This paper is concerned with studying symbolic m-plithogenic vector spaces with finite orders between 6 and 10, where it defines and characterizes the AH-subspaces, AH-kernels, and AH- linear transformations in five different symbolic m-plithogenic spaces (6-plithogenic, 7-plithogenic,10-plithogenic vector spaces). Also, we prove many theorems that describe the computation of the kernels and direct images of the plithogenic AH-linear transformations.
Read MoreDoi: https://doi.org/10.54216/IJNS.240322
Vol. 24 Issue. 3 PP. 258-267, (2024)
The widespread dissemination of World Wide Web has paved the way to express individual sentiments. Also, it is a medium with a massive quantity of data where the user can view the opinions of other users that are categorized into dissimilar sentimental classes and are growing increasingly as a major aspect in decision making. Sentiment analysis (SA) is a method utilized in natural language processing (NLP) that defines the emotion or sentiment formulated in the text portion. SA method is often performed on text datasets to assist in accepting client requirements, businesses monitoring brands, and product sentiment in customer feedback. SA is the challenging and most common complication in artificial intelligence (AI). It applies automated mechanisms to identify physiological information namely feelings, thoughts, and attitudes shown in text and indicated through blogs, social networks, and news. This manuscript develops Applied Linguistics driven Artificial Intelligence for Automated Sentiment Detection and Classification (ALAI-ASDC) technique. The preprocessing stage includes tokenizing and cleaning textual information, followed by encoder words into vector representation using pretrained GloVe embeddings. This embedding captures semantic similarities between words, which provides an abundant depiction of textual information for SA. Integrating single-valued neutrosophic fuzzy soft expert set (SVNFSES) improves the SA method by addressing imprecision, uncertainty, and ambiguity inherent in text sentiment expression. FNS enables the representation of linguistic variables with degrees of truth, falsity, and indeterminacy, allowing a nuanced understanding of sentiment polarity. Moreover, the Hybrid Jelly Particle Swarm Optimization (HJPSO) is applied for the parameter tuning of the SA technique. Enhancing the performance of the SA model. Empirical analysis illustrates the efficiency of the presented technique in precisely categorizing sentiment polarity in different textual datasets
Read MoreDoi: https://doi.org/10.54216/IJNS.240301
Vol. 24 Issue. 3 PP. 08-20, (2024)
Enterprise Resource Planning (ERP) is paramount in modern business, integrating many fundamental processes such as human resources, economics, customer relationship management, and supply chain management into a comprehensive infrastructure. Leveraging the wide-ranging data apprehended by ERP techniques, an organization could improve its financial analysis abilities, involving bankruptcy prediction. By using analytics methods like predictive modeling and machine learning, the ERP system could examine market trends, historical financial information, key performance indicators, and other related factors to evaluate the financial stability and health of the company. This prediction insight empowers businesses to vigorously detect advanced indicators of financial distress, alleviate risks, and make informed strategic decisions to avoid bankruptcy. Integrating bankruptcy prediction techniques within the ERP system allows organizations to reinforce contingency strategies, financial planning, and risk management, protecting long-term competitiveness and sustainability in a dynamic business environment. This study introduces a Bankruptcy Prediction using the Diophantine Neutrosophic Number for Enterprise Resource Planning (BPDNN-ERP) technique on the value of accounting information. The BPDNN-ERP technique begins with a harmony search algorithm (HSA) for electing feature subsets. In addition, the BPDNN-ERP technique applies the DNN model for the prediction of bankruptcies. To increase the performance of the DNN model, the manta ray foraging optimization (MRFO) model can be used. The experimental study demonstrated the enhanced performance of the BPDNN-ERP algorithm equated to existing forecasting methods
Read MoreDoi: https://doi.org/10.54216/IJNS.240302
Vol. 24 Issue. 3 PP. 21-33, (2024)
Neutrosophic logic is founded on non-standard evaluation. In neutrosophic set (NS), the computation of indefiniteness is explicit, while the membership of truth, falsity, and indeterminacy are non-reliable. Recently, various attractive game theory application is extended by entrenching the fuzzy set logic. The accounting data analysis has to contribute the innovativeness. This includes various characteristics. It applies billions of individuals in the business to develop and design novel products until the sale managing of the enormous sales staff. While cloud storage provides flexibility and scalability, it also comes with related costs, involving data transfer fees, subscription fees, and storage costs. Optimizing and managing cloud storage costs associated with business needs and budgetary constraints is crucial. Cloud-based AIS decreases the necessity for localized infrastructure and hardware, oscillating rate from capital to operational expenditure. This enables organizations to pay only for the used resource, resulting in economic efficiencies. Incorporating cloud technology into accounting information systems (AIS) provides several advantages. To increase the capability of accounting data statistics and analysis, this article introduces an N‐person intuitionistic neutrosophic soft game with Neutrosophic Cognitive Maps (NINSG-NCM) for cloud storage with AIS. The NINSG-NCM technique considered a contemporary accounting data analysis is built based on the block bit sequence evaluation technique and extracts the association rule representative amount of accounting data. Integrated with cloud computing (CC) framework, the NINSG-NCM method is proposed, and the NCM clustering technique is used for realizing the modern accounting data clustering, and the NINSG method could enhance the capability of statistical analysis and parallel computing of accounting data. Lastly, salp swarm algorithm (SSA) is applied for hyperparameter tuning method. The experimental outcomes illustrate that the designed intelligent data evaluation technique makes the parallel computing efficacy high and the statistical evaluation capability of accounting data better.
