The Fuzzy Logic or the Fuzzy Logic Control is an Artificial Intelligence approach/technique, which is especially used for designing and developing intelligent controlling systems. It provides an effective and efficient method to simulate the human thinking and behaviors in order to ensure the related intelligent controlling structure. In this context, this paper introduces the FL-LAB v2: a soft...

This paper presents a methodological approach for the application of virtual prototyping for the evaluation of the intelligent vehicle active suspension system performance. In this approach, a full passenger car model is developed using ADAMS software. In the modeling approach, not only the suspension components are precisely modeled, but also modeling of all systems like steering systems that ...

A supply chain (SC) distribution network design model is developed in this paper. The goal of the model is to select the optimum numbers, locations and capacity levels of plants and warehouses to deliver products to retailers at the least cost while satisfying desired service level to retailers. A maximal covering approach is used in statement of the service level. The model distinguishes itsel...

In this paper, a new notion called fuzzy relevance feedback in interactive content-based image retrieval (CBIR) systems is introduced. Conventional binary labeling scheme requires a crisp decision to be made on the relevance of the retrieved images. However, user interpretation varies with respect to different information needs and perceptual subjectivity. In addition, users tend to learn from ...

The development of adaptive user interfaces (UI) presents for a long time an important research area in which researcher attempt to call upon the full resources and skills of several disciplines, The adaptive UI community holds a thorough knowledge regarding the adaptation of UIs with users and with contexts of use. Several solutions, models, formalisms, techniques and mechanisms were proposed ...

This paper presents a new framework called fuzzy relevance feedback in interactive content−based image retrieval (CBIR) systems based on soft−decision. An efficient learning approach is proposed using a fuzzy radial basis function network (FRBFN). Conventional binary labeling schemes require a crisp decision to be made on the relevance of the retrieved images. However, user interpretation varie...

Abstract.With respect to interval-valued hesitant fuzzy multi-attribute decision making, this study first presents a new ranking method for interval-valued hesitant fuzzy elements. In order to obtain the comprehensive values of alternatives, two induced generalized interval-valued hesitant fuzzy hybrid operators based on the Shapley function are defined, which globally consider the importance o...

Most conflicts in collaborative design are categorized as the problem of fuzzy multiple attributive group decision-making (FMAGDM). Both fuzzy assessments and the aggregation of multiple experts' opinions should be considered in the conflict resolution process. This paper presents a new approach for the problem, where cooperation degree (CD) and reliability degree (RD) are introduced for aggreg...

One of the primary differences between humans and other animals is our capacity for high level cognition and the use of language. Historically, AI has understandably focused on duplicating these aspects of human behavior, and selected its architectures accordingly. However, humans are nevertheless social mammals and share a large part of the mammalian behavior repertoire, such as feeding, as we...