نتایج جستجو برای: concentration number c n fractal model logratio matrix

تعداد نتایج: 4900967  

2009
Kazuhiko MINAMI

Fractal structure of the six-vertex model is introduced with the use of the IFS (Iterated Function Systems). The fractal dimension satisfies an equation written by the free energy of the six-vertex model. It is pointed out that the transfer matrix method and the n-equivalence relation introduced in lattice theories have also been introduced in the area of fractal geometry. All the results can b...

The Zarshuran Carlin-like gold deposit is located at the Takab Metallogenic belt in the northern part of the Sanandaj-Sirjan zone, NW Iran. The high-grade ore bodies are mainly hosted by black shale and cream to gray massive limestone along the NNE-trending extensional fault/fracture zones. The aim of this investigation was to determine and separate the gold mineralized stages based on the surf...

The purpose of this study is to identify the enriched zones of Cu, Mo and Re in Nowchun Mo-Cu porphyry deposit (SE Iran) based on subsurface data and using of concentration–volume (C–V) fractal model. The C-V model illustrates four and five geochemical zones based on Mo and Cu distributions respectively and there are three geochemical populations for Re. The main mineralization for Mo, Cu and R...

The most significant aspect of a geochemical exploration program is to define and separate the anomalous values from the background. In the past decades, geochemical anomalies have been identified by means of various methods. Most of the conventional statistical methods aiming at defining the geochemical concentration thresholds for separating anomalies from the background have limited the effi...

2008
Julien Prados Alexandros Kalousis Melanie Hilario

In this article we present a novel kernel function, logRatio, which was designed to address two common problems in biological applications: data preprocessing and attribute interaction modelling. An extension of the SVMRFE feature selection algorithm was built around this new kernel function and compared with the original on a number of biological data and text classification problems. Experime...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه صنعتی اصفهان - دانشکده ریاضی 1390

به طور کلی در فرآیندهای مارکوف ارگودیک دو بعدی یافتن فرم بسته توزیع ایستا، تنها برای حالات خیلی خاص امکان پذیر است. با توجه به این مشکل و نیز با توجه به اهمیت توزیع ایستا، بررسی و مطالعه رفتار مجانبی توزیع ایستای این فرآیندها مورد توجه قرار گرفته است. زنجیر قدم زدن تصادفی دو بعدی که در برخی متون به آن، فرآیند qbd دو طرفه نیز می گویند، یکی از این فرآیندها است. یک فرآیند qbd زمان گسسته یک زنجیر م...

Abstract Most conventional statistical methods aiming at defining geochemical concentration thresholds for separating anomalies from background have limited effectiveness in areas with complex geological settings and variable lithology. In this paper, median+2MAD as a method of exploratory data analysis (EDA) and concentration-area (C-A) fractal model as two effective approaches in separation g...

Resources/reserves classification is crucial for block model creation utilised in mine planning and feasibility study. Selection of estimation methods is an essential part of mineral exploration and mining activities. In other word, resources classification is an issue for mining companies, investors, financial institutions and authorities, but it remains subject to some confusion. The aim of t...

A. K. Wadhwani Manish Dubey, Monika Saraswat

The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN  of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most      relevant information of X. These eigenvectors are called principal components [8]. Ass...

A. K. Wadhwani Manish Dubey, Monika Saraswat

The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN  of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most      relevant information of X. These eigenvectors are called principal components [8]. Ass...

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