Read MoreDoi: https://doi.org/10.54216/IJNS.240303
Vol. 24 Issue. 3 PP. 34-44, (2024)
Game theory is more popular in competitive situations due to its importance in decision making. Several kinds of fuzzy sets can manage uncertainty in matrix games. Neutrosophic set theory has been instrumental in investigating ambiguity, complexity, inconsistency, and incompleteness in real-time issues. Nowadays, sarcastic comments on social media have become a general tendency. Sarcasm is frequently used by individuals to pester or taunt others. It is often conveyed via inflection, tonal stress in speech, or lexical, hyperbolic, and pragmatic features existing in the text. Sentiment Analysis (SA) is regarded as the data mining targets of sentiment organization of the client's criticisms obtainable in textual form. Sarcasm is a form of speech that states an individual's downside feeling through a positive term. Labeling sarcasm in characters is a dynamic task for Natural Language Processing to evade the misconception of sarcastic speeches as a verbatim declaration. The outcome of these kinds of sarcastic speeches is hard for the people and machines. Sarcasm has a considerable influence on the efficacy of SA techniques that are impacted by mendacious sentiments that frequently belong to sarcastic classes. This study introduces an Interval-valued Fermatean Neutrosophic Graph with Grey Wolf Optimization for Sentiment Analysis (IFeNG-GWOSA) on Microblogging Data. The IFeNG-GWOSA technique includes a sarcasm detection technique that categorizes words in sarcastic or non-sarcastic form. The initial phase is preprocessing, where the tokenization and stop word removal are implemented. Then, the preprocessed data is subjected to feature extraction, where the BERT word embedding is applied. The IFeNG model is used for sarcasm detection, and the grey wolf optimizer (GWO) generates its parameter selection technique. Lastly, the efficiency of the presented technique is compared with existing approaches under different measures
Read MoreDoi: https://doi.org/10.54216/IJNS.240304
Vol. 24 Issue. 3 PP. 45-55, (2024)
Inventory management is characterized by a continuous struggle to lower goods levels and related costs while also providing customers with the goods they need. However, reducing costs while simultaneously striving for ideal inventory levels is difficult, notably in the current situation of high unpredictability of goods demand and lead time. Traditional inventory models are not strong enough to endure changes like goods demand and lead-time demand. As a result, it must be adjusted to achieve results. The oeuvre below presents a new kind of inventory model that deals with uncertainty in the demand for goods and lead time. In this regard, the presented work, the novel Neutrosophic Economic Order Quantity approach is a mechanism to account for the likely imprecision in the model. Specifically, the Neutrosophic set theory is integrated into the EOQ model so that it can handle variations in the demand and lead-time pattern successfully. An objective function is established for obtaining economical order quantities that include demand, lead-time, and other necessary components’ irregularities. The process variables in the model are given the final values using genetic algorithms and simulated annealing. To highlight the impact of the proposed Neutrosophic approach, it is then applied to several realistic examples. This will provide the audience a sense of how effective inventory management may be in high-uncertainty situations. The rapid evolution of organizations necessitates innovative inventory control tactics to meet growing demands
