Statistical modelling of networked human-automation performance using working memory capacity

Ergonomics

Volumn 57, Issue 3, 2014, Pages 295-318

  Ahmed, Nisar ^a   de Visser, Ewart ^b   Shaw, Tyler ^b   Mohamed Ameen, Amira ^c   Campbell, Mark ^a   Parasuraman, Raja ^b  

^a School of Operations Research and Industrial Engineering   (United States)

^b GEORGE MASON UNIVERSITY   (United States)

^c UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

Bayesian networks; inverse reasoning; linear and Gaussian process regression; networked human automation systems; predictive statistical models; working memory

Indexed keywords

AUTOMATION; ENTERPRISE RESOURCE PLANNING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); ISOMERS; UNMANNED AERIAL VEHICLES (UAV);

BAYESIAN NETWORK MODELS; EXPERIMENTAL CONDITIONS; GAUSSIAN PROCESS MODELS; GAUSSIAN PROCESS REGRESSION; INVERSE REASONING; PROBABILISTIC INFERENCE; STATISTICAL PREDICTION; WORKING MEMORY;

BAYESIAN NETWORKS;

AIRCRAFT; ATTENTION; BAYES THEOREM; COMPUTER SIMULATION; DECISION MAKING; FEMALE; HUMAN; MALE; MAN MACHINE INTERACTION; NONPARAMETRIC TEST; PSYCHOLOGY; REGRESSION ANALYSIS; ROBOTICS; SHORT TERM MEMORY; STATISTICAL MODEL; TASK PERFORMANCE; WORKLOAD;

AIRCRAFT; ATTENTION; BAYES THEOREM; COMPUTER SIMULATION; DECISION MAKING; FEMALE; HUMANS; LINEAR MODELS; MALE; MAN-MACHINE SYSTEMS; MEMORY, SHORT-TERM; REGRESSION ANALYSIS; ROBOTICS; STATISTICS, NONPARAMETRIC; TASK PERFORMANCE AND ANALYSIS; WORKLOAD;

EID: 84897438445     PISSN: 00140139     EISSN: 13665847     Source Type: Journal    
DOI: 10.1080/00140139.2013.855823     Document Type: Article

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