Abstract: As to the relationship between grain size and sedimentary environment, in this paper, an identification method of sedimentary environment is proposed based on fuzzy neural network, which combines the advantages of both fuzzy logic and artificial neural network. The proposed approach includes taking the key size parameters of clastic rock as inputs, being standardized and fuzzified by the network and being defuzzified of outputs. As a result, the fuzzy inference process is involved in the neural network sufficiently and successfully. The experiment shows that the improved network’s misjudgment rate of identification is 9.1%, less than 32.1% of BPNN obviously. Moreover, the former is faster than the latter in the aspect of convergence. Therefore, the network in this paper can fulfill the necessaries of practical projects.

Key words: fuzzy neural network; sedimentary environment; identification analysis; grain size analysis; classification