Read MoreDoi: https://doi.org/10.54216/IJNS.240305
Vol. 24 Issue. 3 PP. 56-64, (2024)
In actual life, dealing with uncertain information has become a challenge for researchers who strive day after day to develop more accurate mathematical tools for better dealing with this information. The Q-Fuzzy soft model can process uncertain information in two dimensions by dealing with the subjective judgments of users effectively. Therefore, this article aims to increase the effectiveness of the Q-fuzzy soft model and address the challenges of design-making under uncertain information by proposing a new model called the interval-valued Q-fuzzy soft (IV-Q-FSS) model. Under the IV-Q-FSSs, we discuss strongly set-theory operations such as subset, union of two IV-Q-FSSs, intersection of two IV-Q-FSSs, complement of IV-Q-FSS, AND operation, and OR operation for IV-Q-FSSs, and some operations like the possibility and necessity operations of an IV-Q-FSS. In addition, we hand over numerous properties held up by numerical examples that describe how they toil. Finally, this recently developed model has been successfully trying out in dealing with one of the design-making problems based on hypothetical data for a respiratory disease. This algorithm is built based on the aggregation operator for IV-Q-FSS data to break this issue (i.e., selecting the optimal alternative).
Read MoreDoi: https://doi.org/10.54216/IJNS.240306
Vol. 24 Issue. 3 PP. 65-76, (2024)
In this research work, basic concepts and properties are considered within the context of a generalized topological space (X, μ), as tools to generate a new generalized topology bμ by means of a μ-base formed by the μ-interiors of μ-closed sets. This leads to an exploration of the relationship between some of the properties of the generalized topologies μ and bμ, such as generalized separation axioms, generalized connectedness, generalized continuity, generalized topological sum, and generalized product topology.
Read MoreDoi: https://doi.org/10.54216/IJNS.240307
Vol. 24 Issue. 3 PP. 77-84, (2024)
We introduce the notion of q-neutrosophic cubic vague subbisemiring (q-NSCVSBS) and level set of q- NSCVSBS of a bisemiring. The q-NSCVSBS is a new concept of subbisemirings of bisemirings. Let X be a neutrosophic vague subset of L. Then W = ([T-, T+ ], [I-, I+ ],[F-,F+ ]) is a q-NSCVSBS of L if and only if all non-empty level set is also a SBS of L. Let X be the q-NSCVSBS of L and ¡ be the strongest cubic q-neutrosophic vague relation of L*L. Then X is a q-NSCVSBS of L* L. Let X be the q-NSCVSBS of L, show that pseudo cubic q-neutrosophic vague coset is also a q-NSCVSBS of L. Let X1, X2,….. Xn be the any family of q-NSCV SBSs of L1, L2,…., Ln respectively, then X1* X2 *….. * Xn is also a q-NSCVSBS of L1 * L2 *…. *Ln .The homomorphic image of every q-NSCVSBS is also a q-NSCVSBS. The homomorphic pre-image of every q-NSCVSBS is also a q-NSCVSBS.
Read MoreDoi: https://doi.org/10.54216/IJNS.240308
Vol. 24 Issue. 3 PP. 85-101, (2024)
This paper is dedicated to study the Invertibility properties of all plithogenic square matrices of high orders between 20 and 24, where we present the mathematical conditions and formulas for computing the inverses of all plithogenic square matrices with real plithogenic entries. This goal will be completed by proving many theorems that describe the Invertibility of all classic matrix parts of the corresponding symbolic m-plithogenic matrix.
