On detecting outliers in complex data using Dixon’s test under neutrosophic statistics PDF Download

Author: Muhammad Aslam
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 4

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Book Description
The existing Dixon’s test (DT) under classical statistics has been widely applied in a variety of fields. The main target of DT is to recognize the outlier or suspicious observation in the sample. The DT available in the literature is workable when all the observations in the sample or the population are precise, determined and certain. In practice, under the complex system, it may not possible that all observations in the data are determined.

Author: Muhammad Aslam
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 5

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Book Description
In this paper, we will introduce the designing of Grubbs’s test under neutrosophic statistics. The proposed test will be a generalization of Grubbs’s test under classical statistics. We will present the designing and the operational procedure of the proposed test under the neutrosophic statistical interval method.

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: Springer Nature
ISBN: 3030571971
Category : Business & Economics
Languages : en
Pages : 628

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Book Description
This book addresses new concepts, methods, algorithms, modeling, and applications of green supply chain, inventory control problems, assignment problems, transportation problem, linear problems and new information related to optimization for the topic from the theoretical and applied viewpoints of neutrosophic sets and logic. The book is an innovatory of new tools and procedures, such as: Neutrosophic Statistical Tests and Dependent State Samplings, Neutrosophic Probabilistic Expert Systems, Neutrosophic HyperSoft Set, Quadripartitioned Neutrosophic Cross-Entropy, Octagonal and Spherical and Cubic Neutrosophic Numbers used in machine learning. It highlights the process of neutrosofication {which means to split the universe into three parts, two opposite ones (Truth and Falsehood), and an Indeterminate or neutral one (I) in between them}. It explains Three-Ways Decision, how the universe set is split into three different distinct areas, in regard to the decision process, representing: Acceptance, Noncommitment, and Rejection, respectively. The Three-Way Decision is used in the Neutrosophic Linguistic Rough Set, which has never been done before.

Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 314

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Book Description
“Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc.

Author: Maria Letizia Guerra
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 15

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Book Description
Value at Risk (VaR) has become a crucial measure for decision making in risk management over the last thirty years and many estimation methodologies address the finding of the best performing measure at taking into account unremovable uncertainty of real financial markets. One possible and promising way to include uncertainty is to refer to the mathematics of fuzzy numbers and to its rigorous methodologies which offer flexible ways to read and to interpret properties of real data which may arise in many areas. The paper aims to show the effectiveness of two distinguished models to account for uncertainty in VaR computation; initially, following a non parametric approach, we apply the Fuzzy-transform approximation function to smooth data by capturing fundamental patterns before computing VaR.

Author: Hyoshin Kim
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 15

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Book Description
This paper proposes an a-level estimation algorithm for ridge fuzzy regression modeling, addressing the multicollinearity phenomenon in the fuzzy linear regression setting.

Author: Mohammed Albassam
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 5

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Book Description
The D’Agostino test has been widely applied for testing the normality of the data. (e existing D’Agostino test cannot be applied when the data have some indeterminate observations or observations which are obtained from the complex systems. In this paper, we present a D’Agostino test under neutrosophic statistics. We propose the D’Agostino test to test the normality of the data having indeterminate observations. The design of the proposed test is given and implemented with the help of real data. From the comparison, it is concluded that the proposed test is effective, adequate, and suitable to be applied in the presence of indeterminacy.

Author: De-Shuang Huang
Publisher: Springer Nature
ISBN: 9819947421
Category : Technology & Engineering
Languages : en
Pages : 827

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Book Description
This three-volume set of LNCS 14086, LNCS 14087 and LNCS 14088 constitutes - in conjunction with the double-volume set LNAI 14089-14090- the refereed proceedings of the 19th International Conference on Intelligent Computing, ICIC 2023, held in Zhengzhou, China, in August 2023. The 337 full papers of the three proceedings volumes were carefully reviewed and selected from 828 submissions. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers that focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.

Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
ISBN: 1461463963
Category : Computers
Languages : en
Pages : 457

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Book Description
With the increasing advances in hardware technology for data collection, and advances in software technology (databases) for data organization, computer scientists have increasingly participated in the latest advancements of the outlier analysis field. Computer scientists, specifically, approach this field based on their practical experiences in managing large amounts of data, and with far fewer assumptions– the data can be of any type, structured or unstructured, and may be extremely large. Outlier Analysis is a comprehensive exposition, as understood by data mining experts, statisticians and computer scientists. The book has been organized carefully, and emphasis was placed on simplifying the content, so that students and practitioners can also benefit. Chapters will typically cover one of three areas: methods and techniques commonly used in outlier analysis, such as linear methods, proximity-based methods, subspace methods, and supervised methods; data domains, such as, text, categorical, mixed-attribute, time-series, streaming, discrete sequence, spatial and network data; and key applications of these methods as applied to diverse domains such as credit card fraud detection, intrusion detection, medical diagnosis, earth science, web log analytics, and social network analysis are covered.