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This paper presents an original software implementation of the elitist non-dominated sorting genetic algorithm (NSGA-II) applied and adapted to the multi-objective optimization of a polysiloxane synthesis process. An optimized feed-forward neural network, modeling the variation in time of the main parameters of the process, was used to calculate the(More)
  • Florin Leon
  • 2012 IEEE 8th International Conference on…
  • 2012
In this paper, a new variant of a quantum-inspired evolutionary algorithm is proposed, which is characterised by a population-based elitism, a resetting mutation for the qubits, and an evolutionary hill-climbing phase at the end of the main search, meant to further improve the quality of the solution. The algorithm was applied for finding near-optimal(More)
This paper aims at designing some data mining methods of evaluating the seismic vulnerability of regions in the built infrastructure. A supervised clustering methodology is employed, based on k-nearest neighbor graphs. Unlike other classification algorithms, the method has the advantage of taking into account any distribution of training instances and also(More)
Organizational intelligence is the capability of an organization to create knowledge and to use it in order to strategically adapt to its environment. Intelligence of an organization is more than the aggregated intelligence of its members – it is an emergent property of the complex interactions of its subsystems and the way they are aggregated. Processes(More)
The optimal control policies for a polymerization process, particularly for the batch free radical polymerization of methyl methacrylate, have been determined using a multiobjective optimization technique. The process objectives considered in the optimization include monomer conversion, polydispersity index, polymerization degree and total reaction time,(More)
In this paper, we discuss the main issues concerning e-learning and its advantages over traditional instruction. We present a few possible implementation approaches and insist on the use of intelligent agents for e-learning. We propose a framework of intelligent agents with BDI architecture that can search server knowledge bases in order to investigate the(More)
A hybrid model for time series forecasting is proposed. It is a stacked neural network, containing one normal multilayer perceptron with bipolar sigmoid activation functions, and the other with an exponential activation function in the output layer. As shown by the case studies, the proposed stacked hybrid neural model performs well on a variety of(More)