The notion of bipolar neutrosophic finite switchboard state machines (BNFSSTMs), homomorphisms and strong homomorphisms of bipolar neutrosophic finite state machines (BNFSSTMs) are introduced and some related results are studied.
Read MoreDoi: https://doi.org/10.54216/IJNS.210204
Vol. 21 Issue. 2 PP. 59-70, (2023)
The current study presents a new concept of sets and called fuzzy neutrosophic weakly generalized M-closed and fuzzy neutrosophic strongly M-generalized closed sets in fuzzy neutrosophic topological space. Actually, this study is an extended form of a research conducted by Z.A. Khalaf, F. M. Mohammed [1]. Moreover, it presents certain related relations of these notions as well as some theorems, propositions with some necessary examples.
Read MoreDoi: https://doi.org/10.54216/IJNS.210201
Vol. 21 Issue. 2 PP. 08-19, (2023)
In this article, we discuss various Inverses Minimum norm g-inverse, Least square g-inverse, Moore Penrose inverse, Group Inverse, Generalized Symmetric Neutrosophic Fuzzy Matrices. Also we describes secondary k-column symmetric Neutrosophic fuzzy matrices are produced. It is discussed how s-k-column symmetric, s-column symmetric, k-column symmetric, and column symmetric Neutrosophic fuzzy matrices relate to one another. For an Neutrosophic fuzzy matrices to be an s-k-column symmetric Neutrosophic fuzzy matrices, necessary and sufficient requirements are identified.
Read MoreDoi: https://doi.org/10.54216/IJNS.210202
Vol. 21 Issue. 2 PP. 20-31, (2023)
maps, fuzzy hypersoft pre open maps, fuzzy hypersoft δ open maps, fuzzy hypersoft δ pre open maps, fuzzy hypersoft δ semi open maps, fuzzy hypersoft e open maps, fuzzy hypersoft δα open maps, fuzzy hypersoft e∗ open maps and their respective closed maps in fuzzy hypersoft topological spaces. Also, we have discussed the properties of various forms of fuzzy hypersoft open and closed maps. Moreover, a new cotangent similarity measure for fuzzy hypersoft sets is introduced and an application in Covid-19 diagnosis is explained with an example.
Read MoreDoi: https://doi.org/10.54216/IJNS.210203
Vol. 21 Issue. 2 PP. 32-58, (2023)
The main aim of this paper is to present a few characteristics of the neutrosophic filter of BL-algebras. Also, we introduce the notion of the neutrosophic fantastic filter of BL-algebras with an illustration and discuss a few of its properties. Moreover, we prove every neutrosophic fantastic filter is a neutrosophic filter in BL-algebras. Finally, we acquire an extension property and equivalent condition of the neurosophic fantastic filter of BL-algebras.
Read MoreDoi: https://doi.org/10.54216/IJNS.210205
Vol. 21 Issue. 2 PP. 59-67, (2023)
Heart disease, often known as cardiovascular illness, encompasses a broad range of heart-related disorders and has emerged as the leading cause of mortality during the last few decades everywhere in the globe. Numerous hazards are linked to cardiovascular disease, and timely, effective, and practical methods for making an early diagnosis are required for effective and efficient treatment. In this study, we describe a novel clustering technique for data that is unreliable clustering called neutrosophic c-means (NCM), which draws inspiration from both fuzzy c-means and the neutrosophic set architecture. The NCM is used to predict heart disease. There are four different databases included in the collection, all of which were created in 1988: Cleveland, Hungary, Switzerland, and Long Beach V. There are 76 qualities total, such as the anticipated characteristic, however only 14 have been used in any of the published trials.
