A decision-making approach using point-cloud-based granular information
作者： Obaid Khozaimy , Abdulla Al-Dhaheri , A.M.M. Sharif Ullah
DOI: 10.1016/J.ASOC.2010.10.007
关键词:
摘要: Real-life decision problems are often solved by using a very limited set of data points. The computational complexity such can be handled easily mathematical entity called stochastic point cloud (SPC). In general, SPC is form granular information and simulated data-driven process. this study, particular interests given on normal-distribution-driven SPCs. When the parameters normally distributed variable not clearly known due to lack or multiplicity regression analysis, it forms Three types SPCs described in detail study. effectiveness solving real-life problem (i.e., how minimize vehicle emissions Abu Dhabi Emirate United Arab Emirates) also shown. To develop more realistic man-machine-friendly support systems one use
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