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Important Neutrosophic Rules for Decision-Making in the Case of Uncertain Data

An urgent need to make a rational decision has emerged in the world of rapid changes based on quantitative methods that reduce the proportion of risk, especially if the decisions are fateful and the decision issues are huge and complex, noting that the decision-making process and the selection of the optimal alternative depends on the quality of the data that describes the issue that the decision is intended to be taken. Because the theory of administrative decision-making depends on this data and on the type of this data if it is confirmed data or unconfirmed data and not specified with sufficient accuracy, or random data that is repeated according to a certain probability distribution law, after which the decision maker uses the methods used to obtain on the optimal decision. In this research we will study the theory of administrative decisions in the case of uncertain data, which is the situation that the decision maker faces, and he does not know anything certain about the state that nature (market or management --) will take, nor even about the possibilities of any of them, then it is assumed that the cases the possible ones are equal and they enter the analysis at the same opportunity and make a trade-off between the alternatives available to him in all circumstances. In the classical logic, a set of rules was used to help the decision maker to make the ideal decision, and since the ideal decision depends on specific classical values ​​that do not take into account the changes that may occur in the work environment, which is represented by high prices or unavailability of materials or others, it was necessary to search for a better method that helps us to avoid dealing with specific values ​​and gives us a margin of freedom. Therefore, in this research, we will study the theory of decision-making in the case of uncertain data using the Neutrosophic Logic, the logic that helps us to face fluctuations and changes that we may encounter during work, through uncertainty that the Neutrosophical values ​​have, which we will take in the elements of the profit (or loss) matrix and rely on them in the decision-making process, as we will take these values ​​in the form of fields representing the minimum field of profit (or loss) that we can get in the worst cases of nature, and represents the upper limit of the field of profit (or loss) that we can get in the best cases of nature, and we will show the most important rules used in the case of uncertain data with an applied example of each rule.

groups
Maissam Jdid mail -
Basel Shahin mail -
Fatima Al Suleiman mail
link https://doi.org/10.54216/IJNS.1803014

Volume & Issue

Vol. Volume 18 / Iss. Issue 3

Details open_in_new

Artificial Flora Optimization Algorithm with Functional Link Neural Network for DoS Attack Classification in WSN

Wireless sensor networks (WSN) is widely utilized for collecting data related to physical parameters from the environment. Security remains a challenging issue in the design of WSN. Security in WSN from Denial of Service (DoS) attack is an important security risk. This study introduces an artificial flora optimization algorithm with functional link neural network (AFOA-FLNN) model for DoS attack classification in WSN. The presented AFOA-FLNN model initially undergoes data pre-processing to transform the data into meaningful way. Secondly, the FLNN model is utilized for the effective recognition and classification of intrusions in WSN. Finally, the AFOA is exploited for optimally tuning the parameters involved in the FLNN model and results in enhanced performance. In order to demonstrate the better outcomes of the AFOA-FLNN model, a wide-ranging experimentation assessment on test data and the results pointed out the improved outcomes of the AFOA-FLNN model.

groups
Mahmoud A. Zaher mail -
Mohmaed A. Labib mail
link https://doi.org/10.54216/IJWAC.040101

Volume & Issue

Vol. Volume 4 / Iss. Issue 1

Details open_in_new

Evaluating the Performance of Battery Electric Vehicles using an Incorporated Decision Support Framework Based on Ranking Algorithms

The use of alternative energy sources rather than fossil fuels will be unavoidable in the nearish term due to rising levels of toxic residues that threaten natural life and human health. Furthermore, the use of fossil fuels puts subsequent generations in danger from environmental damage and climate change. Battery electric vehicles (BEVs), an environmentally friendly kind of vehicle, are important in light of transportation's significant contribution to the carbon footprint. In light of the recent fast growth of the BEV industry, it has become more important to consider all available BEV options from the perspective of the end-user. Each BEV's fundamental characteristics may be examined in order to make this evaluation. For the correct BEV buying choice, MCDM strategies are useful. As a result, eleven battery-electric vehicles (BEVs) are considered in this study. A variety of multi-criteria methodologies are used to rate these cars on the basis of their technical specifications, such as acceleration, pricing, battery life, and range. It is then used entropy weight and TOPSIS approaches to gather findings from different MCDM strategies. The entropy method is used to compute the weights of the criteria. Then the TOPSIS is used to rank the options.  The 3 key considerations for BEV choosing are "price," "permitted load," and "energy usage," with Tesla Model S emphasized as the preferred route. 

groups
Lobna Osman mail
link https://doi.org/10.54216/IJWAC.030203

Volume & Issue

Vol. Volume 3 / Iss. Issue 2

Details open_in_new

Neutrosophic Crisp minimal Structure

 In this paper, the neutrosophic crisp minimal structure which is a more general structure than the neutrosophic minimal structure is built on neutrosophic crisp sets. The necessary arguments which are neutrosophic minimal crisp open set, neutrosophic minimal crisp closed set, neutrosophic crisp minimal closure, and neutrosophic crisp minimal interior are defined and their basic properties are presented. Also, the neutrosophic crisp minimal structure subspace of neutrosophic crisp minimal structure is defined and studied some of its properties. Finally, many examples are presented. 

groups
Riad K. Al-Hamido mail
link https://doi.org/10.54216/JNFS.030103

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

Details open_in_new

An Intelligent Bankruptcy Prediction Model based on an Enhanced Sparrow Search Algorithm

