Abstract: In the field of FPD, the routing between FPC ports and IC ports is called PCB routing. Affected by many factors such as the shape of routing area, the width of interconnect, the space between interconnects and so on, PCB routing may be regular or irregular, which makes it very difficult to accurately and quickly calculate the interconnect resistances. The existing resistance calculation method can calculate the resistance of PCB routing with arbitrary shape based on the coordinates of the inflection point of routing, but has very large time and space overhead, which seriously affects the convergence of the design and cannot effectively utilize historical routing data. The calculation method of PCB routing resistance based on machine learning is studied for the first time. Firstly, the PCB routing with arbitrary shape is divided into several continuous quadrilateral. Secondly, the resistance of a single quadrilateral is predicted by using the established quadrilateral resistance calculation method. Finally, the resistance values of all quadrilateral routing are accumulated to obtain the resistance of the PCB routing. Efficient and accurate calculation of the resistance of PCB routing with ar-bitrary shape is carried out through the “division-prediction-calculation” method. Compared with the tradi-tional method, the average absolute error of our method is only about 1 ohm, and the memory cost and time cost are reduced by 60.9% and 97.9%, respectively.

Key words: resistance calculation, machine learning, PCB routing ,