Scale Effect and Anisotropic Analysis of Rock Joint Roughness Coefficient Neutrosophic Interval Statistical Numbers Based on Neutrosophic Statistics PDF Download
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Author: Wenzhong Jiang
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 11
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Book Description
In rock mechanics, mechanical properties of rock masses in nature imply complexity and diversity. The shear strength of rock mass is a key factor for affecting the stability of the rock mass. Then, the joint roughness coefficient (JRC) of rock indicates an important parameter in the shear strength and stability analysis of rock mass. Since the nature of the rock mass is indeterminate and incomplete to some extent, we cannot always express rock JRC by a certain/exact number. Therefore, this paper introduces neutrosophic interval statistical numbers (NISNs) based on the concepts of neutrosophic numbers and neutrosophic interval probability to express JRC data of the rock mass in the indeterminate setting. Then we present the calculational method of the neutrosophic average value and standard deviation of NISNs based on neutrosophic statistics. Next, by an actual case, the neutrosophic average value and standard deviation of the rock JRC NISNs are used to analyze the scale effect and anisotropy of the rock body corresponding to different sample lengths and measuring directions. Lastly, the analysis method of the scale effect and anisotropy for JRC NISNs shows its effectiveness and rationality in the actual case study.
Author: Wenzhong Jiang
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 11
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Book Description
In rock mechanics, mechanical properties of rock masses in nature imply complexity and diversity. The shear strength of rock mass is a key factor for affecting the stability of the rock mass. Then, the joint roughness coefficient (JRC) of rock indicates an important parameter in the shear strength and stability analysis of rock mass. Since the nature of the rock mass is indeterminate and incomplete to some extent, we cannot always express rock JRC by a certain/exact number. Therefore, this paper introduces neutrosophic interval statistical numbers (NISNs) based on the concepts of neutrosophic numbers and neutrosophic interval probability to express JRC data of the rock mass in the indeterminate setting. Then we present the calculational method of the neutrosophic average value and standard deviation of NISNs based on neutrosophic statistics. Next, by an actual case, the neutrosophic average value and standard deviation of the rock JRC NISNs are used to analyze the scale effect and anisotropy of the rock body corresponding to different sample lengths and measuring directions. Lastly, the analysis method of the scale effect and anisotropy for JRC NISNs shows its effectiveness and rationality in the actual case study.
Author: Jiqian Chen
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 14
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Book Description
In rock mechanics, the study of shear strength on the structural surface is crucial to evaluating the stability of engineering rock mass. In order to determine the shear strength, a key parameter is the joint roughness coefficient (JRC). To express and analyze JRC values, Ye et al. have proposed JRC neutrosophic numbers (JRC-NNs) and fitting functions of JRC-NNs, which are obtained by the classical statistics and curve fitting in the current method.
Author: Wenzhong Jiang
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 10
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Book Description
This paper introduces neutrosophic interval statistical numbers (NISNs) based on the concepts of neutrosophic numbers and neutrosophic interval probability to express JRC data of the rock mass in the indeterminate setting.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 18
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Book Description
In this paper, we prove that Neutrosophic Statistics is more general than Interval Statistics, since it may deal with all types of indeterminacies (with respect to the data, inferential procedures, probability distributions, graphical representations, etc.), it allows the reduction of indeterminacy, and it uses the neutrosophic probability that is more general than imprecise and classical probabilities and has more detailed corresponding probability density functions. While Interval Statistics only deals with indeterminacy that can be represented by intervals. And we respond to the arguments by Woodall et al. [1]. We show that not all indeterminacies (uncertainties) may be represented by intervals. Also, in some cases, we should better use hesitant sets (that have less indeterminacy) instead of intervals. We redirect the authors to the Plithogenic Probability and Plithogenic Statistics which are the most general forms of MultiVariate Probability and Multivariate Statistics respectively (including, of course, the Imprecise Probability and Interval Statistics as subclasses).
