ANALYSIS OF THE DIFFERENT LINES OF RESEARCH
Before describing the different lines of research, it is important to bear in mind that often the appearance of different subject matters are caused by the need to find new points of view for solving a given problem. That is why in many cases there is no real separation between one line of research and another. On the other hand, this is a natural phenomenon, since here we are talking about an integrated and coordinated working group.
Genetic Algorithms
Learning and Knowledge Acquisition
Decision Support Systems
Approximate Reasoning and Fuzzy Logic
Artificial Neural Networks
Knowledge-Based Systems
Pattern Recognition using Fuzzy Techniques
Intelligent Planning and Control
Handling Linguistic Information
Data Bases and Artificial Intelligence
Evaluation of Environmental Impact using Fuzzy Techniques (EEI fuzzy)
Learning and Knowledge Acquisition
- Use of different techniques for the learning of rules based on examples: neural networks, logical induction, genetic algorithms,...
- Study on the theoretical conditions for developing learning algorithms in uncertain, imprecise and/or incomplete environments.
- Systems for classifying uncertain and/or imprecise environments.
- Systems for knowledge acquisition based on validation and fine tuning.
- Integration of systems based on interviews, systems of induction and those based on validation and fine tuning.
Decision Support Systems
- Algorithms and models of optimization with fuzzy information: Fuzzy Linear Programming, fuzzy multiobject programming, problem with the transportation, fuzzy combinatory optimization, games theory.
- Models of networks and fuzzy graphs.
- Decision-making problems (unipersonal, multipersonal, multicriteria, ...).
- Analysis and relationship between preference structures in decision-making models.
- Metaheuristics applied to fuzzy optimization problems.
- Systems of help for decision-making: developments in semi-structured and badly structured environments.
- Applications economic-financial and environmental fields.
Approximate Reasoning and Fuzzy Logic
- Analysis and design fuzzy inference methods.
- Theoretical Study of Fuzzy Logic.
- Non monotonous, fuzzy and multivalued Reasoning.
- Relation of Fuzzy Logic to multivalued and bivalued Logic.
- Design of tools and applications: syntactical system, ATMS,...
Artificial Neural Networks
- Use network technology for solving imprecise problems in optimization, classification,...
- Crisp grammatical and fuzzy inference using recurrent neural networks. Optimization of recurrent neural networks. Extracting rules based on recurrent neural networks.
- Fuzzy Inference using neural networks and weighted fuzzy rules.
- Comparing and ordering fuzzy numbers according to personal criteria.
- Identification of fuzzy systems.
- Fuzzy neural models: a fuzzy neuron and fuzzy associative memories.
- Logical interpretation of trained neural networks.
- Neural networks in parallel architectures.
Knowledge-Based Systems
- Representation of knowledge.
- Fuzzy knowledge-based systems.
- Verification and validation.
- Construction of expert systems.
Genetic Algorithms
- Application of techniques based on fuzzy logic for improving the behaviour of genetic algorithms: design of operators, control of parameters,...
- Genetic Algorithms in optimization problems with imprecise information.
- Application of genetic algorithms to the design and identification of fuzzy systems: adjustment and learning of fuzzy rule bases.
Data Bases and Artificial Intelligence
- Problems of defining and representing a fuzzy database.
- Design and development of software for a fuzzy database management system.
- Theoretical problems of functional dependence and design.
- Fuzzy logic data bases.
- Complex structures for representing imprecise knowledge. Applications.
- Development of a medical database that allows vague questions and accepts incomplete information.
- Exploitation and acquisition of the knowledge in data bases.
Handling Linguistic Information
- Coding linguistic information.
- Aggregating linguistic information.
- Analysis of linguistic preference structures.
- Design of selection processes, measures of consensus and consensus processes in group decision-making problems in a linguistic context.
Intelligent Planning and Control
- Study of the applicability of fuzzy operators in the design of intelligent control systems.
- Automatic design of controllers.
- Theoretical analysis of fuzzy controllers.
- Planning in domains with incomplete information. Application to the control of processes.
- Application of intelligent control in robotics.
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