Evaluation for Development Effect of Enterprise Innovation with Neural Network from Low-Carbon Economy

China has resolved to pay more and attention the sustainability of ecological construction social development. The country proposed a low-carbon economy policy; development management enterprises are also actively responding call for economy. Through series innovations changes, it intends realize its own production business development, thereby promoting transformation optimization industrial institutions. Innovation is significant driving force national economic In order build into an innovative country, there need innovation strategy system. state vigorously promotes implementation innovation-driven strategies. Enterprises not only important carrier implement mass entrepreneurship but powerful There dire importance identify techniques evaluate impact corporate on effects with Considering this aforementioned problem, random initialization parameters in back propagation network used. This evaluation process can easily lead functioning model falling local optimum. work designs (IGWO-BP) improved gray wolf algorithm (IGWO) optimize BP network. To improve ability GWO, study uses chaotic map initialize population. nonlinear convergence factor as well dynamic weight used promote so initial threshold point IGWO-BP applied perform case enterprise relevant