Artificial Neural Networks in Finance and Manufacturing

• #1. Artificial Neural Networks: Applications in Finance and Manufacturing
• #2. Simultaneous Evolution of Network Architectures and Connection Weights in Artificial Neural Networks
• #3. Neural Network-Based Stock Market Return Forecasting Using Data Mining for Variable Reduction
• #4. Hybrid-Learning Methods for Stock Index Modeling
• #5. Application of Higher-Order Neural Networks to Financial Time-Series Prediction
• #6. Hierarchical Neural Networks for Modelling Adaptive Financial Systems
• #7. Forecasting the Term Structure of Interest Rates Using Neural Networks
• #8. Modeling and Prediction of Foreign Currency Exchange Markets
• #9. Improving Returns on Stock Investment through Neural Network Selection
• #10. Neural Networks in Manufacturing Operations
• #11. High-Pressure Die-Casting Process Modelling Using Neural Networks
• #12. Neural Network Models for the Estimation of Product Costs: An Application in the Automotive Industry
• #13. A Neural-Network-Assisted Optimization Framework and Its Use for Optimum-Parameter Identification
• #14. Artificial Neural Networks in Manufacturing: Scheduling
• #15. Recognition of Lubrication Defects in Cold Forging Process with a Neural Network

Dr. Joarder Kamruzzaman received his B.Sc and M.Sc. in Electrical and Electronic Engineering from Bangladesh University of Engineering & Technology, Dhaka, Bangladesh in 1986 & 1989 respectively, and PhD in Information Systems Engineering from Muroran Institute of Technology, Japan in 1993. Currently he is a faculty member in the Faculty of Information Technology, Monash University, Australia. His research interest includes computational intelligence, computer networks and bioinformatics. He has published more than 90 refereed papers in international journals and conference proceedings. He is currently serving as a program committee member of a number of international conferences.

Dr. Rezaul Begg received the B.Sc. and M.Sc. Eng degrees in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh, and the Ph.D. degree in Biomedical Engineering from the University of Aberdeen, U.K. Currently he is a Faculty member at Victoria University, Melbourne, Australia. Previously, he worked with Deakin University and BUET. He researches in Biomedical Engineering, Biomechanics and Machine Learning areas, and has published over 100 research papers in these areas. He is a regular reviewer for several international journals, and was on the TPC for a number of major international conferences. He received several awards, including the BUET Gold medal and the Chancellor prize for academic excellence.

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.