Neutrosophic TOPSIS for prioritization Social Responsibility Projects

S. Alvarez; P. P. Jairo; L. Vázquez

doi:https://doi.org/10.54216/IJNS.190132

International Journal of Neutrosophic Science | 2022

Neutrosophic Cognitive Maps for Violence Cause Analysis

Among the most valuable AI methods for modeling complicated things at the moment is the use of fuzzy cognitive mapping (FCMs). Conventional FCMs, on the other hand, can't handle the ambiguity that often arises in decision-making scenarios. A novel expansion of conventional FCMs called neutrosophic cognitive mapping (NCMs) was developed to address this shortcoming. However, the indeterminacy is not well handled by the NCMs stated in the citations since the level of indeterminacy is not quantified. In certain cases, choices should be seen as a series of steps that are only loosely related to one another. This occurs in project assessment when several activities depend on one another. Another difficult aspect of FCMs is that there isn't an appropriate topology for representing these types of decision-making difficulties. To aid in making decisions over several time periods, this research introduces a neutrosophic cognitive map built on triangular neutrosophic values (MS-TrNCM) for violence analysis. Through the use of triangular neutrosophic numbers, the suggested model allows experts to express their choices while considering various extents of truth, indeterminacy, and falsity in the underlying map linkages.

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H. E. Lozano Rojas mail -

F. Sánchez Nelson mail -

Mendez Cabrita Marina mail

link https://doi.org/10.54216/IJNS.190128

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2022

A Novel Approach on Neutrosophic Binary αgs Neighborhood Points and its Operators

The main idea of this paper is to introduce neutrosophic binary αgs-neighborhood points and neutrosophic binary αgs interior and closure operators. Furthermore, some of its properties are contemplated.

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Surekha S. S mail -

Sindhu G mail -

broumi said mail

link https://doi.org/10.54216/IJNS.190127

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

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American Journal of Business and Operations Research | 2022

Statistical Machine Learning Model and Commodity Futures Volatility Information for Financial Stock Market Forecasting

A country's economy and social structure are greatly influenced by the stock market. It is extremely difficult for investors, expert analysts, and scholars in the financial industry to forecast the stock market accurately because of the pretty unstable, parametric, non-linear dynamical, and unstable character of stock price time series. In the financial sector, stock market forecasting is a critical activity and a prominent study subject because stock market investments carry greater risk. It's conceivable, however, to reduce most of the risk through the development of computationally intelligent approaches. This paper introduces the support vector machine regression to make a model forecasting the stock market financial.

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Denis A. Pustokhin mail -

Irina V. Pustokhina mail

link https://doi.org/10.54216/AJBOR.070203

Volume & Issue

Vol. Volume 7 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2022

New Entropy Measure Concept for Single Value Neutrosophic Sets with Application in Medical Diagnosis

This study aims to propose a new entropy weight on the distance measure of single value neutrosophic set (SVNS) to analyse medical diagnosis patient’s risk. Four distance measures will be integrated with three entropy weight concepts and applied to medical diagnosis. A new entropy weight measure integrated with the four distance measures are calculated using the medical data of one patient with five symptoms and five diseases. The calculated new entropy and its associated distance measures give consistent finding with the existing entropy weight measures. However, all the values are even smaller showing that the relation between patient A and disease are stronger. This evaluation and diagnosis approach is applicable to a wide variety of other resources and medical problems.

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Norzieha Mustapha mail -

Suriana Alias mail -

Roliza Md Yasin mail -

Nurnisa Nasuha Mohd Yusof mail -

Nurul Najiha Fakhrarazi mail -

Nik Nur Aisyah Nik Hassan mail

link https://doi.org/10.54216/IJNS.190118

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

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Fusion: Practice and Applications | 2022

