To study seasonal and intraseasonal variations of the Taiwan Warm Current (TWC) in detail,Rotated Empirical Orthogonal Function (REOF) and Extended Associate Pattern Analysis (EAPA) are jointly adopted with daily sea ...To study seasonal and intraseasonal variations of the Taiwan Warm Current (TWC) in detail,Rotated Empirical Orthogonal Function (REOF) and Extended Associate Pattern Analysis (EAPA) are jointly adopted with daily sea surface salinity (SSS), sea surface temperature (SST) and sea surface height (SSH)datasets covering 1126 days from American Navy Experimental Real-Time East Asian Seas Ocean Nowcast System in the present paper. Results show that the first and second REOFs of SST in the southern East China Sea(SECS) account for 50,8% and 39.8% of the total variance. The surface TWC contains persistent (multi-year mean), seasonal and intraseasonal components. The persistent one mainly inosculates with the Kuroshio but the seasonal and intraseasonal ones are usually active only on the continental shelf. Its persistent component is produced by inertial flow of the Kuroshio, however its seasonal and intraseasonal ones seems coming from seasonal and intraseasonal oscillations of monsoon force. The seasonal one reaches its maximum in late summer,lasting about four months and the intraseasonal one takes place at any seasons, lasting more than 40 days.展开更多
There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fi...There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search.展开更多
基金Supported by the National Basic Research Program (No. G1999043803), Hi-Tetch Research and Development Program of China (No. 2001AA633060) and the grant of Institute of Oceanology, Chinese Academy of Sciences (No.L370221117).
文摘To study seasonal and intraseasonal variations of the Taiwan Warm Current (TWC) in detail,Rotated Empirical Orthogonal Function (REOF) and Extended Associate Pattern Analysis (EAPA) are jointly adopted with daily sea surface salinity (SSS), sea surface temperature (SST) and sea surface height (SSH)datasets covering 1126 days from American Navy Experimental Real-Time East Asian Seas Ocean Nowcast System in the present paper. Results show that the first and second REOFs of SST in the southern East China Sea(SECS) account for 50,8% and 39.8% of the total variance. The surface TWC contains persistent (multi-year mean), seasonal and intraseasonal components. The persistent one mainly inosculates with the Kuroshio but the seasonal and intraseasonal ones are usually active only on the continental shelf. Its persistent component is produced by inertial flow of the Kuroshio, however its seasonal and intraseasonal ones seems coming from seasonal and intraseasonal oscillations of monsoon force. The seasonal one reaches its maximum in late summer,lasting about four months and the intraseasonal one takes place at any seasons, lasting more than 40 days.
基金Project(60574030) supported by the National Natural Science Foundation of ChinaKey Project(60634020) supported by the National Natural Science Foundation of China
文摘There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search.
