Abstract
The process of the reaction of carbon molecules in the dark reaction of photosynthesis was chosen as a BDA (Biosystem-Derived Algorithm). In this paper, the BDA was referred to as the 'Photosynthetic Learning Algorithm (PLA)'. The PLA utilizes the rules governing the conversion of carbon molecules from one substance to another in the Benson-Calvin cycle and Photorespiration reactions. In this paper, the principles of the PLA are presented in detail. Neural network training was selected as a typical optimization or parameter estimation problem to demonstrate the performance of the PLA. The neural network model for the logical functions was successfully trained
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