Abstract: To solve the defect of poor search ability and bad precision of optimal result of differential evolution algorithm, a cooperative co-evolutionary differential evolution algorithm based on colony information mining (CCDE) was proposed. It first split the population into several sub-populations based on cooperative co-evolution. Each sub-population did the differential operations and crossover operations individually, using different differential strategies. Then it combined all the sub-populations into a whole population, and picked out one best individual depending on the fitness of each individual. The multiple regression analysis and pattern search algorithm were joined into the algorithm to improve the local search ability. It used the information of search direction gained by the least square to guide each individual of the entire colony to do the pattern search. The simulation experiment and the application in parameter estimation of 4-carboxybenzaldehyde content soft sensor in the production of pure terephthalic acid showed that the performance of the algorithm was much better than differential evolution algorithm and the result was good.