Mohd Najib B. Mohd Salleh

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The back propagation (BP) algorithm is a very popular learning approach in multilayer feedforward networks. However, the most serious problems associated with the BP are local minima problem and slow convergence speeds. Over the years, many improvements and modifications of the BP learning algorithm have been reported. In this research, we propose a new(More)
In some practical Neural Network (NN) applications, fast response to external events within enormously short time is highly demanded. However, by using back propagation (BP) based on gradient descent optimisation method obviously not satisfy in several application due to serious problems associated with BP which are slow learning convergence velocity and(More)
Spiking neural network (SNN) is considered as the third generation of artificial neural networks. Although there are many models of SNN, Evolving Spiking Neural Network (ESNN) is widely used in many recent research works. Evolutionary algorithms (EAs) have been used to optimize the ESNN, which has been used to solve the learning problems. In this paper, the(More)
This paper reports the empirical results that provide high return in planting material breeders in agriculture industry through effective policies of decision making. The analytical data about the rainfall pattern, soil structure of the planting crop will partition data by taking full advantage of the incomplete information to achieve better performance.(More)
Hybridization has become one of the current focuses of new research areas of the evolutionary algorithms over the past few years. Hybridization offers better speed of convergence to the evolutionary approach and better accuracy of the final solutions. This paper presents a hybrid non-dominated sorting genetic algorithm-II (NSGA-II) to optimize Three-Term(More)