Explore how AI is driving sustainable economic growth and transforming business analysis worldwide

Nilufar

doi:https://doi.org/10.54216/JSDGT.040201

Journal of Intelligent Systems and Internet of Things | 2024

An adaptive distributed intrusion detection system in local network: Hybrid classification methods

In the realm of cybersecurity, the incessant evolution of network attacks necessitates advanced and robust intrusion detection systems (IDS). The major issues with these systems are numerous: false positive/negative alarms, delayed response and detection time, size of processed data, adaptability to future threats, scalability of the system, difficulty in detecting distributed attacks, and downtime (fault tolerance). We propose a system that introduces a distributed framework aimed at enhancing network security by effectively identifying subtle deviations from normal network behavior. This is achieved through transfer learning based on artificial neural networks, and support vector machine (SVM), capitalizing on their complementary strengths in recognizing complex patterns and addressing high-dimensional datasets. To validate the efficacy of the proposed approach, the NSL-KDD dataset is utilized within a distributed IDS architecture. It consists of several intrusion detection nodes representing subnetworks. A node consists of two agents that work collaboratively. A way is proposed to avoid interference between analysis agents: the network agents manager monitors the functioning of the nodes and displays the results of each vulnerability-detecting node in each subnet separately. Such communication between agents should reduce FPAS (false positive alarms) significantly. The Detection engine extracts relevant features of network attacks to solve the problem of SVM in processing huge sizes of data and detect adaptive future threats to detect famous distributed denial of services (DDOS) attacks in real-time. The system is highly scalable by increasing the number of intrusion detection system nodes if necessary. Central processing is avoided to circumvent a system failure situation, where processing and decision-making take place at the detection node level within each subnet.

groups

Amjad Hijazi mail -

Nizar Alhafez mail -

Iyad Al-khayat mail

link https://doi.org/10.54216/JISIoT.120110

Volume & Issue

Vol. Volume 12 / Iss. Issue 1

Details open_in_new

Fusion: Practice and Applications | 2024

Optimizing Task Scheduling and Resource Allocation in Computing Environments using Metaheuristic Methods

Optimizing system performance in dynamic and heterogeneous environments and the efficient management of computational tasks are crucial. This paper therefore looks at task scheduling and resource allocation algorithms in some depth. The work evaluates five algorithms: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Firefly Algorithm (FA) and Simulated Annealing (SA) across various workloads achieved by varying the task-to-node ratio. The paper identifies Finish Time and Deadline as two key performance metrics for gauging the efficacy of an algorithm, and a comprehensive investigation of the behaviors of these algorithms across different workloads was carried out. Results from the experiments reveal unique patterns in algorithmic behaviors by workload. In the 15-task and 5-node scenario, the GA and PSO algorithms outclass all others, completing 100 percent of tasks before deadlines, Task 5 was a bane to the ACO algorithm. The study proposes a more extensive system that promotes an adaptive algorithmic approach based on workload characteristics. Numerically, the GA and PSO algorithms triumphed completing 100 percent of tasks before their deadlines in the face of 10 tasks and 5 nodes, while the ACO algorithm stumbled on certain tasks. As it is stated in the study, The above-mentioned system offers an integrated approach to ill-structured problem of task scheduling and resource allocation. It offers an intelligent and aggressive scheduling scheme that runs asynchronously when a higher number of tasks is submitted for the completion in addition to those dynamically aborts whenever system load and utilization cascade excessively. The proposed design seems like full-fledged solution over project scheduling or resource allocation issues. It highlights a detailed method of the choice of algorithms based on semantic features, aiming at flexibility. Effects of producing quantifiable statistical results from the experiments on performance empirically demonstrate each algorithm performed under various settings.

groups

Heba M. Fadhil mail

link https://doi.org/10.54216/FPA.150113

Volume & Issue

Vol. Volume 15 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2024

Betam-Closed Sets in Fuzzy Neutrosophic Topological Spaces

The current work offers a new concept of sets and called uzzy eutrosophic m-closed sets in fuzzy neutrosophic topology. In fact, the research is an extended form of a research conducted by F. M. Mohammed et.al. [1-7]. It explores a number of noteworthy examples to shed the light on the new characteristics and attributes of these recently formed conceptions, as well as some associated interactions between them.

