Intuitionistic Fuzzy Similarity Measures and Their Role in Classification

Abstract

We present some similarity and distance measures between intuitionistic fuzzy sets (IFSs). Thus, we propose two semi-metric distance measures between IFSs. The measures are applied to classification of shapes and handwritten Arabic sentences described with intuitionistic fuzzy information. The experimental results permitted to do a comparative analysis between intuitionistic fuzzy similarity and distance measures, which can facilitate the selection of such measure in similar applications.

On Integration Linguistic Factors to Fuzzy Similarity Measures and Intuitionistic Fuzzy Similarity Measures

“…Thelastcolumnindicates3classesof50instanceseach(Setosa,VersicolourandVirginica),where eachclassisatypeofIrisplants.Here,weusesomesimilarity-basedclassificationalgorithms(ours ILVS algorithm; our FLVS algorithm; intuitionistic-fuzzy-similarity-measure-based classification algorithm, IFS (Baccour & Alimi 2016); fuzzy-linguistic-similarity-measure-based classification algorithm,FS(Baccour&Alimi2014))toclassifythetypeoftheseplants.…”

Taylor-based Optimized Recursive Extended Exponential Smoothed Neural Networks Forecasting Method

“…Hence, our goal is to understate the error E in order to adjust the network's connection weights and update them according to (10).…”

“…w ij (t + 1) = w ij (t) + w ij (10) In the same way, all connection strengths in JRNN architecture are so updated. In our study, to approximate the value of a function, we considered recursive architecture inspired from the Exponential Smoothed (ES) method [35] which is a statistical forecasting technique.…”

“…We often forecast weather [1][2][3] [4], wind speed [5] [6], word speech recognition [7], image recognition [8][9] [10][11] [12], face recognition [13], writer identi cation [14], stock market [15], electricity [16][17] [18][19] [20], etc. Meanwhile, forecasting literature contains a wide diversity of techniques that can be organized into two main families [20] [21]:…”