Browsing by Author "Varkonyi-Koczy, A. R."
Now showing 1 - 5 of 5
Results Per Page
Sort Options
- Anytime information processing based on fuzzy and neural network modelsPublication . Varkonyi-Koczy, A. R.; Ruano, Antonio; Baranyi, P.; Takacs, O.In modern measurement and control systems, the available time and resources are often not only limited, but could change during the operation of the system. In these cases, the so-called anytime algorithms could be used advantageously. While diflerent soft computing methods are wide-spreadly used in system modeling, their usability in these cases are limited.
- Anytime models in fuzzy controlPublication . Varkonyi-Koczy, A. R.; Bencsik, Attila; Ruano, AntonioIn time critical applications, anytime mode of operation offers a way to ensure continuous operation and to cope with the possibly dynamically changing time and resource availability. Soft Computing, especially fuzzy model based operation proved to be very advantageous in power plant control where the high complexity, nonlinearity, and possible partial knowledge usually limit the usability of classical methods. Higher Order Singular Value Decomposition based complexity reduction makes possible to convert different classes of fuzzy models into anytime models, thus offering a way to combine the advantages, like low complexity, flexibility, and robustness of fuzzy and anytime techniques. By this, a model based anytime control methodology can be suggested which is able to keep on continuous operation using nonexact, approximate models of the plant, thus preventing critical breakdowns in the operation. In this paper, an anytime modeling method is suggested which makes possible to use complexity optimized fuzzy models in control. The technique is able to filter out the redundancy of fuzzy models and can determine the near optimal non-exact model of the plant considering the available time and resources. It also offers a way to improve the granularity (quality) of the model by building in new information without complexity explosion.
- Improving the diagnosis of ischemic CVA's through CT scan with neural networksPublication . Ribeiro, Luís; Ruano, Antonio; Ruano, M. Graça; Ferreira, P. M.; Varkonyi-Koczy, A. R.Technological and computing evolution promoted new opportunities to improve the quality of life, in particular, the quality of diagnostic evaluations. Computerized tomography is one of the imaging equipments of diagnosis which has most benefited from technological improvements. Because of that, and due to the quality of the diagnosis produced, it is one of the most employed equipments in clinical applications. The ischaemic cerebral vascular accident (ICVA) is the pathology that confirms the frequent use of the computerized tomography. The interest for this pathology, and in general for the encephalon image analysis as a preventive diagnosis, is mainly due to the frequent occurrence of ICVAs in development countries and its social-economic impact. In this sense, we propose to evaluate the ability of artificial neural networks (ANN) for automatic identification of ICVA by means of tissue density images obtained by computerised tomography. This work employed cranioencephalon computerised tomography exams and their respective medical reports, to train ANNs classifiers. Features extracted from the images were used as inputs to the classifiers. Once the ANNs were trained, the neural classifiers were tested with data never seen by the network. At this stage we may conclude that the ANNs may significantly contribute as an ICVAs computerised tomography diagnostic aid, since among the test cases the automatic identification of ischaemic lesions has been performed with no false negatives e very few false positives.
- Soft-computing-based car body deformation and EES determination for car crash analysis systemsPublication . Varkonyi-Koczy, A. R.; Rovisco, Ana; Ruano, M. GraçaCar body deformation modeling plays a very important role in crash accident analyses, as well as in safe car body design. The determination of the energy absorbed by the deformation and the corresponding energy equivalent speed can be of key importance; however, their precise determination is a very difficult task. Starting from the results of crash tests, intelligent and soft methods offer a way to model the crash process itself, as well as to determine the absorbed energy, the before-crash speed of the car, etc. In this paper, a modeling technique and an intelligent expert system are introduced, which, together, are able to follow the deformation process of car bodies in car crashes and analyze the strength of the different parts, which can significantly contribute to the improvement of the safety of car bodies.
- SVD based modeling of nonlinear systemsPublication . Varkonyi-Koczy, A. R.; Baranyi, P.; Ruano, Antonio; Gyori, S.; Petres, Z.; Legrady, P.Nowadays practical solutions of measurement and control problems involve model-integrated computing. Model based approaches offer a very challenging way to integrate a priori knowledge into the procedure. In this paper the applicability of the Higher Order Singular Value Decomposition based modeling is analyzed and a medical example, the modeling of the behavior of the human liver-bile system is introduced.