Intelligent Software for Chemical Analysis

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. Conclusions. Bibliography. 3. Developing Expert Systems (H. van Leeuwen). Introduction. Prerequisites. Knowledge acquisition. Knowledge engineering. Inferencing. Explanation facilities. The integration of separate systems. Expert-system testing validation and evaluation. Concepts. Conclusions. Bibliography. 4. Expert-System-Development Tools (L. Buydens, H. van Leeuwen, R. Wehrens). Tools for implementing expert systems. Tool selection. Knowledge-acquisition tools. Concepts. Conclusions. Bibliography. 5. Validation and Evaluation of Expert Systems for HPLC Method Development - Case Studies (F. Maris, R. Hindriks). Introduction. Case study I: Expert systems for method selection and selectivity optimization. Case study II: System-optimization expert system. Case study III: Expert system for repeatability testing, applied for trouble-shooting in HPLC. Case study IV: Ruggedness-testing expert system. General comments on the evaluations. Concepts. Conclusions. Bibliography. 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. Conclusions. Bibliography. 7. Inductive Expert Systems (R. Wehrens, L. Buydens). Introduction. Inductive classification by ID3. Applications of ID3 in analytical chemistry. Concluding remarks. Concepts. Conclusions. Bibliography. 8. Genetic Algorithms and Neural Networks (G. Kateman). Introduction. Genetic algorithms. Artificial neural networks. Concepts. Conclusions. Bibliography. 9. Perspectives. Limitations of Intelligent Software. Dealing with intelligent software. Potential of intelligent software. Index.