Read MoreDoi: https://doi.org/10.54216/IJNS.210206
Vol. 21 Issue. 2 PP. 68-74, (2023)
Because of its far-reaching effects, diabetes remains a major health problem on a worldwide scale. It's a metabolic illness that causes hyperglycemia and a host of other health issues, including cardiovascular disease, renal failure, and neuropathy. Many scientists have spent time and energy over the years trying to develop a reliable diabetes prediction model. Researchers are forced to adopt big data analytics and machine learning (ML)-based methodologies since there are still major open research concerns in this area owing to a lack of acceptable data sets and prediction techniques. This study seeks solutions by way of an examination of healthcare predictive analytics. The major purpose of this research was to explore the potential applications of big data analytics and machine learning-based approaches in the field of diabetes. In this study, we used the neutrosophic AHP as a feature selection method. The neutrosophic AHP is used to compute the importance of features, then apply the machine learning methods to these features. This study applied logistic regression, support vector machine (SVM), and random forest (RF) to predict the disease of diabetes.
Read MoreDoi: https://doi.org/10.54216/IJNS.210207
Vol. 21 Issue. 2 PP. 75-83, (2023)
The MBJ-Neutrosophic positive implicative LI-ideals, the MBJ-Neutrosophic associative LI-ideals, and the MBJ-Neutrosophic fantastic LI-ideals are all introduced in this study. Of all these ideals, several their qualities and corresponding conditions were explored. We have demonstrated how every positive implicative MBJ-Neutrosophic LI-ideal evolved into an MBJ-Neutrosophic LI-ideal, MBJ-Neutrosophic implicative LI-ideal, and MBJ-Neutrosophic fantastic LI-ideal. Additionally, it was demonstrated that any MBJ-Neutrosophic fantastic LI-ideal is a MBJ-Neutrosophic associative LI-ideal.
Read MoreDoi: https://doi.org/10.54216/IJNS.210208
Vol. 21 Issue. 2 PP. 84-97, (2023)
Given the importance of suppliers to the overall viability and effectiveness of a supply chain, the assessment and choice of suppliers is a popular topic of research. Thus, in today's global climate, businesses must develop a methodical approach to evaluating and selecting the most suitable supplier based on their standards. To meet this need, businesses might turn to multi-criteria decision-making (MCDM) techniques, since deciding on a reliable provider is fundamentally an MCDM challenge. Although many examples of using these strategies for supplier assessment and choice can be found in the published literature, not enough research has been conducted on their effectiveness in the healthcare industry. In the healthcare industry, hospitals must also think about supplier-related choices to lessen hazards and threads that impact their efficacy. The VIKOR technique, which is focused on the development of a compromising answer within the context of options and assessment standards, yields excellent outcomes in situations requiring the consideration of numerous factors simultaneously. Numerous studies have shown that neutrosophic numbers actively aid in the process of making decisions. Suppliers in healthcare alternatives selection is a challenge that has been solved by the presented technique.
Read MoreDoi: https://doi.org/10.54216/IJNS.210209
Vol. 21 Issue. 2 PP. 98-106, (2023)
The aim of this paper is to analyze how economic growth and fiscal policy impact on poverty rate in Uzbekistan. To reach this aim neutrosophic-AHP method was applied together with two time series models, namely Autoregressive Distributed Lags (ARDL) and Vector Autoregression (VAR) models. The statistical data of Uzbekistan over the period of 2000-2021 was used. Neutrosophic-AHP served as a basis for time series analysis. In accordance with AIC and BIC criteria, VAR was chosen as the most adequate model. Results of VAR model showed that a poverty rate has a delay effect on two years, when the increase of the second lag of poverty difference by one unit also increased current poverty difference by 0.501 units. Also, it was revealed that economic growth affects poverty adversely with delay in one lag, whereas taxes – with two lags. Interesting situation occurred with government expenditures, which impacted negatively on poverty after a one-year lag, but positively after two lags.
Read MoreDoi: https://doi.org/10.54216/IJNS.210210
Vol. 21 Issue. 2 PP. 107-117, (2023)
The third most common disease worldwide, colorectal cancer (CRC) is responsible for around 10% of annual cancer diagnoses. The success of personalized treatment hinges on the ability to recognize biomarkers linked with CRC longevity and forecast the prognosis of CRC patients. The goal of this research is to provide a novel approach to doing multi-attribute colorectal cancer analysis by using machine learning algorithms with multi-criteria decision-making (MCDM) methods and neutrosophic set (NS). The NS is used to overcome the uncertainty in the dataset. This paper used the neutrosophic AHP method to get the weights of features in the used dataset. Then the machine learning algorithms are used to give analysis and prediction of colorectal cancer. The decision tree (DT) and support vector machine (SVM) is used to analyze and predict colorectal cancer. The dataset has nine features like age, gender, dukes stage, location, and Disease-free survival. This paper shows the analysis of the dataset and the correlation among the features.
