additional boreholes considering combined variance minimization
ترجمه فارسی عنوان
مقایسه بهینه سازی ازدحام ذرات و بازپخت شبیه سازی شده برای مکان یابی گمانه اضافی با توجه به حداقل رساندن ترکیب واریانس
کلمات کلیدی
حفاری اضافی. زمین آمار؛ ترکیبی واریانس؛ بهینه سازی ازدحام ذرات؛ بازپخت شبیه سازی شده
Additional drilling; Geostatistics; Combined variance; Particle swarm optimization; Simulated annealing
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• Definition of new objective function for locating additional boreholes.
• Application of metaheuristic methods for objective function minimization.
• Comparison of results from proposed objective function to conventional ones.
• Validation of algorithm in Esphordi phosphate mine.

One of the most important stages in complementary exploration is optimal designing the additional drilling pattern or defining the optimum number and location of additional boreholes. Quite a lot research has been carried out in this regard in which for most of the proposed algorithms, kriging variance minimization as a criterion for uncertainty assessment is defined as objective function and the problem could be solved through optimization methods. Although kriging variance implementation is known to have many advantages in objective function definition, it is not sensitive to local variability. As a result, the only factors evaluated for locating the additional boreholes are initial data configuration and variogram model parameters and the effects of local variability are omitted. In this paper, with the goal of considering the local variability in boundaries uncertainty assessment, the application of combined variance is investigated to define the objective function. Thus in order to verify the applicability of the proposed objective function, it is used to locate the additional boreholes in Esfordi phosphate mine through the implementation of metaheuristic optimization methods such as simulated annealing and particle swarm optimization. Comparison of results from the proposed objective function and conventional methods indicates that the new changes imposed on the objective function has caused the algorithm output to be sensitive to the variations of grade, domain's boundaries and the thickness of mineralization domain. The comparison between the results of different optimization algorithms proved that for the presented case the application of particle swarm optimization is more appropriate than simulated annealing.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Geosciences - Volume 95, October 2016, Pages 146–155
نویسندگان
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