Part 1 Theoretical issues: an introduction to artificial neural networks, D.T. Pham; unsupervised neural learning, E. Oja; back-propagation and its variations, D. Tsaptsinos; the general approximation problem for feed-forward neural networks, A.B. Bulsari; connectionism vs symbolism - an overview, A.B. Bujosa et al; introduction to connectionist computer vision systems, D.W. Moolman et al. Part 2 Applications: lime kiln simulation and control by neural networks, B. Ribeiro and A. Dourado Correia; concentration estimation using neural networks and partial conventional models, B. Schenker and M. Agarwal; data rectification for dynamic processes using artificial neural networks, T.W. Karjala and D.M. Himmelblau; applications of neural networks in process dynamics, A.B. Bulsari; process modelling for fault detection using neural networks, T. Fujiwara; local modelling as a tool for semi-empirical or semi-mechanistic process modelling, B.A. Foss and T.A. Johansen; estimation of measurement error variances and process data reconciliation, C. Aldrich and J.S.J. van Deventer; process monitoring and visualization using self-organizing maps, O. Simula and J. Kangas; an overview of dynamic system control using neural networks, P. Zufiria; nonlinear system identification using neural networks - dynamics and instabilities, R. Rico-Martinez et al; pattern-based interpretation of on-line process data, J.F. Davis and C.-M. Wang; modelling ill-defined behaviour of reacting systems using neural networks, C. Aldrich and J.S.J. van Deventer; global vs local networks in identification and control -a case study of neutralization, M.N. Karim and B. Eikens; modelling chemical processes using multiresolution representation neural networks, K. Yoda and T. Furuya; the videographic characterisation of flotation froths using neural networks, D.W. Moolman et al; fuzzy modelling using two connectionist architectures, J. Zhang and A.J. Morris; system identification using elman and Jordan networks, D.T. Pham et al; time-series prediction with on-line correction of kalman gain - a connectionist approach, A. Dobnikar et al; neural networks based control strategies for a continuous polymerisation reactor, N. Watanabe; statistical and neural methods in classification and modelling, E.B. Martin et al; clustering and statistical techniques in neural networks, V. Venkatasubramanian and R. Rengaswamy.