Read MoreDoi: https://doi.org/10.54216/IJNS.210211
Vol. 21 Issue. 2 PP. 118-128, (2023)
This study proposes a methodology that integrates the Pythagorean Neutrosophic Set (PNS) with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach. This integration is intended to effectively handle the challenges of uncertainty and linguistic vagueness that are commonly encountered in multi-criteria decision-making scenarios. The PNS-DEMATEL framework comprises eight distinct steps, wherein the fundamental divergence lies in the creation of a linguistic variable within the PNS-DEMATEL framework. The linguistic variable has been formulated utilizing the PNS methodology, thereby enabling a more all-encompassing depiction of the viewpoints of experts. The application of the 7-point linguistic scale is utilized to acquire evaluations from experts, resulting in heightened precision and discernment. The method that has been put forth aims to improve the representation and management of linguistic variables, thereby enhancing the usability and validity of the model. The verification of the linguistic variable's validity is achieved by ensuring that the conditions outlined for the PNS are met. The integration of PNS with DEMATEL can facilitate the exploration of causal relationships in the barriers to halal certification. This approach can provide decision-makers with a more comprehensive and accurate representation of their opinions and judgements, leading to improved effectiveness in decision-making across various application domains.
Read MoreDoi: https://doi.org/10.54216/IJNS.210212
Vol. 21 Issue. 2 PP. 129-141, (2023)
Supply Chain Management (SCM) plays a critical role in the success of any business organization. Individuals involved in business activities often have to make decisions regarding different aspects of the supply chain, including planning, procurement, production, inventory management, transportation, distribution, and customer relationship management. The combination of neutrosophic logic and machine learning has gained significant attention in the field of SCM as a means to tackle uncertainties and improve decision-making. This paper highlights the potential benefits and applications of integrating neutrosophic reasoning and machine learning in SCM. Neutrosophic reasoning provides a framework for handling imprecise and uncertain information, while machine learning techniques offer powerful tools for data analysis, pattern recognition, and predictive modeling. By leveraging machine learning algorithms within the context of neutrosophic logic, SCM practitioners can enhance demand forecasting accuracy, optimize inventory management, improve transportation and routing decisions, and strengthen supply chain collaboration. The integration of neutrosophic logic and machine learning enables the handling of complex supply chain data, accommodates dynamic and uncertain environments, and supports proactive decision-making. Furthermore, the combination of these approaches can contribute to improved supply chain resilience, sustainability, and customer satisfaction. This paper applied the neutrosophic AHP method as a feature section to select the highest importance criteria as an input to machine learning. Then we applied two machine learning models named random forest and decision. The results show the random forest has the highest accuracy followed by a decision tree.
Read MoreDoi: https://doi.org/10.54216/IJNS.210213
Vol. 21 Issue. 2 PP. 142-160, (2023)
This study examines the effect of social media marketing activities on passenger retention through brand image in the airline industry in the case of Fly Emirates. The survey included a sample of his 758 passengers traveling to Dubai from destinations around the world. The questionnaire was randomly distributed, and data was collected and returned from his 455 passengers. The purpose of this study is to examine the effect of social media marketing activities (trendiness, entertainment, interaction, word of mouth, and customization) on passenger retention through mediated brand image. This study applies structural equation modeling (PLS-SEM) to investigate the relationship among the constructs in the proposed model. These aspects are modeled using the neutrosophic decision-making trial and evaluation laboratory (DEMATEL) approach. The DEMATEL models the fuzziness related to domain specialists generating judgments inside the DEMATEL as single-valued neutrosophic numbers, while also handling the causal linkages among elements of social media marketing activities. The study concludes that all dimensions of social media marketing activities (trendiness, entertainment, interaction, word of mouth, and customization) have a positive effect on brand image. The findings also confirmed that brand image plays a mediation role between social media and passenger retention, with a positive brand image being associated with increased passenger retention. The study found that without effective social media marketing, Fly Emirates loses passengers, and brand image is a key driver of passenger retention. The study recommends that Fly Emirates, looking to improve passenger retention, invest heavily in attractive social media marketing activities in the marketing innovation segment.
