Graph multidimensional scaling with self-organizing maps
Information Sciences—Informatics and Computer Science: An International Journal
Gene clustering by using query-based self-organizing maps
Expert Systems with Applications: An International Journal
Mining data by query-based error-propagation
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Disease diagnosis using query-based neural networks
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
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In this paper, a three-layer force-directed self-organizing map is designed to resolve the circuit placement problem with arbitrarily shaped rectilinear modules. The proposed neural model with an additional hidden layer can easily model a rectilinear module by a set of hidden neurons to correspond the partitioned rectangles. With the collective computing from hidden neurons, these rectilinear modules can correctly interact with each other and finally converge to a good placement result. In this paper, multiple contradictory criteria are accounted simultaneously during the placement process, in which, both the wire length and the module overlap are reduced. The proposed model has been successfully exploited to solve the time consuming rectilinear module placement problem. The placement results of real rectilinear test examples are presented, which demonstrate that the proposed method is better than the simulated annealing approach in the total wire length. The appropriate parameter values which yield good solutions are also investigated