groups

Nawras N. Sabry mail -

Fatimah M. Mohammed mail

link https://doi.org/10.54216/IJNS.230412

Volume & Issue

Vol. Volume 23 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2024

Enhancing Digital Social Innovation Ecosystems: A Pythagorean Neutrosophic Bonferroni Mean (PNBM) -DEMATEL Analysis of Barriers Factors for Young Entrepreneurs

This study employs a Pythagorean Neutrosophic Bonferroni Mean (PNBM) - Decision Making Trial and Evaluation Laboratory (DEMATEL) approach to analyze barriers faced by young entrepreneurs in Digital Social Innovation (DSI). Pythagorean Neutrosophic Set (PNS) enriches the analysis, accommodating uncertainties in the complex socio-economic context. Limited Access to Funding emerges as the most influential barrier, showcasing its pivotal role in impacting other DSI challenges. Regulatory and Compliance Challenges are identified as interdependent, emphasizing their interconnected nature with broader barriers. Neutrosophic elements elucidate the uncertainties surrounding financial constraints, regulatory frameworks, and mentorship dynamics. The study contributes to a nuanced understanding of DSI challenges and pioneers the application of neutrosophic logic in socio-economic research. It advocates for a more inclusive decision-making methodology, fostering adaptability in addressing the indeterminate nature of barriers faced by young entrepreneurs navigating the digital social innovation landscape. The findings aim to enhance support systems, fostering a conducive environment for DSI initiatives and encouraging future research in neutrosophic decision-making methodologies.

groups

Zahari Rodzi mail -

Nur A. Binti Shafie mail -

N. Binti Abdul Razak mail -

Faisal Al-Sharqi mail -

Ashraf Al-Quran mail -

Ali M. A. Bany Awad mail

link https://doi.org/10.54216/IJNS.230413

Volume & Issue

Vol. Volume 23 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2024

Optimization of Neutrosophic Vendor-Buyer Economic Order Quantity Model Using Particle Swarm Optimization

This research introduces the Neutrosophic Vendor-Buyer Economic Order Quantity (EOQ) model, integrating Neutrosophic Set Theory and Particle Swarm Optimization (PSO) for advanced inventory management. Addressing uncertainties in demand and costs, Neutrosophic Sets quantify truth, indeterminacy, and falsity degrees for key parameters. The model, employing PSO inspired by collective behaviour in nature, aims to minimize the combined total cost (C) encompassing vendor and buyer expenses. A grocery store scenario illustrates the approach, demonstrating substantial total cost reduction through the optimization of decision variables. MATLAB R2015a visualizations include a mesh plot depicting cost changes across varying EOQ and demand variability values, emphasizing optimal solutions. A bar chart compares initial and optimized total costs, showcasing efficiency gains. Cost breakdowns and pie charts detail the impact on vendor and buyer expenses. Sensitivity analysis systematically explores variable influences, aiding decision-makers in understanding trade-offs and optimal ranges by using Python. This comprehensive framework contributes empirical insights for practical implementation, enabling businesses to make informed decisions and enhance adaptive inventory strategies efficiently.

groups

K. Kalaiarasi mail -

N. Anitha mail -

S. Swathi mail -

B. Ranjitha mail

link https://doi.org/10.54216/IJNS.230414

Volume & Issue

Vol. Volume 23 / Iss. Issue 4

Details open_in_new

Prospects for Applied Mathematics and Data Analysis | 2023

Double Indeterminacy - Neutrosophic study of an Approximation Techniques Used to Find Random Variables

The main interest in statistical analysis is to generate a series of random variables that follow the probability distribution in which the system under study operates. In almost all simulation tests, we need to generate random variables that follow a distribution, a distribution that adequately describes and represents the physical process involved in the experiment at That point. During the experiment, it may be necessary to simulate a real and perform the process of generating a random variable from a distribution many times depending on the complexity of the model to be simulated in order to obtain more accurate simulation results. In previous research, we presented a neutrosophical study of the process of generating random numbers and some techniques that can be used to convert these random numbers into variables. Randomness follows the probability distributions according to which the system to be simulated operates. These techniques were specific to probability distributions defined by a probability density function that is easy to deal with in terms of finding the cumulative distribution function and the inverse function of the cumulative distribution function or by calculating the values of this function at a certain value, and in reality, we encounter Many systems operate according to these distributions, which requires techniques other than the techniques presented. Therefore, in this research we will present a neutrosophical study of the approximation technique for generating random variables that follow probability distributions known as a complex probability density function. We will apply this study to find random variables that follow the distribution. Standard natural

groups

Maissam Jdid mail -

Florentin Smarandache mail

link https://doi.org/10.54216/PAMDA.030102

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

Details open_in_new

Prospects for Applied Mathematics and Data Analysis | 2023

Foundation of Appurtenance and Inclusion Equations for Constructing the Operations of Neutrosophic Numbers Needed in Neutrosophic Statistics (revised)

