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- W2321896348 abstract "In a plant factory, optimal control technique for growth optimization of plants is severely required from a view of cost-performance. The present works is attempts to apply the intelligent control technique including neural networks and genetic algorithms to the optimal control of the growth of spinach plants in hydroponics. The optimal control problem is to decide three set points of light intensity, temperature during the daytime and temperature during the nighttime, which maximize the fresh weight of the plants. In the system, responses of the fresh weight as affected by light intensity and temperatures during day and night are first identified using the neural network and then optimal values (three set points) are searched through the simulation of the identified model using the genetic algorithm. A three-layer neural network was effective for the identification of the fresh weight as affected by light intensity, temperature during daytime and temperature during nighttime. The genetic algorithm allowed the optimal value to be quickly sought from the model simulation. Thus, the intelligent control technique involving neural networks and genetic algorithms is quite useful for the control for growth optimization of plants in a plant factory." @default.
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- W2321896348 date "1994-01-01" @default.
- W2321896348 modified "2023-10-18" @default.
- W2321896348 title "Growth Optimization of Spinach Plants in Plant Growth Factory Using Intelligent Control." @default.
- W2321896348 doi "https://doi.org/10.2525/jshita.6.203" @default.
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