鎶ュ憡棰樼洰錛歁odeling a stochastic age-structured capital system with Poisson jumps using neural networks
銆€銆€鎶?鍛?浜猴細(xì)寮犲惎鏁?錛堝畞澶忓ぇ瀛︽暟瀛︾粺璁″闄紝鏁欐巿銆佸崥瀵鹼級(jí)
銆€銆€鎶ュ憡鏃墮棿錛?019騫?1鏈?1鏃?涓婂崍9:50
銆€銆€鎶ュ憡鍦扮偣錛氭牸鑷翠腑妤?00浼?xì)璁?br>銆€銆€鎽樿錛欼n this talk, an approach is investigated for modeling a stochastic age-structured capital system (SASCS) with Poisson jumps, in which the transfer rate of capital, noise intensity and jump intensity are approximated by feedforward neural networks (FNNs). The approximate stock of capital for the system is calculated using Euler鈥檚 scheme in time discretization. Based on Barkholder-Davis-Gundys inequality and Gronwalls lemma, the error between the approximate stock of capital and the actual stock of capital is estimated by using mean squares. Theoretical analysis of the convergence of the approximate stock of capital is conducted.
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鐞嗗闄?br>2019騫?1鏈?鏃?/p>
