Finite time Stability and Synchronization of the Glycolysis Reaction-Diffusion model

Raed; Issam; Ahmad; Rania; Adel; Mohamed

doi:https://doi.org/10.54216/IJNS.250431

International Journal of Neutrosophic Science | 2025

Fractional-Order SEIR Model for COVID-19: Finite-Time Stability Analysis and Numerical Validation

This paper investigates a fractional-order SEIR model to study the dynamics of infectious diseases, specifically COVID-19, by incorporating memory effects through fractional derivatives. The model’s formulation enhances the understanding of epidemic dynamics by considering disease transmission, recovery, and mortality rates under fractional calculus. Stability analyses are conducted for the disease-free equilibrium (DFE) and the pandemic fixed point (PFP), identifying critical conditions for finite-time stability using Lyapunov functions and fractional derivatives. Numerical simulations validate theoretical findings, demonstrating finitetime stabilization around the equilibrium points under realistic parameter settings. The results underscore the advantages of fractional-order modeling in capturing complex epidemic dynamics and highlight its potential to inform public health intervention strategies.

groups

Shaher Momani mail -

Iqbal M. Batiha mail -

Mohammad S. Hijazi mail -

Issam Bendib mail -

Adel Ouannas mail -

Nidal Anakira mail

link https://doi.org/10.54216/IJNS.260123

Volume & Issue

Vol. Volume 26 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

Neutrosophic subgroups and neutrosophic normal subgroups of groups

In this paper, we introduce the concepts of neutrosophic subgroups and neutrosophic normal subgroups of groups and investigate several properties. We investigate relations between neutrosophic subgroups (neutrosophic normal subgroups) and their neutrosophic level subsets of a group. We also look at the homomorphic image and inverse image of the neutrosophic subgroups and neutrosophic normal subgroups of groups, as well as some related properties.

groups

Aiyared Iampan mail -

C. Sivakumar mail -

Neelamegarajan Rajesh mail

link https://doi.org/10.54216/IJNS.260124

Volume & Issue

Vol. Volume 26 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

A Comprehensive Approach to Solid Waste Management Site Selection Using Simplified Neutrosophic Distance-Based Similarity Measures with N-Valued T-Spherical Fuzzy Neutrosophic Sets

In a neutrosophic environment, a single-valued neutrosophic multi-set, and an intuitionistic fuzzy-valued neutrosophic multi-set are defined by sequences of acceptance, indeterminacy, and rejection grades. The structure of these sets enables the incorporation of multiple layers of information across acceptance, indeterminacy, and rejection grades, making them particularly valuable for multi-criteria decision-making processes. This paper presents the N-valued T-spherical fuzzy neutrosophic set as an advanced extension of neutrosophic sets, aimed at improving uncertainty management and imprecision in complex, real-world scenarios. Building upon previous models such as neutrosophic sets, intuitionistic fuzzy-valued neutrosophic sets, Pythagorean fuzzy neutrosophic sets, and T-spherical fuzzy neutrosophic sets, this new approach introduces greater flexibility in handling indeterminacy. The authors define N-valued T-spherical fuzzy neutrosophic sets and numbers, incorporating new mathematical operations and comparison functions. A significant contribution of the work is the development of simplified neutrosophic-valued distance-based similarity measures for N-valued T-spherical fuzzy neutrosophic sets, along with a score function to rank simplified neutrosophic values. To illustrate the practical utility of this framework, an algorithm is applied to a real-world problem of site selection for solid waste management systems, effectively addressing decision-making scenarios with disjoint criteria. The results and discussions show that the N-valued T-spherical fuzzy neutrosophic set outperforms existing methods by providing more accurate and precise results, specifically in multi-criteria decision-making contexts. The site choice example for solid waste management highlights how this new approach enhances accuracy.

groups

Mahizha J. C. mail -

Immaculate Mary M. mail

link https://doi.org/10.54216/IJNS.260125

Volume & Issue

Vol. Volume 26 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

A Generalized Directed Divergence of Fuzzy Entropy

In the present paper, we introduced a new generalized parametric measure of fuzzy directed divergence of order σ with the proof of its validity. The particular case and some elegant properties of fuzzy directed divergence measure are studied. Total ambiguity , fuzzy information improvement measure and reduction in improvement measure are given for the proposed measure. A comparative study of proposed measure with existing generalized fuzzy directed divergence measure is computed numerically and represented by using graphical representation. The application of proposed fuzzy directed divergence measure in multi criteria decision making problem is demonstrated by using numerical example.

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Vaishali Manish Joshi mail -

Javid Gani Dar mail

link https://doi.org/10.54216/IJNS.260126

Volume & Issue

Vol. Volume 26 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

An Efficient Symmetric Operational Matrix Method for Solving Tempered Fractional Differential Equations with Respect to Another Function

In this paper, we introduce a novel extension of the symmetry operational matrix method specifically designed to tackle tempered fractional differential equations (FDE) that incorporate an additional function. Our approach leverages the framework of shifted Legendre polynomials (SLP), which are well-suited for this context. While the operational matrix method has been widely recognized for its efficacy in addressing a range of problems within fractional calculus, its application to tempered fractional differential equations remains relatively uncharted territory. To bridge this gap, we begin by deriving the analytical expression for the tempered fractional derivative (TFD) of the term τ p. This crucial step paves the way for the formulation of a new operational matrix that captures the behavior of fractional derivatives in conjunction with another function. We use a method that combines a limited number of terms from the shifted Legendre polynomial basis. This allows us to accurately solve tempered fractional differential equations that include an additional function. We show that our approach works well through several numerical examples, demonstrating how effective and accurate our results are in tackling these complex equations.  

groups

Mohammad Abdel Aal mail -

Ahmad Arafah mail

link https://doi.org/10.54216/IJNS.260128

Volume & Issue

Vol. Volume 26 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

Neutrosophic Methodological Foundations of Marketing Research in the Rural Labor Market

This article introduces a neutrosophic methodological framework for conducting personnel marketing research in the rural labor market of Uzbekistan. Given the inherent uncertainty and indeterminacy in labor market dynamics, the study applies neutrosophic logic to enhance the reliability of marketing data regarding labor demand and supply. The research outlines the interrelated stages of personnel marketing analysis, incorporating neutrosophic sets to better identify discrepancies between labor demand and supply, the scale and causes of rural unemployment, and the structural needs for new professions. Key areas of focus include problem identification, goal formulation, data collection and analysis, forecasting labor market trends, and developing targeted interventions to mitigate unemployment and improve workforce qualifications. Additionally, the study proposes strategic marketing initiatives for rural employment assistance centers, integrating neutrosophic decision-making models to optimize labor market strategies. By adopting neutrosophic approaches, the study provides a robust, uncertainty-aware methodology for balancing labor market proportions and formulating evidence-based policies to enhance rural employment opportunities.

groups

Kholmuminov Shayzak Rakhmatovich mail

link https://doi.org/10.54216/IJNS.260129

Volume & Issue

Vol. Volume 26 / Iss. Issue 1

Details open_in_new

Fusion: Practice and Applications | 2025

Enhancement of Underwater Images using Color Correction and Weight Maps

Physical characteristics of underwater environments, such as absorption, scattering, and progressive color loss, are only a few of the many factors that cause underwater images to degrade. Additionally, the turbid water and marine plankton influence the degradation of these images. All of these play a major role in the difficulty of extracting features from underwater images. This study aims to develop a new system that combines color correction techniques and weight maps to address the challenges caused by underwater environments. First step: the color correction, which consists of both color compensation and white balance, are used to improve the colors of images. In the second step:  a comprehensive enhancement solution has been adopted on the two images that resulted from the first step by performing two different ways, the first image is improved by an image sharpening algorithm, and the gamma correction is used to process the second one. Four weights maps are applied for feature extraction and finally multi-scale fusion process is used to find the final enhanced image. Three types of underwater scenes are used (Bluish, Greenish and Foggy) to assess the suggested work. In addition to evaluating the results visually, a number of statistical metrics (IE, PCQI, AG, UIQM and UCIQE) are used to evaluate the results and compare them with previous works. The results indicate a marked improvement in all types of image.

groups

Safa Burha mail -

Asmaa Sadiq mail

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

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

Enhancing educational environments with Social Media Feedback Evaluation Employing Hybrid Neutrosophic Decision Optimization (HNDO) and Neutrosophic Sentiment Fusion (NSF)

