Rough Neutrosophic Digraphs with Application

A rough neutrosophic set model is a hybrid model which deals with vagueness by using the lower and upper approximation spaces. In this research paper, we apply the concept of rough neutrosophic sets to graphs. We introduce rough neutrosophic digraphs and describe methods of their construction. Moreover, we present the concept of self complementary rough neutrosophic digraphs. Finally, we consider an application of rough neutrosophic digraphs in decision-making

Quadripartitioned single valued neutrosophic rough sets and their applications in decision making

This paper introduces the notion of quadripartitioned single valued neutrosophic rough set. Some basic set metaphysical terminologies, operations and properties of quadripartitioned single valued neutrosophic rough set are given here. Conjointly different kinds of distances and similarity measures are mentioned here. Finally a decision making problem using the similarity measure technique of quadripartitioned single valued neutrosophic rough sets has been solved.Publisher's Versio

Intuitionistic Fuzzy Soft Rough Set and Its Application in Decision Making

The soft set theory, originally proposed by Molodtsov, can be used as a general mathematical tool for dealing with uncertainty. In this paper, we present concepts of soft rough intuitionistic fuzzy sets and intuitionistic fuzzy soft rough sets, and investigate some properties of soft rough intuitionistic fuzzy sets and intuitionistic fuzzy soft rough sets in detail. Furthermore, classical representations of intuitionistic fuzzy soft rough approximation operators are presented. Finally, we develop an approach to intuitionistic fuzzy soft rough sets based on decision making and a numerical example is provided to illustrate the developed approach

Rough sets for mining educational data

While educational data are typically analyzed with statistical software, data mining techniques are increasingly appropriate in revealing complex relationships among multiple variables in large amounts of data. We experimented with the rough set method in conjunction with statistical analysis to identify patterns in, and thereby extract meaning from, complex educational data. Results establish the benefits of combining rough set decision making with stochastic analysis in mining exceedingly complex and difficult to interpret educational data sets

An Intelligent Agent Based Intrusion Detection System Using Fuzzy Rough Set Based Outlier Detection

Since existing Intrusion Detection Systems (IDS) including misuse detection and anomoly detection are generally incapable of detecting new type of attacks. However, all these systems are capable of detecting intruders with high false alarm rate. It is an urgent need to develop IDS with very high Detection rate and with low False alarm rate. To satisfy this need we propose a new intelligent agent based IDS using Fuzzy Rough Set based outlier detection and Fuzzy Rough set based SVM. In this proposed model we intorduced two different inteligent agents namely feature selection agent to select the required feature set using fuzzy rough sets and decision making agent manager for making final decision. Moreover, we have introduced fuzzy rough set based outlier detection algorithm to detect outliers. We have also adopted Fuzzy Rough based SVM in our system to classify and detect anomalies efficiently. Finally, we have used KDD Cup 99 data set for our experiment, the experimental result show that the proposed intelligent agent based model improves the overall accuracy and reduces the false alarm rate

Rough Neutrosophic TOPSIS for Multi-Attribute Group Decision Making

This paper is devoted to present Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for multi-attribute group decision making under rough neutrosophic environment. The concept of rough neutrosophic set is a powerful mathematical tool to deal with uncertainty, indeterminacy and inconsistency. In this paper, a new approach for multi-attribute group decision making problems is proposed by extending the TOPSIS method under rough neutrosophic environment. Rough neutrosophic set is characterized by the upper and lower approximation operators and the pair of neutrosophic sets that are characterized by truth-membership degree, indeterminacy membership degree, and falsity membership degree. In the decision situation, ratings of alternatives with respect to each attribute are characterized by rough neutrosophic sets that reflect the decision makers’ opinion. Rough neutrosophic weighted averaging operator has been used to aggregate the individual decision maker’s opinion into group opinion for rating the importance of attributes and alternatives. Finally, a numerical example has been provided to demonstrate the applicability and effectiveness of the proposed approach

Multi Attribute Decision Making Strategy on Projection and Bidirectional Projection Measures of Interval Rough Neutrosophic Sets

In this paper, we define projection and bidirectional projection measures between interval rough neutrosophic sets and prove their basic properties. Then two new multi attribute decision making strategies are proposed based on interval rough neutrosophic projection and bidirectional projection measures respectively. Then the proposed methods are applied for solving multi attribute decision making problems. Finally, a numerical example is solved to show the feasibility, applicability and effectiveness of the proposed strategies

New Trends in Neutrosophic Theory and Applications Volume II

Neutrosophic set has been derived from a new branch of philosophy, namely Neutrosophy. Neutrosophic set is capable of dealing with uncertainty, indeterminacy and inconsistent information. Neutrosophic set approaches are suitable to modeling problems with uncertainty, indeterminacy and inconsistent information in which human knowledge is necessary, and human evaluation is needed. Neutrosophic set theory was proposed in 1998 by Florentin Smarandache, who also developed the concept of single valued neutrosophic set, oriented towards real world scientific and engineering applications. Since then, the single valued neutrosophic set theory has been extensively studied in books and monographs introducing neutrosophic sets and its applications, by many authors around the world. Also, an international journal - Neutrosophic Sets and Systems started its journey in 2013. Single valued neutrosophic sets have found their way into several hybrid systems, such as neutrosophic soft set, rough neutrosophic set, neutrosophic bipolar set, neutrosophic expert set, rough bipolar neutrosophic set, neutrosophic hesitant fuzzy set, etc. Successful applications of single valued neutrosophic sets have been developed in multiple criteria and multiple attribute decision making. This second volume collects original research and application papers from different perspectives covering different areas of neutrosophic studies, such as decision making, graph theory, image processing, probability theory, topology, and some theoretical papers. This volume contains four sections: DECISION MAKING, NEUTROSOPHIC GRAPH THEORY, IMAGE PROCESSING, ALGEBRA AND OTHER PAPERS. First paper (Pu Ji, Peng-fei Cheng, Hongyu Zhang, Jianqiang Wang. Interval valued neutrosophic Bonferroni mean operators and the application in the selection of renewable energy) aims to construct selection approaches for renewable energy considering the interrelationships among criteria. To do that, Bonferroni mean (BM) and geometric BM (GBM) are employed