Intelligent software for chemical analysis

Abstract

1. Introduction: Automation and intelligent software Expert systems Neural networks and genetic algorithms Reader's guide: Concepts Conclusions. 2. Knowledge-based Systems in Chemical Analysis, P. Schoenmakers: Computers in analytical chemistry Sample preparation Method selection Method development Instrument control and error diagnosis Data handling and calibration Data interpretation Validation Laboratory management Concluding remarks Concepts. 3. Developing Expert Systems, H. van Leeuwen: Prerequisites Knowledge acquisition Knowledge engineering Inferencing Explanation facilities The integration of separate systems Expert-system testing validation and evaluation Concepts. 4. Expert-System-Development Tools, L. Buydens, H. van Leeuwen, R. Wehrens: Tools for implementing expert systems Tool selection Knowledge-acquisition tools Concepts. 5. Validation and Evaluation of Expert Systems for HPLC Method Development - Case Studies, F. Maris, R. Hindriks: Case study 1 - Expert systems for method selection and selectivity optimization Case study 2 - System-optimization expert system Case study 3 - Expert system for repeatability testing, applied for trouble-shooting in HPLC Case study 4 - Ruggedness-testing expert system General comments on the evaluations Concepts. 6. Self-adaptive Expert Systems, R. Wehrens: Introduction - maintaining expert systems Self-adaptive expert systems - Methods and approaches The refinement approach of SEEK Examples from analytical chemistry Concluding remarks Concepts. 7. Inductive Expert Systems, R. Wehrens, L. Buydens: Inductive classification by ID3 Applications of ID3 in analytical chemistry Concluding remarks Concepts. 8. Genetic Algorithms and Neural Networks, G. Kateman: Genetic algorithms Artificial neural networks Concepts. 9. Perspectives: Limitations of Intelligent Software Dealing with intelligent software Potential of intelligent software.