The invention relates to an indoor illumination
estimation method based on a BP neural network
algorithm, and belongs to the technical field of
intelligent algorithms. The method comprises the following steps: S1, analyzing parameters obtained through traditional formula calculation and a sensor to obtain BP neural network input parameters and a training model; S2, based on the
light flux transferfunction
matrix model, obtaining the required indoor
illuminance through LED
luminous flux calculation; S3, linearly superposing the
illuminance of the n light sources, calculating the
illuminance ofthe corresponding point, performing reverse approximation according to a successive approximation rule to obtain the
luminous flux of the lamp, and obtaining the illuminance of the calculation point;and S4, calculating the illuminance needing to be compensated by utilizing the illuminance data, predicted by the BP neural
network model, of the natural light at a plurality of point locations of the indoor working face. According to the method, under the condition that
natural illumination is fully utilized in different seasons, the maximum balance among the three requirements of seeking energyconservation, saving and comfort is met through light supplement.