AgenaRisk

AgenaRisk uses the latest developments from the field of artificial intelligence and visualisation to solve complex, risky problems. AgenaRisk enables decision-makers to measure and compare different risks in a way that is repeatable and auditable. The AgenaRisk solution includes predictive analytics and scales up to organisational-level risk monitoring and assessment. It is ideal for risk scenario planning.


References in zbMATH (referenced in 13 articles )

Showing results 1 to 13 of 13.
Sorted by year (citations)

  1. Wieten, Remi; Bex, Floris; Prakken, Henry; Renooij, Silja: Information graphs and their use for Bayesian network graph construction (2021)
  2. Alkhairy, Ibrahim; Low-Choy, Samantha; Murray, Justine; Wang, Junhu; Pettitt, Anthony: Quantifying conditional probability tables in Bayesian networks: Bayesian regression for scenario-based encoding of elicited expert assessments on feral pig habitat (2020)
  3. Javidian, Mohammad Ali; Valtorta, Marco; Jamshidi, Pooyan: AMP chain graphs: minimal separators and structure learning algorithms (2020)
  4. Seiti, Hamidreza; Hafezalkotob, Ashkan; Herrera-Viedma, Enrique: A novel linguistic approach for multi-granular information fusion and decision-making using risk-based linguistic d numbers (2020)
  5. Fenton, Norman; Neil, Martin: Risk assessment and decision analysis with Bayesian networks. (2019)
  6. Yet, Barbaros; Neil, Martin; Fenton, Norman; Constantinou, Anthony; Dementiev, Eugene: An improved method for solving hybrid influence diagrams (2018)
  7. Kurzyk, Dariusz; Glos, Adam: Quantum inferring acausal structures and the Monty Hall problem (2016)
  8. Cene, E.; Karaman, F.: Analysing organic food buyers’ perceptions with Bayesian networks: a case study in Turkey (2015)
  9. Dialsingh, Isaac: Book review of: N. Fenton and M. Neil, Risk assessment and decision analysis with Bayesian networks (2014)
  10. Lucas, Peter J. F.: Book review of: N. Fenton and M. Neil, Risk assessment and decision analysis with Bayesian networks (2014)
  11. Madeyski, Lech; Majchrzak, Marek: Software measurement and defect prediction with DePress extensible framework (2014) ioport
  12. Zhou, Yun; Fenton, Norman; Neil, Martin: Bayesian network approach to multinomial parameter learning using data and expert judgments (2014) ioport
  13. Fenton, Norman; Neil, Martin: Risk assessment and decision analysis with Bayesian networks. (2013)