World Knowledge for Control Applications

Bălaş, Marius M.; Balaş, Valentina E.

doi:10.1109/ines.2007.4283702

Cited by 5 publications

(1 citation statement)

References 4 publications

(7 reference statements)

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“…Two strategies are manifested when facing low quality data: one is to use supplementary resources (hardware [3], software, humans) in order to improve the data quality (for example the errors could be detected using hash functions [4] or corrected using cyclic redundancy check codes [5]). The other one is to use the supplementary resources in order to cope with the low quality of data -one such example is the struggle for resilient algorithms and data structures, able to tolerate some degree of errors in data without losses in correctness, performance and storage space [6,7].…”

Section: Introductionmentioning

confidence: 99%

On the resilience of an ant-based system in fuzzy environments. An empirical study

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2014

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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The current work describes an empirical study conducted in order to investigate the behavior of an optimization method in a fuzzy environment. MAX-MIN Ant System, an efficient implementation of a heuristic method is used for solving an optimization problem derived from the Traveling Salesman Problem (TSP). Several publicly-available symmetric TSP instances and their fuzzy variants are tested in order to extract some general features. The entry data was adapted by introducing a two-dimensional systematic degree of fuzziness, proportional with the number of nodes, the dimension of the instance and also with the distances between nodes, the scale of the instance. The results show that our proposed method can handle the data uncertainty, showing good resilience and adaptability.

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Section: Introductionmentioning

confidence: 99%