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KNOWLEDGE REPRESENTATION FOR VERSATILE HYBRID INTELLIGENT PROCESSING APPLIED IN PREDICTIVE TOXICOLOGY

    Abstract:

    The increasing amount and complexity of data used in predictive toxicology call for new and flexible approaches based on hybrid intelligent methods to mine the data. This chapter introduces the specification language PToxML, based on the open XML standard, for toxicology data structures, and the markup language HISML for integrated data structures of Hybrid Intelligent Systems. The second XML application was introduced to fill the gap between existing Predictive Toxicology simple models and complex models based on explicit and implicit knowledge represented as modular hybrid intelligent structures. The two proposed specification languages are of immediate use for predictive toxicology and soft computing applications. First results to represent and process specific features of two pesticides groups through clusters and modular hybrid intelligent models using PToxML and HISML are also presented.