International Journal of Knowledge-based and Intelligent Engineering Systems 

About: International Journal of Knowledge-based and Intelligent Engineering Systems is an academic journal published by IOS Press. The journal publishes majorly in the area(s): Fuzzy logic & Computer science. It has an ISSN identifier of 1327-2314. Over the lifetime, 488 publications have been published receiving 3268 citations. The journal is also known as: International journal of knowledge-based and intelligent engineering systems & Knowledge-based intelligent Engineering Systems.

Pythagorean fuzzy Hamacher aggregation operators and their application to multiple attribute decision making

Abstract: In this paper, we utilize Hamacher operations to develop some Pythagorean fuzzy aggregation operators: Pythagorean fuzzy Hamacher weighted average (PFHWA) operator, Pythagorean fuzzy Hamacher weighted geometric (PFHWG) operator, Pythagorean fuzzy Hamacher ordered weighted average (PFHOWA) operator, Pythagorean fuzzy Hamacher ordered weighted geometric (PFHOWG) operator, Pythagorean fuzzy Hamacher hybrid average (PFHHA) operator and Pythagorean fuzzy Hamacher hybrid geometric (PFHHG) operator. The prominent characteristic of these proposed operators are studied. Then, we have utilized these operators to develop some approaches to solve the Pythagorean fuzzy multiple attribute decision making problems. Finally, a practical example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

The world of independent learners is not markovian

Abstract: In multi-agent systems, the presence of learning agents can cause the environment to be non-Markovian from an agent's perspective thus violating the property that traditional single-agent learning methods rely upon. This paper formalizes some known intuition about concurrently learning agents by providing formal conditions that make the environment non-Markovian from an independent (non-communicative) learner's perspective. New concepts are introduced like the divergent learning paths and the observability of the effects of others' actions. To illustrate the formal concepts, a case study is also presented. These findings are significant because they both help to understand failures and successes of existing learning algorithms as well as being suggestive for future work.

Dynamic route planning for car navigation systems using virus genetic algorithms

Abstract: This paper describes a practical dynamic route planning method using real road maps in a wide area. The maps include traffic signals, road classes, and the number of lanes. The proposed solution is using a genetic algorithm adopting viral infection. The method is to use viruses as domain specific knowledge. A part of an arterial road is regarded as a virus. A population of viruses is generated in addition to a population of routes. Crossover and infection determine the near-optimal combination of viruses. When traffic congestion frequently changes during driving, an alternative route can be selected using viruses and other routes in the population in a real time. Experiments in dynamic environments using a real road map with 28000 cars show that the proposed method is superior to the Dijkstra algorithm for use in practical car navigation devices.

Approaches to multiple attribute group decision making based on the generalized Dice similarity measures with intuitionistic fuzzy information

Abstract: The intuitionistic fuzzy set is characterized by two functions expressing the degree of membership and the degree of non-membership. It was proposed as a generalization of a fuzzy set in order to deal with indeterminate and inconsistent information. In this work, we shall present some novel Dice similarity measures of intuitionistic fuzzy sets and the generalized Dice similarity measures of intuitionistic fuzzy sets and indicates that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures-based multiple attribute group decision making models with intuitionistic information. Then, we apply the generalized Dice similarity measures between intuitionistic fuzzy sets to multiple attribute group decision making. Finally, an illustrative example is given to demonstrate the efficiency of the similarity measures for selecting the desirable ERP system.