Fusion-based Diversified Model for Internet of Vehicles: Leveraging Artificial Intelligence in Cloud Computing

Hayder Sabah; Fatema Akbar

doi:https://doi.org/10.54216/FPA.120205

Journal of Neutrosophic and Fuzzy Systems | 2023

Non-Euclidean Data Exploration using Turiyam Set and its Complement

  Recently, several researchers paid attention towards dealing the data sets beyond Non-Euclidean geometry. To achieve this goal, Turiyam set and its properties is introduced for precise measurement of uncertainty in data sets beyond acceptation, rejection and uncertain parts.  However the characterization of uncertainty requires a new operator and method. To resolve this issue, the current paper introduces a method for precise characterization of fourth dimensional data based on Turiyam operator and its complement with an illustrative example. The proposed method also compared the given method with Euclidean, Non-Euclidean, and NeutroGeometry data characterization.    

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Prem Kumar Singh mail

link https://doi.org/10.54216/JNFS.060203

Volume & Issue

Vol. Volume 6 / Iss. Issue 2

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Journal of Neutrosophic and Fuzzy Systems | 2023

Somewhat Neutrosopic δ-Continuous Functions in Neutrosophic Topological Spaces

In this paper the concepts of somewhat neutrosophic δ-continuous functions, somewhat neutrosophic δ-open functions between neutrosophic topological spaces are introduced and studied. Besides giving characterizations of these functions, several interesting properties of these functions are studied. The concepts of neutrosophic δ-resolvable spaces and neutrosophic δ-irresolvable spaces are also introduced and studied in this paper. These functions can be extended to a somewhat neutrosophic δ-irresolute continuous functions in neutrosophic topological spaces.

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C. John Sundar mail -

A. Vadivel mail

link https://doi.org/10.54216/JNFS.060204

Volume & Issue

Vol. Volume 6 / Iss. Issue 2

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Journal of Artificial Intelligence and Metaheuristics | 2023

A Smart Solution for Sustainable Cotton Farming: A Machine Learning Approach for Visual Recognition of Leaf Diseases

Cotton leaf diseases pose significant threats to sustainable farming practices, leading to yield losses and economic burdens for cotton growers worldwide. In this paper, we propose a smart solution for efficient and accurate detection of cotton leaf diseases using machine learning techniques. Our approach leverages a convolutional neural network (CNN) architecture specifically designed for visual recognition of leaf diseases. To train and optimize the CNN model, we employ a genetic algorithm that enhances the learning process and improves classification performance. The proposed model is trained and evaluated on a comprehensive dataset containing six classes of cotton leaf diseases, namely Aphids, Army worm, Bacterial Blight, Powdery Mildew, Target spot, and healthy leaves. Experimental results demonstrate the effectiveness of our proposed method, achieving an overall accuracy of 97% on the test set. Comparative analyses with existing studies and methodologies reveal the superior performance of our approach, showcasing its potential for practical implementation in the field of cotton leaf disease detection. The outcomes of this study have significant implications for farmers, agronomists, and agricultural organizations, enabling them to make informed decisions and take timely actions to protect their crops and enhance productivity.

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Ehsan khodadadi mail -

Sunil Kumar mail -

Marwa M. Eid mail

link https://doi.org/10.54216/JAIM.030204

Volume & Issue

Vol. Volume 3 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

Rework Warehouse Inventory Model for Product Distribution with Quality Conservation in Neutrosophic Environment

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. 

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Renee Miriam M. mail -

Nivetha Martin mail -

Aleeswari A. mail -

Said Broumi mail

link https://doi.org/10.54216/IJNS.210215

Volume & Issue

Vol. Volume 21 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

Analytical Study of Neutrosophic Fuzzy Unobservable On-Off Fluid Queues in Equipoise Strategies

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.

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P. Yasodai mail -

W. Ritha mail

link https://doi.org/10.54216/IJNS.210216

Volume & Issue

Vol. Volume 21 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

Integrated Single-Valued Neutrosophic Normalized Weighted Bonferroni Mean (SVNNWBM)-DEMATEL for Analyzing the Key Barriers to Halal Certification Adoption in Malaysia

The implementation of halal certification in Muslim-owned dining establishments in Malaysia faces various obstacles. This research aimed to analyze and investigate these challenges. The study used the DEMATEL approach with the integrated single-valued neutrosophic normalized weighted Bonferroni mean (SVNNWBM) to identify and understand the interrelationships among the obstacles. Three groups comprising academicians, industry professionals, and Muslim owner-restaurant representatives provided their perspectives. The findings highlighted three key obstacles hindering the acceptance and implementation of halal certification: customer perception, halal perception, and inadequate awareness. Fiscal constraints, inadequate awareness, and halal perception were significant barriers in Malaysia's restaurant sector. These obstacles were categorized as causal factors, generating additional barriers in the industry. By identifying these challenges, effective strategies can be developed to overcome them and improve the adoption of halal certification. This research provides valuable insights for policymakers, restaurant owners, and other stakeholders, enabling them to understand the obstacles better and develop targeted interventions. Employing the integrated SVNNWBM-DEMATEL approach and incorporating perspectives from experts in academia, industry, and Muslim owner-restaurant representatives ensures a comprehensive analysis of the obstacles faced in halal certification implementation.