Potential Energy Efficient Data Fusion Model for Wireless Sensor Networks

Wireless sensor networks have made a significant contribution to wireless sensor communication system based on resource constraints and limited computational sensors. Over the last decade, several focused research efforts have been made to investigate and provide solutions to problems relating to the energy efficiency data fusion aggregation in Wireless sensor networks. However, the problem of designing routes that are energy efficient has not been resolved. It is rather a tough effort to guarantee that the lifespan of a sensor is prolonged for a longer period because of the restricted computational capabilities of sensors, which are often coupled with energy constraints. The findings of this work present an enhanced energy-efficient technique for communication in sensor networks which consists of three distinct innovative frameworks. The suggested framework known as Data Fusion with Potential Energy Efficiency (DFWPEE) is responsible for the optimization of energy. The proposed work reduces energy consumption by using probabilistic methods and clustering. During the data fusion process, the Multiple Zone Data Fusion (MZDF) architecture uses a globular topology that helps with load balancing. The strategy presents an innovative routing approach that is used to aid in the performance of energy efficient routing in large-scale wireless sensor networks. By introducing the idea of routing agents, the framework for the Tree-Based Fusion Technique (TBFT), as suggested, comes up with an innovative method for dynamic reconfiguration. The plan enables the system to determine which sensor has a higher rate of energy dissipation and then immediately transfers the job of data fusion to a node that is more energy efficient. This threshold-based technique enables a sensor to perform both the role of a cluster head and the function of a member node. The node behaves as a cluster head until it achieves its threshold remnant energy and functions as a member node after it passes the threshold residual energy. Both of these roles may be played simultaneously. The mathematical modeling was done using the conventional radio energy model which improved the dependability of attained results. The proposed system delivers enhanced energy efficient communication performance when measured against existing implemented standards for energy efficient schemes.  The enhanced technique uses nearly half as much energy as LEACH while focusing on reducing the overall time taken for the process to complete leading to enhanced performance.

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Rajeev Pandey mail -

Manoj Kumar mail -

Jaswant Samar mail

link https://doi.org/10.54216/FPA.080204

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2022

Neutrosophic cognitive maps for analysis of social problems analysis

Investors have been flocking to the information technology (IT) industry recently. Any commercial or IT company's success is directly proportional to its employees' efforts. The workforce's contributions are crucial when it comes to the success of technology or any other business on the global stage. However, they will disregard their personal and social lives to achieve their aim. Workers in the private sector, particularly those in the information technology industry, suffer from mental health issues such as stress, depression, anxiety, and addiction. Using Neutrosophic Cognitive Maps (NCM), we evaluated the daily problem they face. The NCM decision-making system incorporates iterative tasks of resolving conflicts until the optimal answer is reached. The NCM uses neutrosophic graphs to model depending on the opinions of experts. Studying the issue with such vague data calls for an approach such as this, which eschews the use of statistics. For unlabeled data, NCM is the most effective method.

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V. B. Frantz Dimitri mail -

M. G. Teresa De Jesús mail -

P. A. Edmundo Enrique mail

link https://doi.org/10.54216/IJNS.190129

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

Fusion: Practice and Applications | 2022

Multi-Sensor Data Fusion for Target Tracking Using Machine Learning Techniques

Target detection using multi fusion data is one of the common techniques used in military as well as defence units. The usage of a wide variety of sensors is now possible due to modern data fusion technology. The major problem is the existing multi-sensor fusion technique is loss of data and delay is message transfer. To overcome the existing problems, proposed work includes optimization, machine learning, and soft computing techniques. Multi Sensor Data Fusion (MSDF) is becoming an increasingly significant field of study and is being explored by a broad range of individuals. Data defects, outliers, misleading data, conflicting data, and data association are some data fusion concerns. In addition to the statistical advantages of more independent observations, the precision of an observation may be improved by using a variety of different types of sensors. Target tracking has earned a lot of attention in recent years in the realm of surveillance and measurement systems, particularly those in which the state of a target is approximated based on measurements. Academics as well as implementers in the fields of radar, sonar, and satellite surveillance are interested in the bearings-only tracking (BOT) problem. The BOT is the sole option available in many surveillance systems, such as those found aboard submarines. Significant difficulties arise because of the constrained observability of target states based only on bearing measurements. The work that is suggested tackles the limitations of EKF and its derivatives in controlling MSDF within the context of BOT. Specifically, the study identifies divergence as a primary challenge and works to devise solutions for it. It is recommended that two key methods of fusion, data level and feature level (or state level), be investigated in depth. This is in recognition of the fact that the MSDF may increase observability, thereby reducing the tendency of the tracking algorithm to diverge and realizing a better estimate of the states. The Information Filter, which is a casting of the Kalman Filter, and its expansions are employed via extensive simulation to lessen the influence of initial assumptions on the convergence of MSDF tracking algorithms. This is accomplished by using the Kalman Filter.