Read MoreDoi: https://doi.org/10.54216/IJNS.240309
Vol. 24 Issue. 3 PP. 102-114, (2024)
An addition of soft set theory, Neutrosophic soft set theory offers a versatile framework for handling indeterminacy and uncertainty in data. Using this theory for the prediction of market share includes representing market data in a neutrosophic soft-set format, where elements pose truth, indeterminacy, and false degrees. The predictive model is constructed to estimate future market shares with consideration for ambiguity and uncertainty by analyzing previous market factors and trends affecting market dynamics within these frameworks. The stock market prediction pattern is interpreted as a significant action and it is more beneficial. Therefore, stock prices will result in substantial profits from sound taking choices. Thus, stock market forecasting is a main task for investors to spend their money to create maximum profit due to the noisy and stagnant data. Stock market prediction uses learning tools and mathematical strategies. Therefore, this manuscript offers the design of Financial Market Share Prediction using the Intuitionistic Possibility Fermatean Neutrosophic Soft Set (FMSP-IPFNS) technique. In the FMSP-IPFNS technique, a three-stage approach is followed. Firstly, the data normalization process is executed using a min-max scalar approach. Secondly, the prediction process can be carried out using the IPFNS approach. Thirdly, the parameter adjustment of the IPFNS approach takes place using the grasshopper optimization algorithm (GOA). To validate the performance of the FMSP-IPFNS system, a sequence of experimentations were tested. The obtained values demonstrate the promising results of the FMSP-IPFNS system compared to other models
Read MoreDoi: https://doi.org/10.54216/IJNS.240310
Vol. 24 Issue. 3 PP. 115-126, (2024)
A neutrosophic set (NS) is a new computing technology that accesses ambiguous data through three memberships. A soft expert set (SES) is based on the concept of a “soft set” with an expert system. Now, this technique has been applied in different domains namely measurement theory, intelligent systems, game theory, probability theory, cybernetics, etc. Customer Churn prediction implies identifying which consumers are expected to cancel a subscription to a service or leave a service. It is a crucial forecast for several businesses because obtaining new users frequently costs more than holding existing ones. The Churn prediction modeling methods try to understand the accurate customer attributes and behaviors that signal the risk and timing of customers leaving. This manuscript offers the design of an AI-based Multi-Dimensional Customer Churn Prediction for Corporate Performance Assessment (AIMD-CCPCPA) technique. The AIMD-CCPCPA technique mainly aims to detect the presence of customer churns and non-churns. It involves a two-stage process. At the initial stage, the AIMD-CCPCPA technique exploits the COPRAS Neutrosophic Method for prediction purposes. Secondly, the AIMD-CCPCPA technique involves parameter selection using a butterfly optimization algorithm (BOA). The experimental analysis of the AIMD-CCPCPA model is examined using a benchmark dataset. The acquired outcomes stated the supremacy of the AIMD-CCPCPA technique equated to other models
Read MoreDoi: https://doi.org/10.54216/IJNS.240311
Vol. 24 Issue. 3 PP. 127-137, (2024)
Neutrosophic set is introduced as a generalization of intuitionistic fuzzy set, where any elements x ∈ X we have membership (T), non-membership (F), and indeterminacy (I)degrees. Neurosophic vague topological spaces are presented in various notations like neurosophic vague compactness and continuity. Trademarks are the essential components of intellectual property that allow owner to earn profit based on their name. In this industry, retailers typically use feedback channels like customer care service, website review complaints and suggestions boxes to gain user reviews on service satisfaction. But, there is a gap between these techniques. Customers are not fulfilled with them due to lack of trust in management, a lack of flexibility and slow responsiveness. This has prompted examination of the effect of customer feedback channels (CFCs) on client satisfaction and the necessity to develop a new CFC using artificial intelligence (AI). Thus, this study designs a Trademark Empowerment using Optimal Neutrosophic Topological Vector Space (TE-ONTVS) technique for Maximizing Customer Attraction. The intention of the TE-ONTVS technique lies in the prediction of customer behaviour and attraction. To accomplish this, the TE-ONTVS technique undergoes data scaling using Z-score normalization. In addition, the TE-ONTVS technique uses NTVS approach for the identification of customer behaviour and attraction. Lastly, whale optimization algorithm (WOA) is applied for optimal parameter tuning of the NTVS algorithm. A series of experiments were involved to demonstrate the enhanced outcomes of the TE-ONTVS algorithm. The obtained results stated that the TE-ONTVS technique reaches optimal performance over other models
Read MoreDoi: https://doi.org/10.54216/IJNS.240312
Vol. 24 Issue. 3 PP. 138-150, (2024)
The family of neutrosophic distributions has received considerable attention from the scientific community, due to the flexible parametric form of its probability density function, in modeling many physical phenomena with imprecise information. In this study, we consider a generalization of Singh Maddala distribution for handling fuzzy data sets. This study presents a new research endeavor: quantifying the lifespan of manufacturing enterprises using the Neutrosophic Singh Maddala Distribution (NSMD). This work significantly enhances the theoretical foundations by providing novel formulations for the moments and mode of the NSMD distribution. In addition, it expands the study beyond the traditional Maddala model by examining conventional statistical models. For estimating the unknown parameters, the maximum likelihood estimation has been used in neutrosophic framework. Characterizations are obtained in terms of neutrosophic measures. The assessment of model performance, carried out using the goodness of fit criterion, highlights the superiority of NSMD compared to other models. In the application section, a real data on carbon emission is provided for usefulness of the proposed model.
