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A Revised TOPSIS Method Based on Interval Fuzzy Soft Set Models with Incomplete Weight Information

Yang Y., Peng X.

Fundamenta Informaticae

2017

Vol. 152, nr 3

297--321

Soft set theory was originally proposed by Molodtsov in 1999 as a general mathematical tool for dealing with uncertainty. However, it has been pointed out that classical soft set model is not appropriate to deal with imprecise and fuzzy problems. In order to handle these types of problems, some fuzzy extensions of soft set theory are presented, yielding fuzzy soft set theory. As a further research, in this work, we first propose concepts of interval fuzzy sets and interval fuzzy soft sets, define some operations on them and study some of their relevant properties, especially, the dual laws are discussed with respect to difference operation in interval fuzzy soft set theory. We then introduce a revised Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method and choice value method for interval fuzzy soft set which the weight information is completely unknown. Meanwhile, an analysis of computation complexity is employed, also the discriminative power of two methods are shown. Finally, two illustrative examples are employed to show that they can be successfully applied to problems that contain uncertainties.

Low complexity multifocus image fusion in discrete cosine transform domain

Phamila A V, Amutha R

Optica Applicata

2013

Vol. 43, nr 4

693--706

This paper presents a low complex, highly energy efficient sensor image fusion scheme explicitly designed for wireless visual sensor systems equipped with resource constrained, battery powered image sensors and employed in surveillance, hazardous environment like battlefields etc. Here an energy efficient simple method for fusion of multifocus images based on higher valued AC coefficients calculated in discrete cosine transform domain is presented. The proposed method overcomes the computation and energy limitation of low power devices and is investigated in terms of image quality and computation energy. Simulations are performed using Atmel ATmega128 processor of Mica 2 mote, to measure the resultant energy savings and the simulation results demonstrate that the proposed algorithm is extremely fast and consumes only around 1% of energy consumed by conventional discrete cosine transform based fusion schemes. Also the simplicity of our proposed method makes it more appropriate for real-time applications.