Read MoreDoi: https://doi.org/10.54216/IJNS.210214
Vol. 21 Issue. 2 PP. 161-176, (2023)
In general, companies are investing a lot of energy and time in conserving the quality of the products. The customers use the attribute of quality as the measuring index of the efficiency of these companies. Quality sustenance is not a phase, but it is a process which must be carried out till the product reaches the end consumer. This is possible by expanding the mechanisms of quality conservation to the spheres of product distribution in addition to product production. In view of it, this research work develops an inventory model with the idea of rework warehouse for the first time. The model formulated in this paper is discussed in a crisp sense and later extended to neutrosophic environments with the intention of making it more accommodative to various business constraints. The numerical example presented in this paper substantiates the proposed model with the application of Particle Swarm optimization. Sensitivity analysis is made with modifications with the changes of crisp and neutrosophic parameters. The model introduced in this work supports decision makers in deriving optimal solutions to the inventory problem associated with quality constraints and this work shall also be extended with the inclusion of other cost parameters, assumptions and constraints associated with product distribution.
Read MoreDoi: https://doi.org/10.54216/IJNS.210215
Vol. 21 Issue. 2 PP. 177-195, (2023)
An unobservable fluid queuing model with alternately occurring on and off states is being examined in this study. The sojourn times differ from one another and are dispersed in a distribution that is exponential. Flow of fluid into the buffer's system accompanied by a few waiting procedures according to the first service is given to those who come first. In a neutrosophic fuzzy environment, the information acquired when the fluid enters the system can be split into fully and partially observable cases. The arrival and outflow rates are both neutrosophic trapezoidal fuzzy numbers. We calculate the average fluid level and sojourn duration per unit of time for the buffer.
Read MoreDoi: https://doi.org/10.54216/IJNS.210216
Vol. 21 Issue. 2 PP. 196-203, (2023)
Leaders at hotels are keen to learn how to improve staff adherence to their newly implemented information security rules in the wake of a spate of events involving the compromise of sensitive customer data. In this research, we analyze the relationship between workers' compliance intentions and their perceptions of deterrence, and the leadership styles of their bosses. Gender, education, role, tenure based on ethical leadership, and information security policy compliance intention were some of the particular leadership aspects connected to the information security policy that were evaluated in our research. The overall relevance of the standards may be calculated using the average method, which is used in decision-making. The suggested novel version of the MULTIMOORA (Multi-objective Optimization by Ratio Analysis Plus Full Multiplicative Form) approach uses a single-valued neutrosophic set to handle directly with the uncertainty of the starting point. Developing a decision-support system that takes into account the new conceptual composite framework we offer for selecting criteria, alternatives, and other aspects of leadership and information security policy in hotels is a feasible next step.
Read MoreDoi: https://doi.org/10.54216/IJNS.210217
Vol. 21 Issue. 2 PP. 204-215, (2023)
The inverse power Lindley distribution is employed in the realm of survival analysis to imitate human lifetime data practices. The neutrosophic inverse power Lindley distribution (NIPLD) is intended to characterize a variety of survival data with indeterminacies. The established distribution is particularly useful for modeling uncertain data that is roughly positively skewed. This work discusses the key statistical properties of the developed NIPLD, including the neutrosophic survival function, neutrosophic hazard rate, and neutrosophic moments. In addition, the neutrosophic parameters are estimated using the well-known maximum likelihood estimation approach. To find out if the predicted neutrosophic parameters were reached, a simulation study is done. Not to mention, actual data has been utilized to discuss potential NIPLD real-world applications. Real data were used to illustrate how well the proposed model performed in compared to the current distributions.
Read MoreDoi: https://doi.org/10.54216/IJNS.210218
Vol. 21 Issue. 2 PP. 216-223, (2023)