The multi-fuzzy N-soft set and its applications to decision-making

Neural Computing and Applications - The goal of this paper is to introduce a novel hybrid model called multi-fuzzy N-soft set, and to design an adjustable decision-making methodology for solving...     

Effect of dispersing and stabilizing additives on rheological characteristics of the upgraded brown coal water mixture

Upgraded brown coal water mixture (UBCWM) preparation by using an Indonesian upgraded coal produced by upgraded brown coal (UBC) process, was carried out to study the effect of dispersing and stabilizing additives on rheological behavior of the UBCWM. Three kinds of anionic dispersing additives, naphthalene sulfonic formaldehyde condensate (NSF), poly (meth) acrylate (PMA) and poly styrene sulfonic acid (PSS) and three kinds of stabilizing additives, carboxyl methyl cellulose (CMC), rhansam gum (S-194) and gellan gum (S-60) were used in this study. Results indicate that the addition of NSF 0.3 wt.% together with S-194 0.01 wt.% is effective in preparing UBCWM with good slurryability and stability, based on its rheological characteristics with the apparent viscosity at shear rate of 100 s^− 1 and yield stress at zero point of shear rate. The rheological behavior of all of the UBCWM that prepared, exhibits non-Newtonian Bingham plastic. From the economical point of view, the price of S-194 is expensive. On the other hand, CMC is cheap and abundant. Therefore, the addition of CMC 0.01 wt.% together with NSF 0.3 wt.% is also effective in preparing UBCWM with good fluidity and stability.     

Parameter reductions in N‐soft sets and their applications in decision‐making

Parameter reduction is an important operation for improving the performance of decision‐making processes in various uncertainty theories. The theory of N‐soft sets is emerging as a powerful mathematical tool for dealing with uncertainties beyond the standard formulation of the soft set theory. In this research article, we extend the notion of parameter reduction to N‐soft set theory, and we also justify its practical calculation. To this purpose, we define related theoretical concepts (e.g. N‐soft subset, reduct N‐soft set and redundant parameter) and examine some of their fundamental properties. Then, we argue that the idea of attributes reduction from the rough set theory cannot be employed in the N‐soft set theory in order to reduce the number of parameters. Consequently, we take an original position in order to adequately define and compute parameter reductions in N‐soft sets. Finally, we develop an application of parameter reduction of N‐soft sets.