Simulations and wargames offer powerful representations to model the mechanics and psychology of military operations that are inherently complex. They offer mechanisms to predict and assess the effectiveness of the mission plans and operations in achieving the military objectives. In this paper, we present a new approach to design the games rules of wargames using fuzzy rule bases, for quantita...

The problem of data association for target tracking in a cluttered environment is discussed. In order to deal with the problem of data association for real time target tracking, a novel data association method based on maximum entropy fuzzy clustering is proposed. Firstly, the candidate measurements of each target are clustered with the aid of the modified maximum entropy fuzzy clustering. Then...

In this paper a predictive controller for real-time target tracking in mobile robotics is proposed based on adaptive/evolving Takagi-Sugeno fuzzy systems, eTS. The predictive controller consists of two modules; i) a conventional fuzzy controller for robot motion control, and ii) a modelling tool for estimation of the target movements. The prediction of target movements enables the controller to...

In this paper a new fuzzy based approach for improving network coverage in wireless mobile sensor networks is proposed. In the proposed approach firstly each mobile sensor node determines its neighbors and its distance from borders and obstacles. According to these values, fuzzy inference engine calculates the priority of node for movement. Then according to the priority, in turn, nodes move aw...

Using fuzzy set theory, we present a fuzzy rule-based algorithm to perform contrast enhancement for digital mammography breast masses. Compared to the well-known histogram equalization enhancement technique, fuzzy rule-based enhancement is able to represent knowledge in a comprehensible way. Four measures of quantifying enhancement in digital mammograms have been introduced. Each measure is bas...

A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifies numerous temporal association rules that occur more frequently in areas of a dataset with specific quantitative values represented with fuzzy sets. The novelty of this research lies in exploring the composition of qu...

This paper proposes modifications to current fuzzy models of gene interaction. Current algorithms apply all combinations of genes to a fuzzy model (i.e. activator/repressor/target), evaluating how well each combination fits the model. The models are susceptible to noisy signals in the gene expression data. Since the margin of error in current microarray technology can be high, the results gener...

This paper considers the fuzzy inference as position estimator for WLAN indoor environments, based on received signal strength measurements RSS. The proposal algorithm includes a fuzzy inference which uses the k-nearest neighbor classification in signal space, where the position of target node is calculated as a weighted combination of nearest fingerprints, where the weights are estimated using...

This paper considers computational methods for obtaining Stackelberg solutions to random fuzzy twolevel linear programming problems. Assuming that the decision makers concerns about the probabilities that their own objective function values are smaller than or equal to certain target values, fuzzy goals of the decision makers for the probabilities are introduced. Using the possibility-based pro...

To optimize telecom service management, it is necessary that information about telecom services is highly related to the most popular telecom service. To this end, we propose an algorithm for mining targetoriented fuzzy correlation rules. In this paper, we show that by using the fuzzy statistics analysis and the data mining technology, the target-oriented fuzzy correlation rules can be obtained...