Bankruptcy detection becomes one of the major subjects in finance. Indeed, for apparent reasons, several actors like shareholders or managers show more attention to the possibility of a firm’s bankruptcy. Subsequently, various researches are being conducted on the matter of bankruptcy prediction. Recently numerous research works have explored the application of machine learning (ML) techniques to bankruptcy prediction by having financial ratios as predictors. This article devises an Enhanced Sparrow Search Optimization with Deep Learning Enabled Bankruptcy Prediction (ESSODL-BP) model. The proposed ESSODL-BP technique involves the forecasting of the bankruptcy of a financial firm. To accomplish this, the ESSODL-BP technique primarily follows the Z-score normalization approach. Followed by, the bidirectional long short-term memory (BLSTM) model is designed to predict the bankruptcy status of a financial firm. Then, the ESSO algorithm is utilized for optimally tuning the hyperparameters related to the BLSTM model and also boosts the prediction performance to a maximum extent. The performance validation of the ESSODL-BP technique is tested using a benchmark dataset. The experimental outcomes reported better performance of the ESSODL-BP technique over other approaches.

groups
Abdulaziz Shehab mail -
Mahmood Mahmood mail
link https://doi.org/10.54216/JISIoT.060101

Volume & Issue

Vol. Volume 6 / Iss. Issue 1

Details open_in_new

Development of Sustainable assessment Model of solar hydrogen production techniques: An integrated MCDM approach

Energy has a critical role in human survival and societal progress. Hydrogen is a possible energy carrier for long-term power generation. Known as both an environmental nuisance and an essential hydrogen source, Hydrogen Sulfide (H2S) may be found in large quantities in the waters of the Black Sea. The primary goal of this research is to determine which breakdown processes, such as thermal, thermochemical, electrochemical, plasma, photochemical and thermal suit sustainability requirements better than others. The most acceptable hydrogen generation technique is chosen based on characteristics such as financial viability, environmental viability, effectiveness, simplicity of the process, energy consumption, safety and dependability, application and operational adaptability, and technological maturity. This paper proposes innovative additions to the CoCoSo approach. The COCOSO method is used to compute the weights of criteria and rank the alternatives. This paper proposed 8 criteria and 5 alternatives.

groups
Mahmoud Ismail mail -
Shereen Zaki mail -
Mahmoud Ibrahim mail
link https://doi.org/10.54216/JISIoT.060102

Volume & Issue

Vol. Volume 6 / Iss. Issue 1

Details open_in_new

An Effective multicriteria decision-making model for extraction of lithium from seawater/brine: Design and practice

PROMETHEE II decision-making methodologies are integrated into a novel framework in this research. A real-world case study of lithium extraction techniques served as the basis for this investigation. Lithium extraction from brines and saltwater has become more difficult due to the limited natural resources of lithium and the worldwide desire to replace fossil fuels with clean and recyclable energy. Using a multicriteria decision-making approach, the suggested framework aids in selecting the best lithium extraction procedure from brines and saltwater. A case study of lithium extraction from brines and saltwater has been used. The findings of the study show that the suggested strategy is logical and enforceable.

groups
Mahmoud Ismail mail
link https://doi.org/10.54216/FPA.040104

Volume & Issue

Vol. Volume 4 / Iss. Issue 1

Details open_in_new

Multi-criteria Decision Making Model for Industrial Arc Welding Robot

Industrial robots have made it possible for manufacturers to make elevated low-cost products, which are thus major elements of advanced production technologies. Welding, cleaning, assembling, dismantling, slotting for computer chips, labeling requirements, stacking pallets, quality inspection, and monitoring are just a few of the applications for robotic systems. All the features are completed with a high level of endurance, speed, and accuracy. Multiple and competing criteria must be assessed simultaneously in a comprehensive selection analysis to identify the effectiveness of robots. To provide an automated machine for such arc machining operation, simple multi-criteria decision-making (MCDM) technique based on the COPRAS method is described in this work. The COPRAS method calculates significance weights using objective preferences and ranks the options. The COPRAS technique was used to determine the ranking order. The findings revealed that MCDM techniques for robot selection are extremely useful. The study's peculiarity is that it uses COPRAS MCDM approaches to select industrial arc welding robots.

groups
Lobna Osman mail
link https://doi.org/10.54216/IJWAC.040102

Volume & Issue

Vol. Volume 4 / Iss. Issue 1

Details open_in_new

Experimental study of an automotive air conditioning system with alternative refrigerants

Optimizing efficiency studies were carried out to comply with environmental norms by using MCDM techniques to pick low GWP refrigerants for automotive air conditioning. Multi-criteria optimization for time consumption based on ratio analysis plus full multiplicative form (MULTIMOORA), is being employed in this work to compare 10 distinct alternatives with 10 criteria. Thermal conductivity, vapor pressure, saturation fluid density, latent specific heat, fluid viscosity, GWP, ozone-depleting potential, and cost per pound are among the many response qualities suited for data acquisition in terms of thermodynamics, and environmental stewardship, and economics. It is possible to standardize decision-makers grading and weighting systems using MCDM methodologies. RAA3 had the greatest rank among the 10 refrigerants tested in the MULTIMOORA methodology. The EDAS and TOPSIS techniques identified R-744 to be the worst refrigerant, whereas the MOORA approach showed RAA5 to be the worst refrigerant.

groups
Mahmoud Ismail mail -
Abduallah Gamal mail
link https://doi.org/10.54216/FPA.050104

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

Details open_in_new