Ruhul Sarker

Ruhul Sarker received his Ph.D. in 1991 from DalTech, Dalhousie University, Halifax, Canada, and is currently a Senior Lecturer in Operations Research at the School of Computer Science, University of New South Wales, ADFA Campus, Canberra, Australia. Before joining at UNSW in February 1998, Dr Sarker worked with Monash University, Victoria, and the Bangladesh University of Engineering and Technology, Dhaka. His main research interests are Evolutionary Optimization, Data Mining and Applied Operations Research. He is currently involved with four edited books either as editor or co-editor, and has published more than 60 refereed papers in international journals and conference proceedings. He is also the editor of ASOR Bulletin, the national publication of the Australian Society for Operations Research.

Publications

How Hard Is It To Red Team?
How Hard Is It To Red Team?
Ang Yang, Hussein A. Abbass, Ruhul Sarker. © 2008. 25 pages.
Red teaming is the process of studying a problem by anticipating adversary behaviors. When done in simulations, the behavior space is divided into two groups: one controlled by...
Artificial Neural Networks: Applications in Finance and Manufacturing
Artificial Neural Networks: Applications in Finance and Manufacturing
Joarder Kamruzzaman, Ruhul Sarker. © 2008. 22 pages.
The primary aim of this chapter is to present an overview of the artificial neural network basics and operation, architectures, and the major algorithms used for training the...
Artificial Neural Networks in Finance and Manufacturing
Artificial Neural Networks in Finance and Manufacturing
Joarder Kamruzzaman, Rezaul Begg, Ruhul Sarker. © 2006. 299 pages.
Two of the most important factors contributing to national and international economy are processing of information for accurate financial forecasting and decision making as well...
Neural Networks in Healthcare: Potential and Challenges
Neural Networks in Healthcare: Potential and Challenges
Rezaul Begg, Joarder Kamruzzaman, Ruhul Sarker. © 2006. 332 pages.
Healthcare costs around the globe are on the rise, creating a strong need for new ways of assisting the requirements of the healthcare system. Besides applications in other...
How Hard Is It To Red Team?
How Hard Is It To Red Team?
Ang Yang, Hussein A. Abbass, Ruhul Sarker. © 2006. 33 pages.
Red teaming is the process of studying a problem by anticipating adversary behaviors. When done in simulations, the behavior space is divided into two groups: one controlled by...
Artificial Neural Networks: Applications in Finance and Manufacturing
Artificial Neural Networks: Applications in Finance and Manufacturing
Joarder Kamruzzaman, Ruhul A. Sarker. © 2006. 27 pages.
The primary aim of this chapter is to present an overview of the artificial neural network basics and operation, architectures, and the major algorithms used for training the...
Simultaneous Evolution of Network Architectures and Connection Weights in Artificial Neural Networks
Simultaneous Evolution of Network Architectures and Connection Weights in Artificial Neural Networks
Ruhul A. Sarker, Hussein A. Abbass. © 2006. 15 pages.
Artificial Neural Networks (ANNs) have become popular among researchers and practitioners for modeling complex real-world problems. One of the latest research areas in this field...
Modeling and Prediction of Foreign Currency Exchange Markets
Modeling and Prediction of Foreign Currency Exchange Markets
Joarder Kamruzzaman, Ruhul A. Sarker, Rezaul K. Begg. © 2006. 13 pages.
In today’s global market economy, currency exchange rates play a vital role in national economy of the trading nations. In this chapter, we present an overview of neural...
Overview of Artificial Neural Networks and their Applications in Healthcare
Overview of Artificial Neural Networks and their Applications in Healthcare
Joarder Kamruzzaman, Rezaul Begg, Ruhul Sarker. © 2006. 19 pages.
Artificial neural network (ANN) is one of the main constituents of the artificial intelligence techniques. Like in many other areas, ANN has made a significant mark in the domain...
Solving Two Multi-Objective Optimization Problems Using Evolutionary Algorithm
Solving Two Multi-Objective Optimization Problems Using Evolutionary Algorithm
Ruhul A. Sarker, Hussein A. Abbass, Charles S. Newton. © 2003. 16 pages.
Being capable of finding a set of pareto-optimal solutions in a single run is a necessary feature for multi-criteria decision making, Evolutionary algorithms (EAs) have attracted...
Data Mining: A Heuristic Approach
Data Mining: A Heuristic Approach
Hussein A. Abbass, Ruhul Sarker, Charles S. Newton. © 2002. 310 pages.
Real life problems are known to be messy, dynamic and multi-objective, and involve high levels of uncertainty and constraints. Because traditional problem-solving methods are no...
Heuristic and Optimization for Knowledge Discovery
Heuristic and Optimization for Knowledge Discovery
Hussein A. Abbass, Charles S. Newton, Ruhul Sarker. © 2002. 296 pages.
With the large amount of data stored by many organizations, capitalists have observed that this information is an intangible asset. Unfortunately, handling large databases is a...