Qualitative reasoning: modeling and simulation with incomplete knowledge
Qualitative reasoning: modeling and simulation with incomplete knowledge
Data mining
Behavior patterns of logistic models with a delay
Mathematics and Computers in Simulation
Decision Queue Classifier for Supervised Learning Using Rotated Hyperboxes
IBERAMIA '98 Proceedings of the 6th Ibero-American Conference on AI: Progress in Artificial Intelligence
Including Qualitative Knowledge in Semiqualitative Dynamical Systems
IEA/AIE '98 Proceedings of the 11th international conference on Industrial and engineering applications of artificial intelligence and expert systems: methodology and tools in knowledge-based systems
Refining imprecise models and their behaviors
Refining imprecise models and their behaviors
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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In this paper is proposed a semiquantitative methodology to study models of dynamic systems with qualitative and quantitative knowledge. This qualitative information may be composed by: operators, envelope functions, qualitative labels and qualitative continuous functions. A formalism is also described to incorporate this qualitative knowledge into these models. The methodology allows us to study all the states (transient and stationary) of a semiquantitative dynamic system. It also helps to obtain its behaviours patterns. The methodology is applied to a logistic growth model with a delay.