This is the second of two issues dedicated to the design and applications of intelligent systems. It contains seven papers from universities and research establishments. These papers reflect the recent trend of using techniques such as expert systems, fuzzy logic, neural networks and genetic algorithms in designing intelligent systems in many fields including business, engineering and science.
The first paper (invited) by Sanchez describes the design of a class of RBF networks. A new learning technique is presented in this paper.
The second paper by Alpaslan and Swigger is on a connectionist expert system using a temporal neural network mode. This paper reports the development of a temporal neural network and backpropagation based temporal learning algorithm.
The third paper by Kottathra and Attikiouzel presents an algorithm to determine the number of neurons in the hidden layer of multilayer feedforward neural networks. The fourth paper, by Ashiru, Czarnecki and Routen presents an intelligent path planning algorithm for mobile robots operating in cluttered environments. This algorithm is validated using three scenarios of increasing complexity.
The fifth paper, by Ceden Λo and Vemuri (invited) presents the use of multi niche crowding genetic algorithm to decide the optimal location of pumping wells in aquifer management.
The sixth paper, by Hunt and Cooke (invited), presents the application of an artificial immune system to promote recognition in DNA sequences. A number of other application areas are also presented. The last paper by Medsker presents an overview of microcomputer applications of hybrid intelligent systems.
I am grateful to M. J. Taylor for the opportunity to edit this special issue on intelligent systems. I would like to express my appreciation to all the reviewers for their time, efforts and technical advice.