Read MoreDoi: https://doi.org/10.54216/IJNS.240313
Vol. 24 Issue. 3 PP. 151-164, (2024)
In this article, homomorphism and anti-homomorphism bipolar valued multi normal fuzzy HX subgroup of a HX group is studied, discussed and their properties are introduced. The theorems presented in this article are considered a generalization of what has been publishedthrough the concept of fuzzy sets. As the concept of fuzzy sets was introduced by Zadeh in 1965, after that this concept, we expanded into more than one types, intuitionistic fuzzy set, bipolar fuzzy sets, tripolar fuzzy set, and bipolar valued multi fuzzy set are one of this.
Read MoreDoi: https://doi.org/10.54216/IJNS.240314
Vol. 24 Issue. 3 PP. 165-171, (2024)
We have new introduced two fundamental new concept that characterize partner multineutrosophic sets, the first of which we call the locally partner multineutrosophic interior and the second the locally partner fuzzy exterior, in addition to a concept related to set composition that we call detachable set, with the most important relationships to which these concept are linked and the properties that we have reached with an analytical view of them.
Read MoreDoi: https://doi.org/10.54216/IJNS.240315
Vol. 24 Issue. 3 PP. 172-178, (2024)
The created SDE-Framework combines neutronosophic logic and fuzzy mathematics in a novel method, aiming at facilitating more informed decision outcomes in computational systems and information technology management. This method hopes to aid in determining strategic solutions by controlling the expected sophistication and ambiguity in these two technologically dynamic industries. Neutronosophic logic divides data into three components: truth, indeterminacy, and falsity, build an exhaustive technique for addressing contradiction and indeterminacy. This significantly increases the method by enabling a more complete exploration of potential options with ambiguous and inadequate data. Second, the fuzzy mathematics gives a valuable contribution. It offers a refined method for managing the levels of probability and certainty through membership features, resulting in more exact and flexible evaluations. By the usage of such compared sophisticated mathematics concepts, SDE-Framework addresses potential decision-making scenarios by letting the computer formulates do the judgements for the determinable and in determinable explicit data. The subsequent crucial parameters are adopted to tolerance values: validity and responsibility, falseness foreach, indeterminacy magnitude to each, and truth value. This guarantees its combination of complexity supportive rand reading of actual surroundings.
Read MoreDoi: https://doi.org/10.54216/IJNS.240316
Vol. 24 Issue. 3 PP. 179-189, (2024)
The neutrosophic fuzzy set offers us a broad outline for combining several existing sets into one. Indeterminate and unpredictable data cannot be dealt with by either the fuzzy set theory or intuitionistic fuzzy set theory. The computing techniques of neutrosophic sets are valid for software development for many uses. The transportation problem profoundly depends on the neutrosophic fuzzy set. Most of the time, the data provided is indeterminate and inconsistent. At this point of time, we cannot make use of the fuzzy set and intutionistic fuzzy set to get deal with this indeterminacy. Here, we have solved numerically to reflect the impact of neutrosophic pentagonal numbers and neutrosophic octagonal numbers. The efficiency of the method is applied is also compared with the other methods.
Read MoreDoi: https://doi.org/10.54216/IJNS.240317
Vol. 24 Issue. 3 PP. 190-200, (2024)
The study of neutrosophy offers a fresh approach for handling uncertain data with adaptability. This article explores the application of neutrosophic probability distribution in constructing a transmuted neutrosophic framework. Specifically, it introduces a generalized transmuted neutrosophic distribution. Building upon this generalization, quadratic and cubic transmuted distributions are developed and examined alongside certain lifetime distributions serving as foundational neutrosophic models. Additionally, an empirical investigation is conducted to assess the practicality and versatility of these distributions in real-world contexts.
