In order to solve the problems that the network bandwidth of previous information application systems can’t guarantee the quality of big data transmission, resulting in low transmission efficiency and slow data processing, etc., an improved information application system is proposed by optimizing the fine integration method of fuzzy fractional ordinary differential equations and combining with software-defined networking (SDN). Firstly, the fractional-order fuzzy differential equation fine integration method of Pade approximation is derived. Then, based on the error analysis theory, the optimization formula for the adaptive selection of weighted parameter N and expanded item number q is obtained. Combined with SDN, an improved information application system is designed, and the improved algorithm and system are detected by example simulation and performance test. The results show that the numerical accuracy and the computational efficiency of the improved algorithm are higher than that of the improved algorithm. The improved port data merge rate and task completion efficiency under different bandwidth are also significantly higher than the original system. It shows that the information application system proposed in this research can better solve the problems of insufficient bandwidth and low communication speed of traditional systems, and provide a new perspective for bandwidth optimization of big data.

为了解决现有信息应用系统的网络带宽不能保证大数据传输质量，传输效率低，数据处理速度慢等问题，提出了一种优化的信息应用系统。模糊分数阶常微分方程的积分方法，并与软件定义网络（SDN）结合。首先，推导了Pade逼近的分数阶模糊微分方程精细积分方法。然后，基于误差分析理论，获得了加权参数N和扩展项数q的自适应选择的优化公式。结合SDN，设计了一种改进的信息应用系统，通过实例仿真和性能测试，检测出改进后的算法和系统。结果表明，改进算法的数值精度和计算效率均高于改进算法。在不同带宽下提高的端口数据合并率和任务完成效率也明显高于原始系统。结果表明，本文提出的信息应用系统可以较好地解决传统系统带宽不足，通信速度低的问题，为大数据带宽优化提供了新的思路。在不同带宽下提高的端口数据合并率和任务完成效率也明显高于原始系统。结果表明，本文提出的信息应用系统可以较好地解决传统系统带宽不足，通信速度低的问题，为大数据带宽优化提供了新的思路。在不同带宽下提高的端口数据合并率和任务完成效率也明显高于原始系统。结果表明，本文提出的信息应用系统可以较好地解决传统系统带宽不足，通信速度低的问题，为大数据带宽优化提供了新的思路。