Uncertainty, imperfections in geographic information

DM-31 - Mathematical models of vagueness: Fuzzy sets and rough sets
  • Compare and contrast the relative merits of fuzzy sets, rough sets, and other models
  • Differentiate between fuzzy set membership and probabilistic set membership
  • Explain the problems inherent in fuzzy sets
  • Create appropriate membership functions to model vague phenomena
DM-30 - Vagueness
  • Compare and contrast the meanings of related terms such as vague, fuzzy, imprecise, indefinite, indiscrete, unclear, and ambiguous
  • Describe the cognitive processes that tend to create vagueness
  • Recognize the degree to which vagueness depends on scale
  • Evaluate vagueness in the locations, time, attributes, and other aspects of geographic phenomena
  • Differentiate between the following concepts: vagueness and ambiguity, well defined and poorly defined objects and fields, and discord and non-specificity
  • Identify the hedges used in language to convey vagueness
  • Evaluate the role that system complexity, dynamic processes, and subjectivity play in the creation of vague phenomena and concepts
  • Differentiate applications in which vagueness is an acceptable trait from those in which it is unacceptable
DM-32 - Error-based uncertainty
  • Define uncertainty-related terms, such as error, accuracy, uncertainty, precision, stochastic, probabilistic, deterministic, and random
  • Recognize expressions of uncertainty in language
  • Evaluate the causes of uncertainty in geospatial data
  • Describe a stochastic error model for a natural phenomenon
  • Explain how the familiar concepts of geographic objects and fields affect the conceptualization of uncertainty
  • Recognize the degree to which the importance of uncertainty depends on scale and application
  • Differentiate uncertainty in geospatial situations from vagueness
DM-31 - Mathematical models of vagueness: Fuzzy sets and rough sets
  • Compare and contrast the relative merits of fuzzy sets, rough sets, and other models
  • Differentiate between fuzzy set membership and probabilistic set membership
  • Explain the problems inherent in fuzzy sets
  • Create appropriate membership functions to model vague phenomena
DM-30 - Vagueness
  • Compare and contrast the meanings of related terms such as vague, fuzzy, imprecise, indefinite, indiscrete, unclear, and ambiguous
  • Describe the cognitive processes that tend to create vagueness
  • Recognize the degree to which vagueness depends on scale
  • Evaluate vagueness in the locations, time, attributes, and other aspects of geographic phenomena
  • Differentiate between the following concepts: vagueness and ambiguity, well defined and poorly defined objects and fields, and discord and non-specificity
  • Identify the hedges used in language to convey vagueness
  • Evaluate the role that system complexity, dynamic processes, and subjectivity play in the creation of vague phenomena and concepts
  • Differentiate applications in which vagueness is an acceptable trait from those in which it is unacceptable
DM-30 - Vagueness
  • Compare and contrast the meanings of related terms such as vague, fuzzy, imprecise, indefinite, indiscrete, unclear, and ambiguous
  • Describe the cognitive processes that tend to create vagueness
  • Recognize the degree to which vagueness depends on scale
  • Evaluate vagueness in the locations, time, attributes, and other aspects of geographic phenomena
  • Differentiate between the following concepts: vagueness and ambiguity, well defined and poorly defined objects and fields, and discord and non-specificity
  • Identify the hedges used in language to convey vagueness
  • Evaluate the role that system complexity, dynamic processes, and subjectivity play in the creation of vague phenomena and concepts
  • Differentiate applications in which vagueness is an acceptable trait from those in which it is unacceptable
DM-32 - Error-based uncertainty
  • Define uncertainty-related terms, such as error, accuracy, uncertainty, precision, stochastic, probabilistic, deterministic, and random
  • Recognize expressions of uncertainty in language
  • Evaluate the causes of uncertainty in geospatial data
  • Describe a stochastic error model for a natural phenomenon
  • Explain how the familiar concepts of geographic objects and fields affect the conceptualization of uncertainty
  • Recognize the degree to which the importance of uncertainty depends on scale and application
  • Differentiate uncertainty in geospatial situations from vagueness
DM-31 - Mathematical models of vagueness: Fuzzy sets and rough sets
  • Compare and contrast the relative merits of fuzzy sets, rough sets, and other models
  • Differentiate between fuzzy set membership and probabilistic set membership
  • Explain the problems inherent in fuzzy sets
  • Create appropriate membership functions to model vague phenomena
DM-31 - Mathematical models of vagueness: Fuzzy sets and rough sets
  • Compare and contrast the relative merits of fuzzy sets, rough sets, and other models
  • Differentiate between fuzzy set membership and probabilistic set membership
  • Explain the problems inherent in fuzzy sets
  • Create appropriate membership functions to model vague phenomena
DM-32 - Error-based uncertainty
  • Define uncertainty-related terms, such as error, accuracy, uncertainty, precision, stochastic, probabilistic, deterministic, and random
  • Recognize expressions of uncertainty in language
  • Evaluate the causes of uncertainty in geospatial data
  • Describe a stochastic error model for a natural phenomenon
  • Explain how the familiar concepts of geographic objects and fields affect the conceptualization of uncertainty
  • Recognize the degree to which the importance of uncertainty depends on scale and application
  • Differentiate uncertainty in geospatial situations from vagueness

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