In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...

Today, urban transportation has attracted urban planners’ and researchers' attention because of air and noise pollution problems associated with it. In Shahrkord city in Iran, no plans have been made for sustainable transportation, and the available poor transportation infrastructure is not responsive to the growing population of the city. This issue has inflicted the city with serious problems...

Here in this article, a hybrid MCDM method on the Pythagorean fuzzy-environment is presented. This based Fuzzy Method Removal Effects of Criterion (PF-MEREC) and Stepwise Weight Assessment Ratio Analysis (SWARA) approaches. Here, objective subjective weights are assessed by PF-MEREC, SWARA model preference order ranking various alternatives done through Complex Proportional (COPRAS) framework f...

In this ever changing business scenario, success of the company lies in understanding the customer preferences, tastes and anticipating the changes required in existing or new products being offered. It was desired to develop a model which allows decision makers to decompose a complex problem in a hierarchical structure to show the relationship of the goals, objectives, criteria and alternative...

Page Title 1 Overview − hierarchical models 2 Calf mortality data 3 Hierarchical regression models 4 Hierarchical survival models: general approaches 5 Calf mortality data: multi-level Cox model 6 Methods for hierarchical Cox models 7 Pig lameness data 8 Pig data: hypothesis and first results 9 Pig data: Cox random slope models 10 Pig data: parametric models 11 Proportional hazards revisited 12...

This article describes a new method and approch of texture characterization. Using complex network representation of an image, classical and derived (hierarchical) measurements, we presente how to have good performance in texture classification. Image is represented by a complex networks : one pixel as a node. Node degree and clustering coefficient, using with traditionnal and extended hierarch...

This article describes a new method and approach of texture characterization. Using complex network representation of an image, classical and derived (hierarchical) measurements, we present how to have good performance in texture classification. Image is represented by a complex networks : one pixel as a node. Node degree and clustering coefficient, using with traditional and extended hierarchi...

Proposing a hierarchical group compromise method can be regarded as a one of major multi-attributes decision-making tool that can be introduced to rank the possible alternatives among conflict criteria. Decision makers’ (DMs’) judgments are considered as imprecise or fuzzy in complex and hesitant situations. In the group decision making, an aggregation of DMs’ judgments and fuzzy group compromi...

Many phenomena in nature have dominant spatial directions along which the essential dynamics occur. Examples are blood flow problems, fluid dynamics in pipes or river beds, and subsurface flow. Motivated by a project on adaptive hydrological modelling of coupled hydrological processes [2] we started to investigate a new dimensional reduction approach [5, 7] for problems with dominant direction ...