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A. Audumbar Pise mail -

Radhika Kapshikar mail

link https://doi.org/10.54216/FPA.080205

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2022

The NILPOTENT Characterization of the finite neutrosophic p-groups

A well known and referenced global result is the nilpotent characterisation of the finite p-groups. This undoubtedly transends into neutrosophy. Hence, this fact of the neutrosophic nilpotent p-groups is worth critical studying and comprehensive analysis. The nilpotent characterisation depicts that there exists a derived series (Lower Central) which must terminate at {ϵ} ( an identity ) , after a finite number of steps. Now, Suppose that G(I) is a neutrosophic p-group of class at least m ≥ 3. We show in this paper that Lm−1(G(I)) is abelian and hence G(I) possesses a characteristic abelian neutrosophic subgroup which is not supposed to be contained in Z(G(I)). Furthermore, If L3(G(I)) = 1 such that pm is the highest order of an element of G(I)/L2(G(I)) (where G(I) is any neutrosophic p-group) then no element of L2(G(I)) has an order higher than pm.

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S. A. Adebisi mail -

Florentin Smarandache mail

link https://doi.org/10.54216/IJNS.190134

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2022

The Representation of Refined Neutrosophic Matrices By Refined Neutrosophic Linear Functions

The aim of this paper is to solve the problem of representing refined neutrosophic matrices by linear functions, where it describes the structure of refined neutrosophic linear transformations that represent refined neutrosophic matrices. On the other hand, this work introduces a novel algorithm to compute a basis of any refined neutrosophic vector space depending on the classical basis of its corresponding classical vector space.

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Mohammad Abobala mail -

M. Bisher Ziena mail -

R. Iqbal Doewes mail -

Zahraa Hussein mail

link https://doi.org/10.54216/IJNS.190131

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

Neutrosophic TOPSIS for prioritization Social Responsibility Projects

Social responsibility is the most important thing to consider while working on a project. When deciding on a project or taking part in a bid, it is crucial to understand the nature and potential consequences of the risks involved. Attempting to implement projects with cutting-edge technologies appears to be necessary, necessitating up-to-date and continuous planning to implement the relevant matters in light of the ever-increasing growth of urban communities, the need to carry out tasks, and the rising standard of living. Due to the strong demand, these strategies try to improve quality while decreasing prices. In the beginning, Smarandache suggests using neutrosophic sets. These sets are an improvement above traditional fuzzy set theory in reflecting the uncertainty and fuzziness of real-world issues. Three decision-making states are considered: uncertainty, truthiness, and falseness. The fuzzy set degree in Zadeh's classic theory is merely the membership function. On the other hand, three membership functions are considered in a neutrosophic setting. An indeterminacy degree is considered, which is not the case with intuitionistic fuzzy sets. To express decision makers' perspectives on the truthiness (T), falsity (F), and indeterminacy (I) for a fuzzy set concurrently, this paper expands the usual neutrosophic TOPSIS approach to interval-valued neutrosophic. One example of how the suggested strategy might be put to use is to prioritize initiatives in the realm of corporate social responsibility using a combination of expert opinion and objective criteria.

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S. Alvarez Hernandez mail -

P. P. Jairo Mauricio mail -

L. Vázquez Maikel mail

link https://doi.org/10.54216/IJNS.190132

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new