Saratha Sathasivam

Learn More
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)
There are two ways to calculate synaptic weights for neurons in logic programming. There are by using Hebbian learning or by Wan Abdullah's method. Hebbian learning for governing events corresponding to some respective program clauses is equivalent with learning using Wan Abdullah's method for the same respective program clauses. We will evaluate(More)
Abduction is the process of proceeding from data describing a set of observations or events, to a set of hypotheses which best explains or accounts for the data. Most of the work on abduction has been done using a logical or a probabilistic approach. In this paper, we describe logic recognition as application of this abduction underlying logic to identify(More)
Neural networks are becoming very popular with data mining practitioners because they have proven through comparison their predictive power with statistical techniques using real data sets. Based on this idea, we will present a method for inducing logical rules from empirical data—Reverse Analysis. When the values of the connections of a neural network(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)
In this study, a quadratic regression model (QRM) and a cascade forward backpropagation neural network (CFBN) are jointly integrated together to form a hybrid model called the new hybrid quadratic regression method and cascade forward backpropagation neural (QRM-CFBN) network method. The new hybrid method was tested on a daily time series data obtained from(More)