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This study investigates the use of Genetic Algorithms (GA) to the design and implementation of Fuzzy Logic Controllers (FLC). A fuzzy logic is fully defined by its membership function. What is the best to determine the membership function is the first question that has been tackled. Thus it is important to select the accurate membership functions but these methods possess one common weakness where...
This paper presents a study on method to develop student model by identifying the students' characteristics in an adaptive hypermedia learning system. The study involves the use of student profiling techniques to identify the features that may be useful to help the researchers have a better understanding of the student in an adaptive learning environment. We propose a supervised Kohonen network with...
In this paper, an adaptive evolutionary multi-objective selection method of RBF Networks structure is discussed. The candidates of RBF Network structures are encoded into particles in Particle Swarm Optimization (PSO). These particles evolve toward Pareto-optimal front defined by several objective functions with model accuracy and complexity. The problem of unsupervised and supervised learning is...
As the widespread modus operandi in real applications, backpropagation(BP) in recurrent neural networks (RNN) is computationally more powerful than standard feedforward neural networks. In principle, RNN can implement almost any arbitrary sequential behavior. However, there are many drawbacks in BP network, for instance, confinement in finding local minimum and may get stuck at regions of a search...
In conventional RBF Network structure, different layers perform different tasks. Hence, it is useful to split the optimization process of hidden layer and output layer of the network accordingly. This study proposes hybrid learning of RBF Network with Particle Swarm Optimization (PSO) for better convergence, error rates and classification results. The hybrid learning of RBF Network involves two phases...
Grey relational analysis (GRA) has been widely applied in analysing multivariate time series data (MTS). It is an alternate solution to the traditional statistical limitations. GRA is employed to search for grey relational grade (GRG) which can be used to describe the relationships between the data attributes and to determine the important factors that significantly influence some defined objectives...
This work introduces a new method for surface reconstruction based on hybrid soft computing techniques: Kohonen network and particle swarm optimization (PSO). Kohonen network learns the sample data through mapping grid that can grow. The implementation is executed by generating Kohonen mapping framework of the data subsequent to the learning process. Consequently, the learned and well-represented...
Despite a variety of artificial neural network (ANN) categories, backpropagation network (BP) and Elman recurrent network (ERN) are the widespread modus operandi in real applications. However, there are many drawbacks in BP network, for instance, confinement in finding local minimum and may get stuck at regions of a search space or trap in local minima. To solve these problems, various optimization...
In this paper, we show that temporal logic can be learnt effectively by a connectionist system. In contrast with other connectionist approaches in this context, we focus more on learning rather than knowledge representation. In order to learn from temporal logic values, the paper proposes a general three-layer connectionist system regardless of the number of logic rules, a condition which must have...
Non-rigid solid object deformations techniques have been widely used in the computer graphics community to simulate and animate deformable objects. Both offline and real time applications have already benefited from deformation techniques evolutions. This paper discusses the most popular geometric deformation techniques used for both real time and offline applications such as virtual surgery and motion...
The shape of a NURBS curve or surface is defined by the location of its control points, the control points' weights, and the knot vectors. Most of the curve and surface design tried to modify the control points. However, it is still impossible to obtained accurate control points for a reconstructed NURBS curve or surface. The fitness of these surfaces is generally considered a subjective notion depending...
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