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This paper aims to set up new rules for processing seawater quality monitoring data collected by photoelectric sensor network, and mine out the useful information contained in the data. For this purpose, the immune algorithm was introduced to the classical genetic algorithm, the fitness function was designed, and the crossover and mutation probabilities were adjusted, thus creating the adaptive immune genetic algorithm (IIGA). The new algorithm was described in details and applied in an actual case. Through the comparison between the IIGA, IGA and apriori algorithms, the author concluded that the IIGA not only shortened the mining time, but also ensured the operation accuracy. The research findings are of great importance to the association rules mining in various fields.

Method of Association Rules Mining and Its Application in Analysis of Seawater Samples