In recent years, pattern recognition technologies for distributed optical fiber vibration sensing
have attracted more and more attention, aiming to intelligently recognize vibration events …

Intuitionistic fuzzy set (IFS) is a representative model of fuzzy theory, and it is widely used to
deal with fuzzy and uncertain problems in many practical applications. In IFS theory, the …

Supplier selection is a complex multiple criteria decision-making (MCDM) problem, which
considers a number of alternative suppliers as well as conflicting and noncommensurable …

It is doubtless that intuitionistic fuzzy set (IFS) theory plays an increasingly important role in
solving the problems under uncertain situation. As one of the most critical members in the …

The learning algorithm for multivariable data analysis (LAMDA) is a learning method to
group or classify quantitative and qualitative historical data. LAMDA can be applied for self …

This paper presents a soft computing technique for modeling and control of nonlinear
systems using the online learning criteria. In order to obtain an accurate modeling, and …

The learning algorithm and multivariable data analysis (LAMDA) is an algorithm to group
quantitative and qualitative data, applying self-learning and/or directed learning. Usually …

Similarity measure is an important uncertainty measurement in intuitionistic fuzzy set (IFS)
theory. In this study, a novel similarity measure is presented by the combination of the …

Changes in the arrangement of atoms in matter, known as structural phase transitions or
phase changes, offer a remarkable range of opportunities in photonics. They are exploited in …

To reduce water conservancy projects' negative effects on the ecological environment, in
this paper, a method is proposed to assess the impact of hydropower stations on the …