An introduction to database systems: vol. I (4th ed.)
An introduction to database systems: vol. I (4th ed.)
Understanding the new SQL: a complete guide
Understanding the new SQL: a complete guide
A General Framework for Concurrent Simulation on Neural Network Models
IEEE Transactions on Software Engineering
A relational model of data for large shared data banks
Communications of the ACM
Neural Networks and Knowledge Engineering
IEEE Transactions on Knowledge and Data Engineering
A cloud-based neural network simulation environment
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
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Many different approaches for the modeling of neural networks were presented in the literature (e.g. [4]). Generally the object-oriented approach proved itself as most appropriate. It provides a concise but comprehensive framework for the design of neural networks in terms of its static and dynamic components, i.e. the information structure and its methods in the object-oriented notion.This paper presents a framework for the conceptual and physical integration of neural networks into object-relational database systems. The static components comprise the structural parts of a neural network, as the neurons and connections, higher topological structures as layers, blocks and network systems. The dynamic components are the behavioral characteristics, as the creation, training and evaluation of the network. Finally the implementation of the new NeuroOraclesystem based on the proposed framework is presented.