We introduce for the first time the appurtenance equation and inclusion equation, which help in understanding the operations with neutrosophic numbers within the frame of neutrosophic statistics. The way of solving them resembles the equations whose coefficients are sets (not single numbers).

groups

Florentin Smarandache mail

link https://doi.org/10.54216/PAMDA.030103

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2024

Single-Valued Pentapartitioned Neutrosophic Bi-Topological Spaces

In this article, we present the notion of Single-Valued Pentapartitioned Neutrosophic Bi-Topological Space (SVPNBTS) as a generalization of Single-Valued Pentapartitioned Neutrosophic Topological Space (SVPNTS) and Neutrosophic Bi-Topological Space (NBTS). Besides, we study the different types of open set and closed set namely single-valued pentapartitioned neutrosophic bi-open set (SVPNBOS), single-valued pentapartitioned neutrosophic bi-closed set (SVPNBCS), single-valued pentapartitioned neutrosophic bi-semi-open set (SVPNBSOS), single-valued pentapartitioned neutrosophic bi-semi-closed set (SVPNBSCS), single-valued pentapartitioned neutrosophic bi-pre-open set (SVPNBPOS), single-valued pentapartitioned neutrosophic bi-pre-closed set (SVPNBPCS), single-valued pentapartitioned neutrosophic bi-b-open set (SVPNBb-OS), single-valued pentapartitioned neutrosophic bi-b-closed set (SVPNBb-CS), etc. via SVPNBTSs. Besides, we introduce the notion of pairwise SVPNOS, pairwise SVPNCS, pairwise SVPNSOS, pairwise SVPNSCS, pairwise SVPNPOS, pairwise SVPNPCS, pairwise SVPNb-OS, pairwise SVPNb-CS, and furnish few illustrative examples on them. Further, we investigate several properties of these classes of sets and prove some interesting results in the form of propositions, theorems, etc. via SVPNBTSs.

groups

Suman Das mail -

Prasanna Poojary mail -

Vadiraja Bhatta G. R. mail -

Sunny Kumar Sharma mail

link https://doi.org/10.54216/IJNS.230415

Volume & Issue

Vol. Volume 23 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2024

Algebraic properties applied to sin trigonometric complex neutrosophic sets

This article presents a new way of analyzing multiple attribute decision-making (MADM) using (♭1, ♭2, ♭3) sin trigonometric complex neutrosophic sets (ST-CNS). Complex neutrosophic weighted averaging (ST-CNWA), sin trigonometric complex neutrosophic weighted geometric (ST-CNWG), sin trigonometric complex generalized neutrosophic weighted averaging (ST-CGNWA), and sin trigonometric complex generalized neutrosophic weighted geometric (ST-CGNWG). During our discussion, we presented an algorithm that utilized these operators. There are extensive numerical illustrations of score values. Furthermore, we will discuss commutativity, idempotency, and monotonicity of sin trigonometric complex neutrosophic sets as part of our discussion. It is easier, faster, and more convenient to find the best option this way. Consequently, the sin trigonometric complex (♭1, ♭2, ♭3) is more closely related to precise conclusions. Also revealed by the study was an intriguing and fascinating observation.

groups

M. Palanikumar mail -

Omaima alshanqiti mail

link https://doi.org/10.54216/IJNS.230416

Volume & Issue

Vol. Volume 23 / Iss. Issue 4

Details open_in_new

Journal of Sustainable Development and Green Technology | 2024

Explore how AI is driving sustainable economic growth and transforming business analysis worldwide

This research paper investigates the implications of the rise of artificial intelligence (AI) on the practice of business analysis and its impact on organizations. By focusing specifically on the integration of AI in business analysis, the study examines the challenges, opportunities, and transformations brought about by this technological advancement. It explores ethical considerations, emphasizes the need for human oversight and interpretation of AI-generated insights, and discusses the evolving skill set required for business analysts in the AI era. The findings contribute to understanding the implications of AI adoption in business analysis and provide valuable insights for organizations aiming to effectively and responsibly leverage AI in their decision-making processes.

groups

Nilufar Ismaılova mail

link https://doi.org/10.54216/JSDGT.040201

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new