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- Nawaf Hamadneh, Saratha Sathasivam, Ong Hong Choon
- 2011

Intelligent systems are yielded from integration of a logic programming and connectionist systems. Radial basis function neural network is a commonly-used type of feedforward networks. In this paper, we proposed a method for connectionist model generation using Radial Basis Function neural network to encode higher order logic programming. We encode each… (More)

Knowledge could be gained from experts, specialists in the area of interest, or it can be gained by induction from sets of data. Automatic induction of knowledge from data sets, usually stored in large databases, is called data mining. Data mining methods are important in the management of complex systems. There are many technologies available to data… (More)

Particle swarm optimization (PSO) is employed to investigate the overall performance of a pin fin.The following study will examine the effect of governing parameters on overall thermal/fluid performance associated with different fin geometries, including, rectangular plate fins as well as square, circular, and elliptical pin fins. The idea of entropy… (More)

- Saratha Sathasivam, Ng Pei Fen
- 2012

In recent studies on artificial intelligence, logic program occupies a significant position because of its attractive features. Neural networks are dynamic systems in the learning and training phase of their operation and convergence is an essential feature, so it is necessary for the researchers developing the models and their learning algorithms to find a… (More)

The logic of abduction and deduction contribute to our conceptual understanding of a phenomenon, while the logic of induction adds quantitative details to our conceptual knowledge. In this paper, we will look into how this reasoning techniques-abduction, deduction and induction, are relevant in neural networks logic programming. Deduction simplifies the… (More)

This paper presents an improved technique for accelerating the process of doing logic programming in discrete Hopfield neural network by integrating fuzzy logic and modifying activation function. Generally Hopfield networks are suitable for solving combinatorial optimization problems and pattern recognition problems. However Hopfield neural networks also… (More)