Abstract: Fuzzy clustering is an efficient tool for unsupervised data analysis, but its performance is often degraded by redundant information and outliers. To solve this issue for boosting clustering ...

In order to accurately describe the impact of the volatility and randomness of renewable energy output power on the operation of industrial park microgrids, a data-driven robust optimization method ...

Abstract: This paper introduces a novel multi-optimum programming mode for the particle swarm optimization algorithm. Initially, to efficiently control the relationship between multi-optimum ...

With the increasing integration of a high proportion of renewable energy, the fluctuation characteristics of distributed power generation such as wind and photovoltaic energy affect the safe and ...

Department of Sustainable Development and Ecological Transition, Università del Piemonte Orientale, Piazza Sant’Eusebio 5, Vercelli 13100, Italy ...

ABSTRACT: This study presents a new approach that advances the algorithm of similarity measures between generalized fuzzy numbers. Following a brief introduction to some properties of the proposed ...

ABSTRACT: In this paper, the statistical averaging method and the new statistical averaging methods have been used to solve the fuzzy multi-objective linear programming problems. These methods have ...