Abstract: In the process of electrolytic copper production the contents of copper ions and acid ions can only be detected once each day through tests, and they arc inadequate to showing the regularity of variation of copper electrolyte composition. It was found that the values for conventional interpolation often differ greatly from the values obtained actually in site. To solve the problem, a soft measurement model is advanced considering the influencing factors on measurement with relevant data forecasted efficiently. The support vector machine is introduced to improve linear interpolation because of its advantages in developing the soft measurement model. And a method is given to determine the weights for the values estimated by the soft measurement and values for conventional linear interpolation. The approach proposed ensures not only the time continuity of data but also the values for interpolation to approximate to actual values. Simulation results showed its effectiveness.