Potential Energy Efficient Data Fusion Model for Wireless Sensor Networks

Rajeev; Manoj; Jaswant

doi:https://doi.org/10.54216/FPA.080204

International Journal of Neutrosophic Science | 2022

On The Neutrosophic Formula of Some Matrix Equations Derived from Data Mining Theory and Control Systems

This paper is dedicated to studying the neutrosophic formula of some famous matrix equations used in theoretical data mining algorithms and control systems by using neutrosophic matrices and refined neutrosophic matrices over neutrosophic real fields. On the other hand, we concentrate on the neutrosophic formula of the Sylvester equation, and Lyapunov equation, where we study their formulas and properties in terms of theorems in the neutrosophic real number field and refined real number field. Also, we illustrate many different examples to clarify the validity of our work.

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S. Obaid Jameel mail -

A. Mahdi Salih mail -

R. Adnan Jaleel mail -

Musaddak M. A. Zahra mail

link https://doi.org/10.54216/IJNS.190122

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

Neutrosophic K-means for market segmentation

Markets may be broken down into subsets with the use of cluster analysis. Multivariate analytic methods are often used in traditional research. Due to their success in engineering, artificial neural systems have recently found use in business as well. When it comes to grouping observations with comparable traits or attributes, the K-means method is a common choice. It has various uses in marketing, but it finds particular success in cluster analyses of customer behavior. Several commercial packages include implementations of the K-means algorithm. Data mining statistical approaches like K-Means are useful for handling this data and analyzing it later on. For better results, this study combines the traditional K-Means technique with Neutrosophy, which accounts for the uncertainty inherent in such complicated data sets by factoring in the data's diversity and its inherent volatility as a result of proximity between the bounds of the separate segments as well as the members who make up each.

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A. Romero Fernández mail -

G. Alvarez Gómez mail -

C. Gómez Armijos mail

link https://doi.org/10.54216/IJNS.190123

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

Evaluation of Social Projects Using Neutrosophic AHP

Recently, industrialization has led to a worldwide rise in energy usage. Consequently, satisfying rising energy demands has assumed more significance. Fuel, gasoline, and nat gas are all finite resources, making it all the more important to discover sustainable energy alternatives. To fulfill the current need for energy, renewable resources play a significant role. Therefore, energy decisions and government policy are of paramount importance for nations. Energy policy and judgment challenges, such as the appraisal of energy projects, the choice among fuel sources, the location of power plants, and the determination of energy policy, are solved using a variety of technical, financial, ecological, and social factors. Multi-criterion decision-making (MCDM) methodologies may be used to assess energy policy decisions, one of the important challenges for governments. Some of the challenges associated with making energy-related decisions and formulating policies are choosing between various energy sources, assessing the relative merits of various energy supply techniques, formulating an energy strategy, and carrying it through. Various forms of fuel sources are taken into account in the much research that has been conducted on energy decision-making challenges. Because they take into account several, sometimes competing, criteria in their assessments of potential solutions, MCDM techniques have proven useful in the resolution of energy-related decision-making issues. By combining MCDM with the neutrosophic set theory (NST), which captures the inherent ambiguity of human judgment, we may get more nuanced, tangible, and practical outcomes. This work intends to provide a thorough analysis of the methodology and implementations of neutrosophic MCDM in the power industry, as well as to synthesize the current literature and the latest recent breakthroughs to help guide researchers in this area. The neutrosophic Analytic Hierarchy Process (AHP) method is used to compute the weights of each criterion of energy in a social project. This research shows that neutrosophic AHP, either on its own or in combination with another MCDM approach, is the most often used MCDM technique.

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R. Comas Rodríguez mail -

J. M. D. Oca Sánchez mail -

V. Lucero Salcedo mail

link https://doi.org/10.54216/IJNS.190124

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

Indeterminate Likert Scale in Social Sciences Research

The Likert scale is by far the most popular psychometric tool for collecting data. The ordinal structure and confined style of the Likert scale make it prone to information misinterpretation and loss. Depending on the consumers' moods, replies in the real world are sometimes erratic, imprecise, and ill-defined. Neutrosophy (the study of the implementation of the provisions and indeterminacy) is utilized to accurately portray the answers. This work introduces a neutrosophic-informed, agnostic version of the Likert scale. Clustering users based on their comments is an efficient method of segmenting the population and marketing to them. In this research, we offer a clustering approach for responses received using arbitrary Likert scales. When dealing with real-world events, indeterminate Likert scales are superior in recording replies properly.

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M. M. Rosa Leonor mail -

G. S. Manaces Easud mail -

P. P. Luis Fernando mail

link https://doi.org/10.54216/IJNS.190125

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

Neutrosophic Multi-Criteria Method for Selecting Optimum Market

The Indonesian rolling stock maker's target market and business strategy are analyzed here—the study's planning, data, and technique. To achieve sustainable growth across the board in the power generating industry, we concentrate on understanding the critical variables driving sustainable development in a market context unlike before. To identify the most vital aspects to consider while dealing with ambiguous rules, a methodology using Multiple-Criteria Decision-Making (MCDM) was presented. To address ambiguity and bring the problem-solving process closer to reality, we created a unique method that integrates MCDM techniques. Analytical Hierarchy Process AHP was employed in this investigation. To zero in on our ideal clientele, we turned to the AHP technique. This strategy considers quantitative aspects such as market characteristics and degree of competition when making decisions. The results indicate that rolling stock manufacturers have good reason to invest in expanding their share of these markets. However, despite the many prospects available in this field, the rolling stock producer faces a significant obstacle: the inability to adequately fund the pursuit of a more considerable portion of the market

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O. ESPINOZA LASTRA mail -

L. Baque Villanueva mail -

A. Izquierdo Morán mail

link https://doi.org/10.54216/IJNS.190126

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

Neutrosophic Cognitive Maps for Violence Cause Analysis

Among the most valuable AI methods for modeling complicated things at the moment is the use of fuzzy cognitive mapping (FCMs). Conventional FCMs, on the other hand, can't handle the ambiguity that often arises in decision-making scenarios. A novel expansion of conventional FCMs called neutrosophic cognitive mapping (NCMs) was developed to address this shortcoming. However, the indeterminacy is not well handled by the NCMs stated in the citations since the level of indeterminacy is not quantified. In certain cases, choices should be seen as a series of steps that are only loosely related to one another. This occurs in project assessment when several activities depend on one another. Another difficult aspect of FCMs is that there isn't an appropriate topology for representing these types of decision-making difficulties. To aid in making decisions over several time periods, this research introduces a neutrosophic cognitive map built on triangular neutrosophic values (MS-TrNCM) for violence analysis. Through the use of triangular neutrosophic numbers, the suggested model allows experts to express their choices while considering various extents of truth, indeterminacy, and falsity in the underlying map linkages.

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H. E. Lozano Rojas mail -

F. Sánchez Nelson mail -

Mendez Cabrita Marina mail

link https://doi.org/10.54216/IJNS.190128

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

A Novel Approach on Neutrosophic Binary αgs Neighborhood Points and its Operators

The main idea of this paper is to introduce neutrosophic binary αgs-neighborhood points and neutrosophic binary αgs interior and closure operators. Furthermore, some of its properties are contemplated.

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Surekha S. S mail -

Sindhu G mail -

broumi said mail

link https://doi.org/10.54216/IJNS.190127

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

American Journal of Business and Operations Research | 2022

Statistical Machine Learning Model and Commodity Futures Volatility Information for Financial Stock Market Forecasting

A country's economy and social structure are greatly influenced by the stock market. It is extremely difficult for investors, expert analysts, and scholars in the financial industry to forecast the stock market accurately because of the pretty unstable, parametric, non-linear dynamical, and unstable character of stock price time series. In the financial sector, stock market forecasting is a critical activity and a prominent study subject because stock market investments carry greater risk. It's conceivable, however, to reduce most of the risk through the development of computationally intelligent approaches. This paper introduces the support vector machine regression to make a model forecasting the stock market financial.

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Denis A. Pustokhin mail -

Irina V. Pustokhina mail

link https://doi.org/10.54216/AJBOR.070203

Volume & Issue

Vol. Volume 7 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2022

New Entropy Measure Concept for Single Value Neutrosophic Sets with Application in Medical Diagnosis

This study aims to propose a new entropy weight on the distance measure of single value neutrosophic set (SVNS) to analyse medical diagnosis patient’s risk. Four distance measures will be integrated with three entropy weight concepts and applied to medical diagnosis. A new entropy weight measure integrated with the four distance measures are calculated using the medical data of one patient with five symptoms and five diseases. The calculated new entropy and its associated distance measures give consistent finding with the existing entropy weight measures. However, all the values are even smaller showing that the relation between patient A and disease are stronger. This evaluation and diagnosis approach is applicable to a wide variety of other resources and medical problems.

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Norzieha Mustapha mail -

Suriana Alias mail -

Roliza Md Yasin mail -

Nurnisa Nasuha Mohd Yusof mail -

Nurul Najiha Fakhrarazi mail -

Nik Nur Aisyah Nik Hassan mail

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

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

Fusion: Practice and Applications | 2022

Potential Energy Efficient Data Fusion Model for Wireless Sensor Networks

Wireless sensor networks have made a significant contribution to wireless sensor communication system based on resource constraints and limited computational sensors. Over the last decade, several focused research efforts have been made to investigate and provide solutions to problems relating to the energy efficiency data fusion aggregation in Wireless sensor networks. However, the problem of designing routes that are energy efficient has not been resolved. It is rather a tough effort to guarantee that the lifespan of a sensor is prolonged for a longer period because of the restricted computational capabilities of sensors, which are often coupled with energy constraints. The findings of this work present an enhanced energy-efficient technique for communication in sensor networks which consists of three distinct innovative frameworks. The suggested framework known as Data Fusion with Potential Energy Efficiency (DFWPEE) is responsible for the optimization of energy. The proposed work reduces energy consumption by using probabilistic methods and clustering. During the data fusion process, the Multiple Zone Data Fusion (MZDF) architecture uses a globular topology that helps with load balancing. The strategy presents an innovative routing approach that is used to aid in the performance of energy efficient routing in large-scale wireless sensor networks. By introducing the idea of routing agents, the framework for the Tree-Based Fusion Technique (TBFT), as suggested, comes up with an innovative method for dynamic reconfiguration. The plan enables the system to determine which sensor has a higher rate of energy dissipation and then immediately transfers the job of data fusion to a node that is more energy efficient. This threshold-based technique enables a sensor to perform both the role of a cluster head and the function of a member node. The node behaves as a cluster head until it achieves its threshold remnant energy and functions as a member node after it passes the threshold residual energy. Both of these roles may be played simultaneously. The mathematical modeling was done using the conventional radio energy model which improved the dependability of attained results. The proposed system delivers enhanced energy efficient communication performance when measured against existing implemented standards for energy efficient schemes.  The enhanced technique uses nearly half as much energy as LEACH while focusing on reducing the overall time taken for the process to complete leading to enhanced performance.

groups

Rajeev Pandey mail -

Manoj Kumar mail -

Jaswant Samar mail

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

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

Details open_in_new