Several non - linear phenomena are also analyzed . by using uncoupled thermal - structure analyzing method , with the consideration the additional stiffness caused by thermal stress , the finite element model for thermal - vibration analysis is obtained and two typical hypersonic wing structures are computed 運(yùn)用非耦合熱-結(jié)構(gòu)分析方法,考慮熱應(yīng)力引起的附加剛度,得到熱環(huán)境下的結(jié)構(gòu)分析的有限元模型,并計(jì)算了兩種典型結(jié)構(gòu)的高超音速翼面熱結(jié)構(gòu)。
In the second part , we try to apply orthogonal polynomial approximations to the dynamical response problem of the duffing equation with random parameters under harmonic excitations . we first reduce the random duffing system into its non - linear deterministic equivalent one . then , using numerical method , we study the elementary non - linear phenomena in the system , such as saddle - node bifurcation , symmetry break bifurcation , phenomena in the system , such as saddle - node bifurcation , symmetry break bifurcation , period - doubling bifurcation and chaos 本文第二部分嘗試將正交多項(xiàng)式逼近方法應(yīng)用于隨機(jī)duffing系統(tǒng),提出與之等價(jià)的確定性非線性系統(tǒng)的新概念,并用數(shù)值方法對(duì)該系統(tǒng)在諧和激勵(lì)下的鞍結(jié)分叉、對(duì)稱(chēng)破裂分叉、倍周期分叉、和混沌等各種基本非線性響應(yīng)進(jìn)行了初步探討。
An artificial neural network ( ann ) model was developed and used in different water bodies to predict timing for environmental changes as well as for the dynamics of resources . the results show that the ann model is superior to classical statistical models ( csm ) and can be used as predictive tool for highly non - linear phenomena 用人工神經(jīng)網(wǎng)絡(luò)方法對(duì)不同水域、不同環(huán)境因子之間非線性和不確定性的復(fù)雜關(guān)系進(jìn)行學(xué)習(xí)訓(xùn)練并預(yù)測(cè)檢驗(yàn),結(jié)果表明:人工神經(jīng)網(wǎng)絡(luò)方法在模擬和預(yù)測(cè)方面均優(yōu)于傳統(tǒng)的統(tǒng)計(jì)回歸模型,在資源與環(huán)境方面的應(yīng)用是可行的,具有較強(qiáng)的模擬預(yù)測(cè)能力。