TY - JOUR N2 - Information fusion approaches have been commonly used in multi sensor environments for the fusion and grouping of data from various sensors which is used further to draw a meaningful interpretation of the data. Traditional information fusion methods have limitations such as high time complexity of fusion processes and poor recall rate. In this work, a new multi-channel nano sensor information fusion method based on a neural network has been designed. By analyzing the principles of information fusion methods, the back propagation based neural network (BP-NN) is devised in this work. Based on the design of the relevant algorithm flow, information is collected, processed, and normalized. Then the algorithm is trained, and output is generated to achieve the fusion of information based on multi-channel nano sensor. Moreover, an error function is utilized to reduce the fusion error. The results of the present study show that compared with the conventional methods, the proposed method has quicker fusion (integration of relevant data) and has a higher recall rate. The results indicate that this method has higher efficiency and reliability. The proposed method can be applied in many applications to integrate the data for further analysis and interpretations. L1 - http://journals.pan.pl/Content/122227/PDF/BPASTS_2022_70_2_2381.pdf L2 - http://journals.pan.pl/Content/122227 PY - 2022 IS - 2 EP - e140258 DO - 10.24425/bpasts.2022.140258 KW - nanosensors KW - multiplexing KW - information fusion KW - data fusion KW - neural network A1 - Li, Chaoke VL - 70 DA - 18.01.2022 T1 - Information fusion method of multichannel nanosensors based on neural network SP - e140258 UR - http://journals.pan.pl/dlibra/publication/edition/122227 T2 - Bulletin of the Polish Academy of Sciences Technical Sciences ER -