Learn More
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)
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)
An important issue in many multiagent systems is the way in which agents can be coordinated in order to perform different roles. This paper proposes a method by which the agents can self-organize based on the changes of their individual utilities. We assume that the tasks given to the agents have a number of attributes and complexity levels, and that the(More)
In this paper, three methods for developing the optimal topology of feed-forward artificial neural networks are described and applied for modeling a complex polymerization process. In the free radical polymerization of styrene, accompanied by gel and glass effects, the monomer conversion and molecular masses are modeled depending on reaction conditions. The(More)
—Data Mining is the process of extraction of interesting (non-trivial, implicit, previously unknown and potentially useful) information or patterns from data in large databases. Agents are defined as software or hardware entities that perform some set of tasks on behalf of users with some degree of autonomy. In order to work for somebody as an assistant, an(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)
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)