1999
DOI: 10.1016/s1474-6670(17)56962-1
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Neural network modeling and intelligent control of the distributed parameter greenhouse climate

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Cited by 3 publications
(2 citation statements)
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“…However, due to the large fluctuation in control parameters in the greenhouse environment, it is necessary to combine the corresponding intelligent algorithm to solve the control of related parameters in a complex greenhouse environment. Traditional greenhouse climate control methods can be divided into three types: proportional-integral-derivative (PID) control methods [153], [154], fuzzy control methods [155], [156] and neural network control methods [157]- [159]. As research becomes more in-depth, an increasing number of new intelligent algorithms have been proposed and applied.…”
Section: A Monitoring and Control Of Environmentmentioning
confidence: 99%
“…However, due to the large fluctuation in control parameters in the greenhouse environment, it is necessary to combine the corresponding intelligent algorithm to solve the control of related parameters in a complex greenhouse environment. Traditional greenhouse climate control methods can be divided into three types: proportional-integral-derivative (PID) control methods [153], [154], fuzzy control methods [155], [156] and neural network control methods [157]- [159]. As research becomes more in-depth, an increasing number of new intelligent algorithms have been proposed and applied.…”
Section: A Monitoring and Control Of Environmentmentioning
confidence: 99%
“…In recent years, several approaches have been proposed to deal with the climate control problem in greenhouses (Boaventura et al 1997;Wang and Wu, 1999), however most techniques provide only indirect constraint compensation.…”
Section: Introductionmentioning
confidence: 99%