Expert systems hybrid

Wehrens R, Lucasius C, Buydens LMC, Kateman G (1993a) HIPS, a hybrid self-adapting expert system for NMR spectrum interpretation using genetic algorithms. Anal Chim Acta 277 313... 

DEREK Hybrid Expert system, rules Sanderson and Earnshaw (1991)... 

Expert systems and QSAR methods can sometimes be combined to produce hybrid systems with greater predictive capability than either model alone. A QSAR model can be initially developed using chemical-substructure,... 

HITERM integrates high-performance computing on parallel machines and workstation clusters with a decision-support approach based on a hybrid expert system. Typical applications are in the domain of technological risk assessment and... 

Fedra, K. and Winkelbauer, L., A Hybrid Expert System, GIS and Simulation Modelling for Environmental and Technological Risk Management, Computer-Aided Civil and Infrastructure Engin., 17, 131, 2002. 

Gini, G., Testaguzza, V., Benfenati, E. and Todeschini, R. (1998) Hybrid toxicology expert system architecture and implementation of a multi-domain hybrid expert system for toxicology. Chemom. Intell. Lab. Syst., 43, 135—145. 

Prediction of the Dynamic Behavior of Temperature Sensitive Recombinent Cells Using a Hybrid Heuristics and Mathematical Model Based Expert System... 

Rabelo, L. (1990), Hybrid Artificial Neural Networks and Knowledge-Based Expert Systems Approach to Flexible Manufacturing System Scheduling, PhD. dissertation. University of Missouri-Rolla. 

Liu, K.F., Lai, J.H., 2009. Decision-support for environmental impact assessment a hybrid approach using fuzzy logic and fuzzy analytic network process. Expert Systems with Applications 36 (3), 5119—5136. 

Chapters 9-16 cover the application of optical and biosensor methods for on-line monitoring and control of bioprocesses. Topics include the use of expert systems for controlling flow injection analysis systems and hybrid process modeling for bioprocess control. 

Ming, Y., Wang, D., Luo, M., Zhang, D., Chen, Q. (2012). Fault detection, isolation and identification for hybrid systems with unknown mode changes and fault patters. Expert Systems with Applications, 39,9955—9965. 

Choy K. L., W. B. Lee, and V. Lo. 2003. Design of an intelligent supplier relationship management system A hybrid case based neural network approach. Expert Systems with Applications. 24 225-237. 

Data-based approaches can only handle defined measurable information and are only adequate for well-structured problems. They use analytical techniques which are frequently used in tactical decisions. On the other hand, experience-based approaches apply hybrid techniques that combine both quantitative and qualitative criteria. They generally employ expert systems, neural networks, and case-based reasoning to define the problem and determine the criteria in the supplier selection decision. The experience-based approaches use brainstorming, cognitive mapping as well as interpretative structural modeling. 

The prediction of three-dimensional chemical structure from a list of atoms in a molecule and their connectivity is a good example of a chemical problem that may be solved by an expert system. We have already seen (Fig. 9.2) how the SMILES interpreter can construct a two-dimensional representation of a structure from its one-dimensional representation as a SMILES string. The CONCORD program (CONnection table to CoORDinates) takes a SMILES string and, very rapidly, produces a three-dimensional model of an input molecule. This system is a hybrid between an expert system and a molecular mechanics program, molecular mechanics being the method by which molecular structures are minimized in most molecular modelling systems. The procedure operates as follows. 

CATABOL A hybrid expert system for predicting the biotransformation pathways, works together with model which calculates the probabilities of individual transformation of molecule http //oasis-lmc.org/ section=software swid=l... 

Tsai, W.H. Chou, W.C. 2009. Selecting management systems for sustainable development in SMEs A novel hybrid model based on DEMATEL, ANP, and ZOGP, Expert Systems with Applications 36 1444 1458. 

The basic methods of artificial intelligence are expert systems, genetic algorithms (Coley 1991), (Goldberg et al. 2003), (Man 1999), neural networks (Kosinski et al. (2007)), fuzzy sets (Yen (1998)). Expert Systems (ES) are a discipline of artificial intelligence, which gained numerous practical applications as the first on from the above list (Zielinski 1991). However, practically, hybrid systems are often used, as they... 

---