Read MoreDoi: https://doi.org/10.54216/IJNS.240318
Vol. 24 Issue. 3 PP. 201-219, (2024)
The purpose of this article is to present a novel approach to the (δ,ε) interval-valued neutrosophic set (IVNS). This is an extension of the IVNS. As a result of this article, we will discuss the concept of (δ,ε) interval valued neutrosophic weighted averaging (IVNWA), (δ,ε) interval-valued neutrosophic weighted geometric (IVNWG), (δ,ε) generalized interval-valued neutrosophic weighted averaging (GIVNWA) and (δ,ε) generalized interval-valued neutrosophic weighted geometric (GIVNWG). Additionally, the (δ,ε) IVNS approach is characterized by idempotency, boundedness, commutativity and monotonicity.
Read MoreDoi: https://doi.org/10.54216/IJNS.240319
Vol. 24 Issue. 3 PP. 220-232, (2024)
Uryson's operators are very famous in the theory of fuzzy functional analysis. This paper is dedicated to studying and generalizing many results about the compactness and the continuity of Uryson's operator in two-variables defined with integral equation on G with the norm ‖u‖f= sup(ρ(v,f)≤) |∫u(x)v(x)dxG | ;v(x)∈L*g ,u(x)∈Lf*. Also, we study the convergence of Urysons' sequences Kn defined with the family of functions Kn (x, y; u) by using the convergence with respect to the defined measure and Caratheodory Condition.
Read MoreDoi: https://doi.org/10.54216/IJNS.240320
Vol. 24 Issue. 3 PP. 233-239, (2024)
We introduce the concept of cosine trigonometric q-rung Diophantine neutrosophic interval-valued set (CosTq-rung DioNSIVS). The fact that CosTq-rung DioNSIVS combines q-rung neutrosophic interval-valued set, q-rung neutrosophic set and neutrosophic interval-valued set is one of its distinguishing characteristics. A new idea of CosTq-rung DioNSIVWA, CosTq-rung DioNSIVWG, GCosTq-rung DioNSIVWA and GCosTq-rung DioNSIVWG is proposed in this study. We also look at the idempotency, boundedness, commutativity, and monotonicity of the CosTq-rung DioNSIVS based on algebraic operations. We considered new kinds of two distances in the proposed models, besides Euclidean and Hamming distances. The CosTq-rung DioNSIVS method was used to analyze the cosine trigonometric aggregation procedures. The study's concluding results include several fascinating and captivating discoveries.
Read MoreDoi: https://doi.org/10.54216/IJNS.240321
Vol. 24 Issue. 3 PP. 240-257, (2024)
This study presents a novel distribution derived from the exponential distribution, referred to as the neutrosophic size-biased exponential distribution (NSBED). Various characteristics of the proposed model, including moments, skewness, and kurtosis, are investigated. Plots depicting the cumulative distribution function, density function, and other relevant functions associated with the survival analysis hazard function under indeterminacy are provided. Parameter estimates for the proposed model within the neutrosophic framework are computed. To illustrate the statistical applications of the results in handling imprecise data, a motivation is provided. A simulation analysis is conducted to validate the theoretical aspects of the proposed NSBED. Results indicate that the new distribution exhibits right skewness and shares many properties with skewed distributions. Our novel distribution outperforms the size-biased exponential distribution. Finally, a real application of the proposed model is provided to illustrate the practical implications.
Read MoreDoi: https://doi.org/10.54216/IJNS.240323
Vol. 24 Issue. 3 PP. 268-279, (2024)
This paper discusses a neutrosophic mathematical model consisting of three nonlinear ordinary differential equations describing the interaction between two prey and a predator with the use of function response Holling's type IV and Lotka Volttra. It appears that the first prey has a way to defend itself by using the toxic substance directly to the predator, as well as the effect of the predator on the toxic substance. The conditions for the existence of the solution and the uniqueness of the boundaries were discussed, and then the different equilibrium points and the stability of the system around the equilibrium points were analyzed. The Lyapunov function was used to study the global dynamics of this proposed model. Finally, numerical simulations were performed to show the analytical results.
Read MoreDoi: https://doi.org/10.54216/IJNS.240324
Vol. 24 Issue. 3 PP. 280-295, (2024)