Computer simulation has become an important means for obtaining knowledge about nature. The practice of scientific simulation and the frequent use of uncertain simulation results in public policy raise a wide range of philosophical questions. Most prominently highlighted is the …
"Uncertainty" represents a wide variety of types of imperfect information. When working with uncertainties the author argues in favour of creating qualitative versions of existing methods and choosing the one that fits best.
In this book Simon Parsons describes qualitative methods for reasoning under uncertainty, "uncertainty" being a catch-all term for various types of imperfect information. The advantage of qualitative methods is that they do not require precise numerical information. Instead, the…
Using qualitative methods to deal with imperfect information.
In this book Simon Parsons describes qualitative methods for reasoning under uncertainty, "uncertainty" being a catch-all term for various types of imperfect information. The advantage of qualitative methods is that they do not require precise numerical information. Instead, the…
Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining : A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for…
Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for …
Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for …
Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for …
Intelligence is currently facing increasingly challenging cross-pressures from both a need for accurate and timely assessments of potential or imminent security threats and the unpredictability of many of these emerging threats. The essence of intelligence is no longer the colle…
"Intelligence is currently facing increasingly challenging cross-pressures from both a need for accurate and timely assessments of potential or imminent security threats and the unpredictability of many of these emerging threats. We are living in a social environment of growing …