Neutrosophic and Information Fusion

Observation and detection in different environments and weather conditions requires the use of multiple imaging methods in different spectral fields (millimeter, IR, visual, ultraviolet), where the merging process collects useful information from each spectral field and presents it in a single image. Fusion requires scene matching (zoom, rotation, shift). This article forms a good basis for real-time video image alignment and fusion, with a special focus on pixel-level fusion. In this work, we applied the affine transformation to align two images with an accuracy of up to one pixel, and then we applied several images fusion algorithms based on summing, average, linear summation, or taking the maximum or minimum values of the pixel values, and the results of applying linear addition and values algorithms were The pixels are great compared to other methods.  

Smarandache presents neutrosophic sets and provides a domain area that is made up of three separate subsets to reflect the various kinds of uncertainty. Neutrosophic sets are defined as the sets where every other element of the universe possesses a degree of truthiness, indeterminacy, and falsity, which range from 0 to 1, and where these degrees are subsets of the neutrosophic sets that are independent of each other. Neutrosophic sets are also known as neutrosophical subsets. In the neutrosophic sets, impreciseness is represented as truth and falsity functions, but the indeterminacy function represents degrees of belongingness and non-belongingness and differentiates between absoluteness and relativeness. Neutrosophic sets can deal with the unpredictability of the system and cut down on the paralysis brought on by conflicting information thanks to this notation. As a result, one might argue that this capacity is the single most significant benefit offered by neutrosophic sets in comparison to the many other forms of fuzzy extensions. By making use of these three functions, neutrosophic sets are able to create a domain area. This area makes it possible for various kinds of mathematical operations to be carried out separately despite the presence of uncertainty. Due to the fact that the behavior of these methodologies is inspired by Nature and its capacity for adapting to issues, in addition to the potential for combining more than one method to reach the best alternatives, metaheuristic algorithms are employed to initiate the finest or the best possible alternatives to a lot of optimization techniques. This is possible because metaheuristic algorithms have the ability to adapt to problems. The fact that numerous academics have utilized these techniques with neutrosophic science to offer several systems in recent years was the impetus for writing this overview study in the first place, which was based on the above rationale.

In latest days, 5G technology has undergone fast development and has since found widespread use in a variety of industries including medicine, travel, agriculture, and others. The 5G network's fundamental equipment, known as 5G ground stations, are responsible for achieving wireless signal transfer among wired communications systems and wireless endpoints. Additionally, 5G stations give communication range. Nevertheless, as the size of 5G ground stations continues to progressively develop, difficulties such as inadequate coverage area and subpar user experiences commonly arise. As a result, it is essential to conduct an all-encompassing performance evaluation of 5G ground stations in order to better understand the challenges that now exist in the development of ground stations. To begin, the components of the performance assessment index system, which include operating efficiency, economic condition, ecological effects, and social pressure, are assembled from their respective vantage points. In the next step, a unique hybrid multi-criteria decision-making (MCDM) approach that is built on the AHP methodology is used. In conclusion, ten 5G base stations are selected as samples for further investigation. The AHP is integrated with the Interval Valued Neutrosophic Sets (IVNSs). The IVNSs used to overcome incomplete and vague information.  The AHP method used to compute the weights of criteria.

Because of stricter rules from the government and growing awareness among the general public, sustainable supply chain management (SSCM) performs a significant role in the management of firm manufacturing operations. Companies that want to promote sustainable supply chain management (SSCM) must first choose the most suitable sustainable supplier, which is a MCDM dilemma, as highlighted in a number of research studies. In addition, because of their limited expertise, those who make decisions have a propensity to convey their opinions via the use of language phrases. The purpose of this work is to report on a unique MCDM model for the choice of sustainable suppliers. This approach integrates the MCDM MABAC method inside an uncertain language situation. With the assistance of uncertain linguistic sets, the neutrosophic sets used to overcome these uncertainty. When it comes to generating the ranking of possible suppliers, the MABAC is dependable and easy to understand. In conclusion, an iron maker is used as an example to illustrate the practicability and efficacy of the suggested strategy for the selection of sustainable suppliers.

In this age of ecological sustainability, energy planning has grown more complicated as a result of the inclusion of numerous standards, including technological, political, financial, and environmental considerations. As a result, this places significant limitations on the ability of policymakers to independently and covertly optimize energy sources, which is particularly problematic for rural populations. In contrast, the constraints imposed by the topography of the land on renewable energy (REEN) systems, which are for the most part dispersed across the natural environment, make energy planning more difficult. In these kinds of situations, decision analysis plays a crucial part in the process of creating these kinds of systems by taking into account a wide range of requirements and goals, even at fragmented levels of digitization. Many criterion decision making, often known as MCDM, is a subfield of operational research that focuses on finding optimum outcomes in complicated situations that include various measures, competing goals, and multiple criteria. Because it enables decision-makers to make choices while simultaneously taking into account all of the standards and goals, this tool is gaining traction in the area of energy planning, which is one of the reasons why it is becoming more famous. In this paper, the TOPSIS MCDM methodology is integrated with the triangular neutrosophic sets to rank and select best source of REEN in Egypt. The neutrosophic sets used due to incomplete and uncertainty in this ranking.

Industrial robots have made it possible for industrial companies to make goods of a good quality at lower costs. As a result, industrial robots are an integral component of sophisticated manufacturing systems. Industrial robots may be programmed to do a wide variety of tasks, including welding, painting, construction, and debugging. All of the elements are completed with an exceptional level of endurance, swiftness, and accuracy. The efficiency of industrial robots is governed by a number of different factors, some of which are in direct opposition to one another; for a strong choice approach, all of these criteria must be examined concurrently. For the purpose of selecting an industrial robot for the arc soldering process, a straightforward multi-criteria decision-making (MCDM) approach that is VIKOR method will be described in this research. The VIKOR method used to rank the robots. The results of the VIKOR methodology are provided here in the form of a priority of rating. The findings demonstrated that the MCDM strategies are highly helpful when selecting robots to utilize.