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Z. bin Md Rodzi mail -

F. Azaliney Mohd Amin mail -

Nadwa Jamiatun mail -

Abdul Qaiyyum mail -

Faisal Al-Sharqi mail -

Zati Aqmar Zaharudin mail -

Muhamad Helmi M. Khair mail

link https://doi.org/10.54216/IJNS.210310

Volume & Issue

Vol. Volume 21 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2023

Scrutinization of a Neutrosophic Fuzzy Erlangian Queuing Model Using a Parametric Programming Technique

This article examines an Erlangian queuing model in a neutrosophic fuzzy environment. The inter-arrival rates and service rates are trapezoidal neutrosophic fuzzy numbers integrated into the Erlangian queuing model. The membership functions of the performance metrics of the corresponding queuing model have been outlined using parametric programming techniques in accordance with the (σ, β, γ)- cuts and Zadeh's extension principle. The neutrosophic fuzzy queues are converted into a family of crisp queues using this principle. The applicability of the provided approach for various cutting possibilities is highlighted by concrete examples.

groups

P. Yasodai mail -

W. Ritha mail

link https://doi.org/10.54216/IJNS.210311

Volume & Issue

Vol. Volume 21 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2023

PCM with Linguistic Contradiction Degree Representations in Decision making on Academic Stress causing Factors

Plithogenic Cognitive Map (PCM) is the generalized form of Cognitive maps that has recently ebbed into the field of decision-making. The first developed PCM model comprises of factors, connection matrix with numeric contradiction degree between the factors. In this research work a PCM model with linguistic contradiction degree representations between the core and sub factors is developed to make the decision-making more comprehensive. The model formulated in this research work is illustrated with the factors causing academic stress to the students of digital educational system. Personal, Social, Economic and Institutional are considered as the core factors and the contradiction degree in linguistic sense is considered with respect to each of these core factors and ten sub factors. The obtained results on comparing with conventional models are highly promising and this model will certainly set new benchmarks of a comprehensive decision-making model.

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N. Angel mail -

P. Pandiammal mail -

N. Ramila Gandhi mail -

Nivetha Martin mail -

Florentin Smarandache mail

link https://doi.org/10.54216/IJNS.210312

Volume & Issue

Vol. Volume 21 / Iss. Issue 3

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Journal of Neutrosophic and Fuzzy Systems | 2023

Shortest Path Problem using Pythagorean Fuzzy Triangular Number

This paper, they developed a new path to compromise with Pythagorean Shortest Path Problem (PSPP) in a network location each edge weight is expressed an Triangular Fuzzy Pythagorean Numbers (TFPNs). Then the Proposed Algorithm (PA) further provide the SP length from the source node (SN) to destination node (DN) from applying a Ranking Function for Pythagorean Fuzzy Numbers (PFN). Certainly, a descriptive example is also included.

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M. Asim Basha mail -

M. Mohammed Jabarulla mail -

broumi said mail

link https://doi.org/10.54216/JNFS.060205

Volume & Issue

Vol. Volume 6 / Iss. Issue 2

Details open_in_new

Fusion: Practice and Applications | 2023

Fusion-based Diversified Model for Internet of Vehicles: Leveraging Artificial Intelligence in Cloud Computing

The Internet of Vehicles (IoV) is a distributed system that enables data connectivity between vehicles and vehicular ad hoc networks, ensuring efficient and secure information exchange with infrastructures. Challenges in IoV include security clustering related to packet loss during data exchange, real-time analysis of public communication, and the need for autonomous-vehicle technology development using machine learning (ML). ML-assisted IoV has made significant progress in communication with public networks and interaction with the immediate surroundings. This study presents an experimental foundation for the advancement of the IoV system. While support vector machine (SVM) offers a robust and accurate approach for clustering velocity and solving classification challenges related to security, it is primarily a binary classifier and faces limitations in handling multi-class classification. To address this, an artificial neural network (ANN) is proposed for effective packet loss management in the autonomous system, improving the physical layer's secure network and offering better packet loss experience using the Global Positioning System. The fusion-based diversified model not only enables IoV systems to compete with rivals but also provides key advantages to ensure consistent profitability in cloud-enabled IoV. This paradigm integrates cloud computing (CC) with in-vehicle networks and the Internet of Things, offering safety and infotainment applications for road users. Data collection and experiments are conducted using Network Simulator 2 to automate AI configuration in the IoV fusion system.

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Hayder Sabah Salih mail -

Fatema Akbar Mohamed mail

link https://doi.org/10.54216/FPA.120205

Volume & Issue

Vol. Volume 12 / Iss. Issue 2

Details open_in_new