This research work examines the critical challenge of enhancing educational environments through social media feedback, often impeded by the very uncertainties and complexities offered by textual data. Existing approaches either may indulge in sentiment analysis or may take the approach of basic data mining; nevertheless, they seldom consider ambiguity, contextual subtlety, and dynamic interventions. We propose an entirely new framework using Hybrid Neutrosophic Decision Optimization (HNDO) and Neutrosophic Sentiment Fusion (NSF) with deep learning-for advanced feature extraction-and reinforcement learning-for adaptive intervention strategies, with Explainable AI (XAI) for transparency. Presenting a new Neutrosophic Quantum Squirrel-Whale Decision Optimization (NQSWDO) framework to optimize educational enhancements based on feedback surveys and social media sentiment analysis, where it can collect, preprocess, extract features, fuse sentiments, optimize decisions, and detect concerns through reinforcement learning before interpreting feedbacks. A Neutrosophic Sentiment Fusion (NSF) model is applied to bring improvement into the accuracy of sentiment classification. Further refinement of educational improvements will come through the new application of hybrid neutrosophic decision optimization (HNDO), which incorporates multi-criteria decision analysis (MCDA) and fuzzy logic. For identification of key concerns, the VGG-Darknet detection model will be used, as well as a deep Q-network (DQN)-based reinforcement-learning system that dynamically intervenes in topic analysis. The last phase will comprehensively interpret feedback and adopt decision-making strategies to avoid wasting time in properly formulating useful educational policies. The results from the experiments indicate the practicality of the proposed framework for improving education decision-making through advanced methodologies on sentiment analysis, optimization, and reinforcement learning.

groups

Walaa Fouda mail -

Asmaa Hegazy mail -

Najla M. Alnaqbi mail -

Ebru Ozbilge mail -

Emre Ozbilge mail

link https://doi.org/10.54216/IJNS.260130

Volume & Issue

Vol. Volume 26 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

Student Academic Performance Classification Using N-Valued Interval Neutrosophic Sets with Optimization Algorithms for Significant Feature Selection

The most effectual tools for demonstrating uncertainty in decision-making issues are the neutrosophic set (NS) and its additions, like interval NS (INS), complex NS (CNS), and interval complex NS (ICNS). NS delivers an effectual and precise method for defining an imbalance of information as per the data features. In present times, students’ academic performances have been evaluated on the base of regular examinations or memory-related tests and by equating their performances to recognize the features for forecasting their academic excellence. The prediction of student academic performance is involved in Educational data mining (EDM), which mainly focuses on using data mining methods in the educational side. EDM progress models for finding data, which is a result of educational surroundings. This paper presents a Student Academic Performance Prediction Using N-Valued Interval Neutrosophic Sets and Optimization Algorithms (SAPP-NINSOA). The main intention of the SAPP-NINSOA technique is to provide a prevalent technology for predicting students’ academic performance using an advanced optimization algorithm. At first, the data pre-processing stage applies Z-score normalization to convert input data into a beneficial format. Besides, the secretary bird optimization algorithm (SBOA) to select the relevant features from input data has executed the feature selection process. Next, the proposed SAPP-NINSOA model designs the N‐Valued Interval Neutrosophic Sets (NVINS) method for the classification process. Finally, the arithmetic optimization algorithm (AOA) fine-tunes the parameter values of the NVINS model. An extensive range of experimentation was led to certify the performance of the SAPP-NINSOA technique. The simulation outcomes stated that the SAPP-NINSOA algorithm emphasized furtherance when compared to other existing systems.

groups

Nahla Moussa mail -

Cuauhtemoc Samaniego mail -

Moustafa Mohamed Abouelnour mail -

Wael F. Ali mail

link https://doi.org/10.54216/IJNS.260131

Volume & Issue

Vol. Volume 26 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

Finite time Stability and Synchronization of the Glycolysis Reaction-Diffusion model

Finite-time stability is a critical property for systems where rapid stabilization is required, as it ensures that the system reaches and maintains equilibrium within a specified time frame, regardless of initial conditions. This contrasts with asymptotic stability, which only guarantees eventual convergence over an indefinite period. This research focuses on demonstrating the finite-time stability of the glycolysis reaction-diffusion system at its equilibrium point. The equilibrium points of the system are derived, and finite-time stability conditions are established. Definitions and lemmas are provided to support the theoretical framework, including conditions for finite-time convergence and Lyapunov stability. A key result shows that the system possesses a unique equilibrium point that can achieve finite-time stability under certain conditions. Additionally, the finite-time synchronization scheme is discussed, highlighting the process of rapidly achieving synchronized behavior in reaction-diffusion systems. The proposed method involves associating the main system with a response system and addressing synchronization discrepancies through the introduction of an error vector. This research provides a robust framework for understanding and achieving finite-time stability and synchronization in complex reaction-diffusion systems.

groups

Raed Hatamleh mail -

Issam Bendib mail -

Ahmad Qazza mail -

Rania Saadeh mail -

Adel Ouannas mail -

Mohamed Dalah mail

link https://doi.org/10.54216/IJNS.250431

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

Details open_in_new