@article{fdi:010062679,
  title = {{I}nteractive diagnosis for a grid network of rain gauges using fuzzy reasoning},
  author = {{G}iap, {Q}. {H}. and {P}loix, {S}. and {A}drot, {O}. and {D}epraetere, {C}hristian},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his paper aims at designing a diagnosis tool to support experts for detecting and localizing faults in a network of rain gauges. {T}his problem is presented in the context of human-machine cooperation. {I}n this problem, it is impossible to model completely the whole expert knowledge about misbehavior. {D}iagnostic becomes a process where only a part of the expert knowledge is formalized, the remaining is kept implicit and is exploited gradually during the diagnostic process thanks to interactions with experts. {A}t each step, the proposed diagnosis tool supports the expert by presenting selected data to be analyzed, i.e. rainfall hyetographs for a cluster of rain gauges for which the expert has to identify possible discrepancies. {A} fuzzy logic based diagnostic reasoning is then used because it proves to be more relevant to express the expert conclusions, which may be dubious. {T}he way of handling such diagnosis processes is presented in this paper.},
  keywords = {{F}ault diagnosis ; {D}iagnosis analysis ; {D}etection test design ; {S}ymptom generation ; {F}uzzy logic ; {BENIN}},
  booktitle = {},
  journal = {{E}ngineering {A}pplications of {A}rtificial {I}ntelligence},
  volume = {36},
  numero = {},
  pages = {99--113},
  ISSN = {0952-1976},
  year = {2014},
  DOI = {10.1016/j.engappai.2014.07.002},
  URL = {https://www.documentation.ird.fr/hor/fdi:010062679},
}