Author: Florentin Smarandache
Publisher: Elsevier
ISBN: 0323994571
Category : Computers
Languages : en
Pages : 495
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Book Description
Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics investigates and presents the many applications that have arisen in the last ten years using neutrosophic statistics in bioinformatics, medicine, agriculture and cognitive science. This book will be very useful to the scientific community, appealing to audiences interested in fuzzy, vague concepts from which uncertain data are collected, including academic researchers, practicing engineers and graduate students. Neutrosophic statistics is a generalization of classical statistics. In classical statistics, the data is known, formed by crisp numbers. In comparison, data in neutrosophic statistics has some indeterminacy. This data may be ambiguous, vague, imprecise, incomplete, and even unknown. Neutrosophic statistics refers to a set of data, such that the data or a part of it are indeterminate in some degree, and to methods used to analyze the data. Introduces the field of neutrosophic statistics and how it can solve problems working with indeterminate (imprecise, ambiguous, vague, incomplete, unknown) data Presents various applications of neutrosophic statistics in the fields of bioinformatics, medicine, cognitive science and agriculture Provides practical examples and definitions of neutrosophic statistics in relation to the various types of indeterminacies
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Antiques & Collectibles
Languages : en
Pages : 487
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Book Description
Papers on neutrosophic programming, neutrosophic hypersoft set, neutrosophic topological spaces, NeutroAlgebra, NeutroGeometry, AntiGeometry, NeutroNearRings, neutrosophic differential equations, etc.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 970
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Book Description
This fourteenth volume of Collected Papers is an eclectic tome of 87 papers in Neutrosophics and other fields, such as mathematics, fuzzy sets, intuitionistic fuzzy sets, picture fuzzy sets, information fusion, robotics, statistics, or extenics, comprising 936 pages, published between 2008-2022 in different scientific journals or currently in press, by the author alone or in collaboration with the following 99 co-authors (alphabetically ordered) from 26 countries: Ahmed B. Al-Nafee, Adesina Abdul Akeem Agboola, Akbar Rezaei, Shariful Alam, Marina Alonso, Fran Andujar, Toshinori Asai, Assia Bakali, Azmat Hussain, Daniela Baran, Bijan Davvaz, Bilal Hadjadji, Carlos Díaz Bohorquez, Robert N. Boyd, M. Caldas, Cenap Özel, Pankaj Chauhan, Victor Christianto, Salvador Coll, Shyamal Dalapati, Irfan Deli, Balasubramanian Elavarasan, Fahad Alsharari, Yonfei Feng, Daniela Gîfu, Rafael Rojas Gualdrón, Haipeng Wang, Hemant Kumar Gianey, Noel Batista Hernández, Abdel-Nasser Hussein, Ibrahim M. Hezam, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Muthusamy Karthika, Nour Eldeen M. Khalifa, Madad Khan, Kifayat Ullah, Valeri Kroumov, Tapan Kumar Roy, Deepesh Kunwar, Le Thi Nhung, Pedro López, Mai Mohamed, Manh Van Vu, Miguel A. Quiroz-Martínez, Marcel Migdalovici, Kritika Mishra, Mohamed Abdel-Basset, Mohamed Talea, Mohammad Hamidi, Mohammed Alshumrani, Mohamed Loey, Muhammad Akram, Muhammad Shabir, Mumtaz Ali, Nassim Abbas, Munazza Naz, Ngan Thi Roan, Nguyen Xuan Thao, Rishwanth Mani Parimala, Ion Pătrașcu, Surapati Pramanik, Quek Shio Gai, Qiang Guo, Rajab Ali Borzooei, Nimitha Rajesh, Jesús Estupiñan Ricardo, Juan Miguel Martínez Rubio, Saeed Mirvakili, Arsham Borumand Saeid, Saeid Jafari, Said Broumi, Ahmed A. Salama, Nirmala Sawan, Gheorghe Săvoiu, Ganeshsree Selvachandran, Seok-Zun Song, Shahzaib Ashraf, Jayant Singh, Rajesh Singh, Son Hoang Le, Tahir Mahmood, Kenta Takaya, Mirela Teodorescu, Ramalingam Udhayakumar, Maikel Y. Leyva Vázquez, V. Venkateswara Rao, Luige Vlădăreanu, Victor Vlădăreanu, Gabriela Vlădeanu, Michael Voskoglou, Yaser Saber, Yong Deng, You He, Youcef Chibani, Young Bae Jun, Wadei F. Al-Omeri, Hongbo Wang, Zayen Azzouz Omar.
Author: Jiqian Chen
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 7
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Book Description
In nature, the mechanical properties of geological bodies are very complex, and their various mechanical parameters are vague, incomplete, imprecise, and indeterminate. However, we cannot express them by the crisp values in classical probability and statistics. In geotechnical engineering, we need to try our best to approximate exact values in indeterminate environments because determining the joint roughness coefficient (JRC) effectively is a key parameter in the shear strength between rock joint surfaces. In this original study, we first propose neutrosophic interval probability (NIP) and define the confidence degree based on the cosine measure between NIP and the ideal NIP.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN: 1599732742
Category : Mathematics
Languages : en
Pages : 125
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Book Description
Neutrosophic Statistics means statistical analysis of population or sample that has indeterminate (imprecise, ambiguous, vague, incomplete, unknown) data. For example, the population or sample size might not be exactly determinate because of some individuals that partially belong to the population or sample, and partially they do not belong, or individuals whose appurtenance is completely unknown. Also, there are population or sample individuals whose data could be indeterminate. In this book, we develop the 1995 notion of neutrosophic statistics. We present various practical examples. It is possible to define the neutrosophic statistics in many ways, because there are various types of indeterminacies, depending on the problem to solve.
Author: Florentin Smarandache
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 110
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Book Description
