Modeling of Dung Beetle Optimization-based Sink Node Localization Approach for Wireless Sensor Networks

R. Padmaraj; K. Selvakumar

doi:https://doi.org/10.54216/JISIoT.130101

International Journal of Neutrosophic Science | 2024

Interval-valued Fermatean Neutrosophic Graph with Grey Wolf Optimization for Sarcasm Recognition on Microblogging Data

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

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Abdulkhaleq Q. A. Hassan mail

link https://doi.org/10.54216/IJNS.240304

Volume & Issue

Vol. Volume 24 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2024

Optimization of Neutrosophic EOQ Model for Effective Demand Management in Uncertain Environment Using Genetic Optimization

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

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Manjula G. J. mail -

N. Anitha mail -

A. P. Pushpalatha mail -

K. Vinaya Laxmi mail -

M. Premalatha mail -

Mekala Selvaraj mail

link https://doi.org/10.54216/IJNS.240305

Volume & Issue

Vol. Volume 24 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2024

Development of a novel uncertainty model for interval-valued Q-fuzzy soft sets: Application in design-making

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).

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Mohanad H. Jameel mail -

Sinan O. Al-Salihi mail -

Faisal Al-Sharqi mail

link https://doi.org/10.54216/IJNS.240306

Volume & Issue

Vol. Volume 24 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2024

A new generalized topology coarser than the old generalized topology

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.

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Jos´e Sanabria mail -

Alexandra Barroso mail -

Jorge Vielma mail

link https://doi.org/10.54216/IJNS.240307

Volume & Issue

Vol. Volume 24 / Iss. Issue 3

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International Journal of Neutrosophic Science | 2024

New approach to bisemiring via the q-neutrosophic cubic vague subbisemiring

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.

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S. Selvaraj mail -

M. Palanikumar mail -

Faisal Al-Sharqi mail -

Ashraf Al-Quran mail -

Ali M. A. Bany Awad mail -

K. Lenin Muthu Kumaran mail -

M. Geethalakshmi mail

link https://doi.org/10.54216/IJNS.240308

Volume & Issue

Vol. Volume 24 / Iss. Issue 3

Details open_in_new

Fusion: Practice and Applications | 2024

Deep Neural Network Discipline and Consequence to be Achieved through Internet Implementation Dropdown

The difficulty of automatically modifying and updating operations within Deep Learning (DL) frameworks can slow down the performance of Deep Neural Network processing (DNNs). This research presents a novel approach to software optimization by leveraging dynamically collected profile data. A unique online auto-tuning system for DNNs was developed to enhance both the training and inference phases. Python Distributed Training of Neural Networks (PyDTNN) is a lightweight toolkit designed for distributed DNN training and estimation. It is utilized to evaluate the VGG19 model on two distinct multi-core architecture options. In testing, our auto-tuning system performs comparably, if not better, than a static selection strategy. The performance of each variation of PyDTNN that employs static selection remains consistently high throughout execution. Conversely, the auto-tuned version initially performs at a set level and progressively improves as more feasible choices become available. While both variations yield similar results in training, the selection strategy outperforms all other inference options by autonomously determining the best strategy for each layer in VGG19. The new online implementation selection tool assists in choosing the best performance option from numerous alternatives while the program is running. Its key features include constructing layered judgments and thoroughly examining 35 possibilities. Our advanced systems represent the optimal choice for monitoring sustainable environmental systems with maximum effectiveness, efficiency, and timeliness.

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Haitham S. Hasan mail

link https://doi.org/10.54216/FPA.160115

Volume & Issue

Vol. Volume 16 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2024

The Mathematical Formulas for Inverting Plithogenic Matrices of Special Orders Between 20 and 24

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.

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Ahmad A.Abubaker mail -

Wael M. Mohammad Salameh mail -

Heba Alrawashdeh mail -

Amani Shatarah mail -

Norah Mousa Alrayes mail -

Abdallah Al-Husban mail

link https://doi.org/10.54216/IJNS.240309

Volume & Issue

Vol. Volume 24 / Iss. Issue 3

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Journal of Neutrosophic and Fuzzy Systems | 2024

On the Non-Commutative Logical Rings As Novel Extensions of Neutrosophic Rings

This paper uses some logical algebraic elements to extend any ring into a non-commutative ring containing the original ring with many generalized substructures and special elements. On the other hand, we study the substructures of non-commutative logical rings such as AH-homomorphisms and AH-ideals with many examples that explain their algebraic validity. Also, we discuss the possibility of solving a linear Diophantine equation with two variables in the non-commutative logical ring of integers, where we present an easy algorithm to solve this kind of generalized Diophantine equation.

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Murat Ozcek mail

link https://doi.org/10.54216/JNFS.080203

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

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Journal of Neutrosophic and Fuzzy Systems | 2024

On the Usage of Orthogonal Polynomials with Picard Iteration Method to Find Numerical Solutions of Neutrosophic Non-Linear Ordinary and Partial Differential Equations

This research aims to modify the Picard iteration method by hybridizing it with some orthogonal polynomials and then applying the hybrid method in solving neutrosophic nonlinear elementary value problems. This method is based on modifying the Picard iteration method by approximating the right-hand side of the neutrosophic differential equation of the studied problem either by Legendre polynomials or by Chebyshev polynomials of the first kind to obtain two different hybrids of the Picard iteration method. Also, we apply this modification to neutrosophic elementary value problems represented by neutrosophic nonlinear and right-handed nonlinear differential equations to demonstrate the reliability and efficiency of the proposed modified method. For this goal, we prove how effective this method is, we calculate the neutrosophic absolute error of approximate solutions resulting from the application of the proposed modification of the Picard iteration method and with the exact solution.

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Arwa Hajjari mail

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

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2024

Modeling of Dung Beetle Optimization-based Sink Node Localization Approach for Wireless Sensor Networks

Wireless sensor network (WSN) performs monitoring of each aspect of the area of interest by detecting the surrounding physical phenomena with sensor nodes and transferring the information to the gateway through the corresponding system. Several researcher workers have introduced localization methods to accomplish high accuracy of localization. An intelligent optimization technique has attracted various researcher workers due to its advantages such as strong optimization capability and few parameters to optimize the localization performance of the DV-Hop method. Sink node localization (NL) using metaheuristics in WSN includes applying optimization techniques inspired by human behavior or natural phenomena to define the geographical coordinates of the sink nodes within the network coverage region. WSNs can accomplish better localization performance, especially in dynamic or complex environments, improving the efficiency and reliability of network management and data transmission by leveraging metaheuristics. In this view, this manuscript develops a Dung Beetle Optimization based Sink Node Localization Approach (DBO-SNLA) for WSN. In the DBO-SNLA technique, the DBO algorithm involved is based on the social behavior of dung beetle populations and is developed with five updated rules to assist in finding high-quality solutions. In addition, the DBO-SNLA technique addresses the issues of defining the sink node location with lowest localization error once the data between the nodes is transferred wirelessly. Finally, the localization errors are calculated and the location of the different unknown nodes is computed. A detailed set of simulation takes place to examine the performance of the DBO-SNLA technique. The empirical analysis stated the betterment of the DBO-SNLA method than other techniques

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R. Padmaraj mail -

K. Selvakumar mail

link https://doi.org/10.54216/JISIoT.130101

Volume & Issue

Vol. Volume 13 / Iss. Issue 1

Details open_in_new