A Probabilistic Neutrosophic Hesitant Fuzzy Set for Waste Water Treatment Plants

Samandarboy

doi:https://doi.org/10.54216/JSDGT.040204

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.

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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

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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

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Maissam Jdid mail -

Florentin Smarandache mail

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

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

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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).

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Florentin Smarandache mail

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

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

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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.

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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

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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.

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M. Palanikumar mail -

Omaima alshanqiti mail

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

Volume & Issue

Vol. Volume 23 / Iss. Issue 4

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Prospects for Applied Mathematics and Data Analysis |

Using Linear Wavelets in Analyzing the GARCH Model with the Simulation

In this research, it was proposed to use linear wavelet shrinkage to reduce the noise in the data of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, which relies on time series data that is not homogeneous in variance, through the use of several linear wavelets, specifically Daubechies, Coiflets, and Dmey of the first order, to maintain the same order as the classical GARCH model, which is suitable for those data by estimating the thresholding level using the Minimax method and applying the soft threshold rule to obtain de- noise data and then using it to estimate the parameters of the GARCH models and comparing it with classical GARCH models that rely on the original data and without adding any percentages of contamination to the data in simulation experiments or real data. Comparison of the efficiency of the estimated models is based on the Akaike and Bayes information criterion through a MATLAB program designed for this purpose. The research results revealed that the GARCH models estimated using the proposed method were more efficient than the GARCH models estimated using the classical method, in addition to the Dmey wavelet being superior to the rest of the linear wavelets used in the research.

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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.

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Nilufar Ismaılova mail

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

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

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Journal of Sustainable Development and Green Technology | 2024

Takaful: Principles, Practices, and Global Growth

This article explores Takaful, an Islamic insurance scheme adhering to Sharia principles. It examines its unique features compared to conventional insurance and its role within Islamic banking. Additionally, it highlights Takaful’s expansion globally, especially in countries like Malaysia, Pakistan, Indonesia, Turkey, UAE, and Great Britain.

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Umidjon Dadabaev mail

link https://doi.org/10.54216/JSDGT.040202

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

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Journal of Sustainable Development and Green Technology | 2024

Evaluating the Onshore Wind Farms based on Multi-Criteria Decision-Making Model under Neutrosophic Set

This work comprehensively evaluates onshore wind farms, focusing on their technological efficiency, environmental impact, economic viability, and societal implications. Onshore wind energy has emerged as a prominent renewable energy source, leveraging the kinetic power of wind to generate electricity on a substantial scale. The evaluation encompasses a detailed analysis of wind resource assessment, turbine technology, grid integration, environmental considerations, economic feasibility, and stakeholder engagement. Findings reveal that onshore wind farms exhibit commendable technological advancements, with modern turbines showcasing higher efficiency and capacity. Environmental assessments highlight their lower carbon footprint compared to conventional energy sources, albeit with considerations for land use and wildlife impacts. Economic evaluations emphasize the decreasing costs of wind energy, yet challenges persist concerning upfront investment and intermittency. Stakeholder engagement emerges as a crucial aspect, stressing the importance of community acceptance and regulatory compliance. The assessment illuminates the multifaceted aspects of onshore wind farms, underscoring their potential as a sustainable energy source while acknowledging the need to address technological, economic, and social barriers to widespread adoption. We used the multi-criteria decision-making (MCDM) model for evaluating the onshore wind farms. The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) method is used to rank the alternatives. The MCDM method used under single valued neutrosophic set (SVNS). The SVNS is used to overcoming the uncertainty in the evaluation process.

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Durdona Uktamova mail

link https://doi.org/10.54216/JSDGT.040203

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

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Journal of Sustainable Development and Green Technology | 2024

A Probabilistic Neutrosophic Hesitant Fuzzy Set for Waste Water Treatment Plants

Decision-makers at wastewater treatment plants must increase process efficiency and circularity while preserving economic performance. They must comply with increasing requirements about lowering emissions, sustainability, and human health safety. To operate and choose technologies to fulfil these expectations leads to complicated multi-objective issues. As a consequence, the water industry has developed several decision support systems. Multi-criteria decision-making (MCDM) is used to deal with various criteria in the evaluation process. The MCDM methodology integrated with the probabilistic neutrosophic hesitant fuzzy set (PNHFS) to deal with vague and incomplete information. The PNHFS used the VIKOR method to rank the alternatives and used the optimal wastewater treatment plants. The criteria weights are computed. The results show that safety is of the highest importance—the sensitivity analysis was conducted to show the different ranks under different cases. The main results show the different ranks are stable, and the suggested MCDM methodology is robust compared with other MCDM methods.

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Samandarboy Sulaymanov mail

link https://doi.org/10.54216/JSDGT.040204

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new