A review on fuzzy preference modeling methods for group decision-making

With the rise of group decision-making and the increasingly complex decision-making environment, preference modeling for decision makers has become more and more important, and many preference modeling methods have emerged. Based on the fuzzy theory, researchers have proposed a large number of preference models to express the subjective uncertainty of decision makers. These methods based on fuzzy theory are collectively referred to as fuzzy preference modeling methods. The fuzzy sets preference model is the first practice of fuzzy theory used in the field of preference modeling, and it is still widely used by researchers until now. Subsequently, based on fuzzy theory, the researchers also proposed linguistic term sets and cloud model. These methods have different representation domains, and are applicable to different decision-making environment. In this paper we give a review of classical fuzzy preference modeling methods and its latest extensions and variants. After the presentation of comparative analyses on the existing methods, we figure out some current challenges and possible future development directions in the field of fuzzy preference modeling.

South East Asia’s Megalodon Shark First Record and Habitat Preference Modeling During Miocene Period (20 Ma) and Winter Monsoon Impacts in South Coast of West Java

Otodus megalodon is known as the biggest shark ever alive and recent records show this species was only existed in America, Africa and Europe continents in the last Miocene period 20 million years ago (Ma). Recently, megalodon teeth have been discovered in South coast of West Java. Here this study aims to present and model the presence of O. megalodon. The length of the excavated tooth was ranging from 13 to 19 cm. The lithological analysis shows that the tooth was found in Miocene rock layers. Paleogeographic model shows that during Miocene southern parts of Java island were submerged including the recent locations where the megalodon tooth have been found. Half parts of the modeled West Java were an ocean with depth ranging from 0 to 200 m. High habitat use preferences by juvenile megalodon were estimated in the shelf (depth 0-40 m) with the size of 1365 km2 . Whereas habitat use preference by adult megalodon was low at this depth. Both juvenile and adult habitat use frequencies were low at a depth of between 80 m and 160 m. Habitat use preferences were increasing at a depth of > 200 m. After Miocene, the paleoclimate records show a decline in temperature and lead to the decline of whale population in ocean. The declining of megalodon’s prey explains the declining of this giant shark especially in post Miocene and early Pliocene periods.

Modeling Imprecise and Bipolar Algebraic and Topological Relations using Morphological Dilations

In many domains of information processing, such as knowledge representation, preference modeling, argumentation, multi-criteria decision analysis, spatial reasoning, both vagueness, or imprecision, and bipolarity, encompassing positive and negative parts of information, are core features of the information to be modeled and processed. This led to the development of the concept of bipolar fuzzy sets, and of associated models and tools, such as fusion and aggregation, similarity and distances, mathematical morphology. Here we propose to extend these tools by defining algebraic and topological relations between bipolar fuzzy sets, including intersection, inclusion, adjacency and RCC relations widely used in mereotopology, based on bipolar connectives (in a logical sense) and on mathematical morphology operators. These definitions are shown to have the desired properties and to be consistent with existing definitions on sets and fuzzy sets, while providing an additional bipolar feature. The proposed relations can be used for instance for preference modeling or spatial reasoning. They apply more generally to any type of functions taking values in a poset or a complete lattice, such as L-fuzzy sets.