mohammadjavad rezapour
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International Journal of Mining & Geo-Engineering, Volume:55 Issue: 1, Winter-Spring 2021, PP 17 -26
This work presents a hybrid-based clustering approach for mineral potential mapping (MPM) of porphyry-type Cu mineralization at Kerman province in the SE of Iran. Whereby a multidisciplinary geospatial data set was processed and integrated in the Chahargonbad district. Data-driven prediction-area (P-A) plots were drawn for each evidence layer derived from geological, geochemical, geophysical and satellite imagery data. The P-A plots provide insight into the weight of evidence for synthesizing all geospatial layers. Out of many knowledge-driven methods which biasing from experts' opinions, index overlay and fuzzy operators were employed to find out an optimum Cu favorability map through calculating an efficiency index representing the performance of each MPM. A concentration-area (C-A) fractal model was implemented to separate the mineral favorability map into some populations to ensure correct determining the cluster numbers. Clusters number is a prerequisite which must be defined correctly to increase the performance of clustering analysis for generating reliable results in MPM. Such an appropriate number of clusters can be incorporated in running three prevalent groups of clustering methodologies as data-driven approaches in MPM. They are self-organizing map, fuzzy c-means, and k-means algorithms. One of the reasons for this tendency to consider a hybrid-based method is that it overcomes the shortcomings of the both methods (bias of experts’ opinions and unknown clusters number) in mineral favorability mapping. The unknown number of clusters was determined through a knowledge-driven method, and then it was passed to an unsupervised data-driven method, i.e. clustering algorithm. This hybrid method produces synthesized maps in close association with known porphyry-Cu mineralization in the Chahargonbad area.
Keywords: Clustering, hybrid method, Mineral Potential Mapping, Porphyry copper, Chahargonbad -
ماده 4 قانون تشدید مجازات مرتکبین ارتشاء و اختلاس و کلاهبرداری مصوب 15/9/1367 مجمع تشخیص مصلحت نظام -که نقش مهمی در رسیدگی به پرونده های کیفری مربوط به مفاسد اقتصادی و جرایم علیه رونق تولید دارد- نوعی از مداخله گروهی در ارتکاب جرایم ارتشاء، اختلاس و کلاهبرداری را تحت عنوان «تشکیل یا رهبری شبکه چند نفری» توصیف کرده و مشمول مجازات های شدیدی قرار داده است. با این حال، نواقص و ابهامات موجود در این مقرره، موجب پیدایش دیدگاه های حقوقی مختلف و شکل گیری رویه-های قضایی مغایری درباره اجزاء و شرایط تحقق وصف مجرمانه موضوع آن مقرره شده است. تحقیق حاضر به روش توصیفی تحلیلی به بررسی این مساله پرداخته و به این نتیجه رسیده است که به دلیل ابهامات مقرره مزبور از یک سو و اشکالات و نواقص دیدگاه های مربوط به آن از سوی دیگر، شکل گیری وحدت رویه قضایی در آینده نزدیک بسیار بعید به نظر می رسد؛ از این رو، پیشگیری از بروز جرایم علیه رونق تولید و مفاسد اقتصادی، مقتضی آن است که اصلاح آن مقرره در اولویت برنامه های قانون گذار قرار گیرد.
کلید واژگان: ارتشاء، اختلاس، کلاهبرداری، ارتکاب شبکه ای، جرایم اقتصادیArticle 4 of severing punishment of perpetrators of Bribery and Embezzlement and Fraud Act (1367.09.15) –that have had an important role in proceeding of criminal cases related to economic corruption and crimes against prosperity of manufacturing- describes a kind of group intervention in those crimes as “making or leadership of a net” punishable by sever punishments. Defects and ambiguities of that Article, however, have arose deferent legal viewpoints and made various judicial proceedings over elements and conditions of that criminal commitment. The present study with a descriptive-analytical method has examined the matter and concluded that arising a unification in judicial proceeding is impossible in a near future due to ambiguities of the Article and defects of related viewpoints; Prevention of crimes against prosperity of manufacturing and economic corruption, therefor, necessitates that the amendment of that Article set in preference of programs of legislator.
Keywords: Bribery, Embezzlement, Fraud, Net-Perpetration, Economic crimes -
This work describes a knowledge-guided clustering approach for mineral potential mapping (MPM), by which the optimum number of clusters is derived form a knowledge-driven methodology through a concentration-area (C-A) multifractal analysis. To implement the proposed approach, a case study at the North Narbaghi region in the Saveh, Markazi province of Iran, was investigated to discover porphyry Cu-bearing favorability zones. Whereby, various exploratory indicators were extracted from a multidisciplinary geospatial data set comprising of geology, geophysics and geochemistry criteria. Those indicators were prepared from magnetometry and geo-electrical survey, lithogeochemical samples and geological field operation. The optimum number of clusters was obtained by running the knowledge-based methods of index overlay and fuzzy gamma operators, indicating five clusters from the C-A multifractal curve. Accessing to exploratory drilling lets us to find out the most efficient synthesized favorability map that was generated by a fuzzy algebraic sum operator (or a gamma value equal to one). Assuming the optimum number of clusters, three clustering methods, namely fuzzy C-means (FCM), K-means and self-organizing map were examined for MPM. Note that the FCM as an unsupervised data-driven methodology, had superiority over other clustering analyses by generating mineral favorability map in close association with drilling results.
Keywords: Mineral Potential Mapping, Index Overlay, Fuzzy Gamma Operator, Clustering
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