A comprehensive performance investigation of cellulose evaporative cooling pad systems using predictive approaches

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@Article{Sohani:2017:ATE,
  author =       "Ali Sohani and Mitra Zabihigivi and 
                 Mohammad Hossein Moradi and Hoseyn Sayyaadi and 
                 Hamidreza Hasani Balyani",
  title =        "A comprehensive performance investigation of cellulose
                 evaporative cooling pad systems using predictive
                 approaches",
  journal =      "Applied Thermal Engineering",
  volume =       "110",
  pages =        "1589--1608",
  year =         "2017",
  ISSN =         "1359-4311",
  DOI =          "doi:10.1016/j.applthermaleng.2016.08.216",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1359431116315769",
  abstract =     "Developing the soft computing and statistical tools
                 (SCST) for predicting the behavior pattern of the
                 performance features of a cellulose evaporative cooling
                 pad system was studied. Three soft computing and
                 statistical tools- artificial neural network (ANN),
                 genetic programming (GP), and multiple linear
                 regression (MLR)- were used to predict the supply air
                 temperature and pad pressure drop. The prediction
                 abilities of obtained models were analyzed and compared
                 with analytical models, and a comprehensive error
                 analysis was conducted. It was found that the MLR and
                 ANN models perform better than the other approaches for
                 predicting the supply air temperature and the pad
                 pressure drop, respectively. The obtained models had
                 the accuracy of numerical models as well as the
                 simplicity of analytical methods. Effects of inlet air
                 conditions and pad characteristics on nine different
                 system performance parameters like thermal comfort
                 indices were also studied, comprehensively. It was
                 found that the best values for pad thickness and
                 specific contact area are the minimum values of them,
                 which provide thermal comfort conditions (7 cm and 420
                 m2 m-3 for the investigated case respectively). Using
                 the direct evaporative cooling system with
                 recirculation of a part of the cooled air in very hot
                 and dry weather conditions was investigated and
                 suggested as an alternative for conventional systems.",
  keywords =     "genetic algorithms, genetic programming, Artificial
                 neural network, Cellulose pad, Evaporative cooling,
                 Inlet air pre-cooling, Multiple linear regression",
}

Genetic Programming entries for Ali Sohani Mitra Zabihigivi Mohammad Hossein Moradi Hoseyn Sayyaadi Hamidreza Hasani Balyani

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