An effective clustering method based on data indeterminacy in neutrosophic set domain PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download An effective clustering method based on data indeterminacy in neutrosophic set domain PDF full book. Access full book title An effective clustering method based on data indeterminacy in neutrosophic set domain by Elyas Rashnoa. Download full books in PDF and EPUB format.
Author: Elyas Rashnoa
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 40
Get Book
Book Description
In this work, a new clustering algorithm is proposed based on neutrosophic set (NS) theory. The main contribution is to use NS to handle boundary and outlier points as challenging points of clustering methods. In the first step, a new de nition of data indeterminacy (indeterminacy set) is proposed in NS domain based on density properties of data.
Author: Elyas Rashnoa
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 40
Get Book
Book Description
In this work, a new clustering algorithm is proposed based on neutrosophic set (NS) theory. The main contribution is to use NS to handle boundary and outlier points as challenging points of clustering methods. In the first step, a new de nition of data indeterminacy (indeterminacy set) is proposed in NS domain based on density properties of data.
Author: Elyas Rashno
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 40
Get Book
Book Description
In this work, a new clustering algorithm is proposed based on neutrosophic set (NS) theory. The main contribution is to use NS to handle boundary and outlier points as challenging points of clustering methods.
Author: Dan Zhang
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 12
Get Book
Book Description
Clustering algorithm is one of the important research topics in the field of machine learning. Neutrosophic clustering is the generalization of fuzzy clustering and has been applied to many fields. this paper presents a new neutrosophic clustering algorithm with the help of regularization. Firstly, the regularization term is introduced into the FC-PFS algorithm to generate sparsity, which can reduce the complexity of the algorithm on large data sets. Secondly, we propose a method to simplify the process of determining regularization parameters. Finally, experiments show that the clustering results of this algorithm on artificial data sets and real data sets are mostly better than other clustering algorithms. Our clustering algorithm is effective in most cases.
Author: Broumi Said
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 118
Get Book
Book Description
International Journal of Neutrosophic Science (IJNS) is a peer-review journal publishing high quality experimental and theoretical research in all areas of Neutrosophic and its Applications. Papers concern with neutrosophic logic and mathematical structures in the neutrosophic setting. Besides providing emphasis on topics like artificial intelligence, pattern recognition, image processing, robotics, decision making, data analysis, data mining, applications of neutrosophic mathematical theories contributions to economics, finance, management, industries, electronics, and communications are promoted.
Author: Fahmi Aliya
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 25
Get Book
Book Description
The paper aims to give some new kinds of operational laws named as neutrality addition and scalar multiplication for the pairs of linguistic interval-valued intuitionistic neutrosophic fuzzy number. The main idea behind these operations is to include the linguistic interval-valued intuitionistic neutrosophic fuzzy number of the decision-maker and score function. We define the linguistic interval-valued intuitionistic neutrosophic fuzzy number and operational laws. We introduce the three geometric operators including, linguistic interval-valued intuitionistic neutrosophic fuzzy weighted geometric operator, linguistic interval-valued intuitionistic neutrosophic fuzzy ordered weighted geometric operator and linguistic interval-valued intuitionistic neutrosophic fuzzy weighted hybrid geometric operator.
Author: Xiaogang An
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 10
Get Book
Book Description
Abel-Grassmann’s groupoid and neutrosophic extended triplet loop are two important algebraic structures that describe two kinds of generalized symmetries. In this paper, we investigate quasi AG-neutrosophic extended triplet loop, which is a fusion structure of the two kinds of algebraic structures mentioned above.
Author: Sudan Jha
Publisher: Infinite Study
ISBN:
Category : Computers
Languages : en
Pages : 18
Get Book
Book Description
Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters. A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets. This paper focuses on cluster analysis based on neutrosophic set implication, i.e., a k-means algorithm with a threshold-based clustering technique. This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm. To evaluate the validity of the proposed method, several validity measures and validity indices are applied to the Iris dataset (from the University of California, Irvine, Machine Learning Repository) along with k-means and threshold-based clustering algorithms. The proposed method results in more segregated datasets with compacted clusters, thus achieving higher validity indices. The method also eliminates the limitations of threshold-based clustering algorithm and validates measures and respective indices along with k-means and threshold-based clustering algorithms.
Author: DEEPIKA KOUNDAL
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 19
Get Book
Book Description
In medical science, diagnosis and prognosis is one of the most difficult and challenging task because of restricted subjectivity of the experts and presence of fuzziness in medical images. In observing the severity of several diseases, different professional experts may result in wrong diagnosis. In order to perform diagnosis intuitively in the medical images, different image processing methods have been explored in terms of neutrosophic theory to interpret the inherent uncertainty, ambiguity and vagueness. This paper demonstrates the use of neutrosophic theory in medical image denoising and segmentation where the performance is observed to be much better.
Author: Anupama Namburu
Publisher: CRC Press
ISBN: 1000221709
Category : Computers
Languages : en
Pages : 150
Get Book
Book Description
This was the first conference organized by the school of Computer Science Engineering in VIT-AP University campus with the cumulative efforts of all the faculty members. The proceedings discusses recent advancements and novel ideas in areas of interest. It covers topics such as advances in computer based systems, processes and applications
Author: Cengiz Kahraman
Publisher: Springer
ISBN: 3030000451
Category : Technology & Engineering
Languages : en
Pages : 735
Get Book
Book Description
This book offers a comprehensive guide to the use of neutrosophic sets in multiple criteria decision making problems. It shows how neutrosophic sets, which have been developed as an extension of fuzzy and paraconsistent logic, can help in dealing with certain types of uncertainty that classical methods could not cope with. The chapters, written by well-known researchers, report on cutting-edge methodologies they have been developing and testing on a variety of engineering problems. The book is unique in its kind as it reports for the first time and in a comprehensive manner on the joint use of neutrosophic sets together with existing decision making methods to solve multi-criteria decision-making problems, as well as other engineering problems that are complex, hard to model and/or include incomplete and vague data. By providing new ideas, suggestions and directions for the solution of complex problems in engineering and decision making, it represents an excellent guide for researchers, lecturers and postgraduate students pursuing research on neutrosophic decision making, and more in general in the area of industrial and management engineering.
