International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems

Atanassov’s intuitionistic fuzzy sets (AIFSs), characterized by a membership function, a non-membership function, and a hesitancy function, is a generalization of a fuzzy set. There are various intuitionistic fuzzy hybrid weighted aggregation operators to deal with multi-attribute decision making problems which consider the importance degrees of the arguments and their ordered positions simultaneously. However, these existing hybrid weighed aggregation operators are not monotone with respect to the total order on intuitionistic fuzzy values (AIFVs), which is undesirable. Based on the Łukasiewicz triangular norm, we propose an intuitionistic fuzzy hybrid weighted arithmetic mean, which is monotone with respect to the total order on AIFVs, and therefore is a true generalization of such operations. We give an example that a company intends to select a project manager to illustrate the validity and applicability of the proposed aggregation operator. Moreover, we extend this kind of hybrid weighted arithmetic mean to the interval-valued intuitionistic fuzzy environments.

Recently, the α-migrativity has been discussed in families of certain operations (e.g., triangular norms, conorms, uninorms, and nullnorms). In this paper, the migrative property for semi-t-operators is studied. All solutions of the migrativity equation for all possible combinations of semi-t-operators are analyzed and characterized.

Along with the development of the modern science and technology, people face a lot of data in different areas of production and life. In dealing with these data which include many indeterminant factors, we can use the multifactor uncertain system to describe a dynamical system with uncertain noises. Optimal control problem is an important research topic which aims at finding the optimal strategy in a dynamical system. In this paper, we consider the optimal control problem for the multifactor uncertain system with two evaluation criterions. Then a two person zero sum differential game model in a multifactor uncertain system is discussed. Finally, as an application, our result is used to solve an uncertain portfolio game model.

We consider the relations between some properties of the certainty equivalent and the form of a utility function under Cumulative Prospect Theory.

We apply a non-classical four-valued logic in the process of reasoning regarding strategies for cops in a modified game of “Cops and Robber” played on a graph. We extend the game by introducing uncertainty in a form of random failures of detecting devices. This is realized by allowing that a robber can be detected in a node only with the given probability P_A. Additionally, with the probability P_F, cops can be given a false-positive, i.e., they are informed that the robber is located at some node, whereas it is located somewhere else. Consequently, non-zero P_F introduces a measurement noise into the system. All the cops have access to information provided by the detectors and can communicate with each other, so they can coordinate the search. By adjusting the number of detectors, P_A, and P_F we can achieve a smooth transition between the two well-known variants of the game: “with fully visible robber” and “with invisible robber”. We compare a simple probabilistic strategy for cops with the non-parametric strategy based on reasoning with a four-valued paraconsistent logic. It is shown that this novel approach leads to a good performance, as measured by the required mean catch-time. We conclude that this type of reasoning can be applied in real-world applications where there is no knowledge about the underlying source of errors which is particularly useful in robotics.

Recommender systems analyze conditions and user behaviors to recommend proportional services to users. Since the aim of such systems is to provide the most appropriate services, it appears essential to use filtering techniques to limit recommender items. In this study, spatial criteria such as distance, movement direction, visibility, and topological relationships were employed as filtering tools to provide the right items. Our model creates appropriate items for better recommendation based on spatial relationships between users and the surrounding service sites. This method demonstrates that the number of recommended items can be limited by considering the shortest distance from the service centers intended by users and taking user direction into account. Moreover, appropriate service centers can be proposed with respect to user visibility. In this study, topological relationships between user location and near places were used as spatial filters, too. Further, if these filters can interact with the environment in the same way as humans, it can be expected the recommendation process to improve. Thus, our model uses the fuzzy approach to help the system to perceive the uncertainty of the spatial linguistic terms. To evaluate the performance and effectiveness of our proposed spatial filtering model, we conduct several experiments on real datasets that were obtained from tracking the users’ location through GPS. Considering the actual conditions, this system solved the cold start problem using spatial filtering model. Experimental results show that 68% of test users considered our recommendations as relevant in new item cold start problem. Moreover, results reveal that compared with an LA-LDA model, using spatial filtering in cold start item problem is more robust.

This paper provides an introduction to how, on the basis of concepts from fuzzy logic, a model of asset allocation can be constructed which can represent and aggregate all the relevant quantitative and qualitative features of an investment plan realistically and in this way attains comparatively good recommendations like an expert. All calculation steps are carried out in a transparent and reproducible manner. In order to clarify the approach and the advantages of the procedure, a pilot model is developed. This supports the advisor with the asset allocation, by first analysing the features of the investment goal and the market expectations and then evaluating the merits of several investment strategies as well as displaying the steps towards their evaluation in a comprehensible manner. Based on case studies, the results of the pilot model are compared with known good recommendations from an investigation of Stiftung Warentest on the quality of advice in banks.

Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA.