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机构地区:[1]郑州大学西亚斯国际学院电子信息工程学院,新郑451150
出 处:《科学技术与工程》2016年第19期255-258,共4页Science Technology and Engineering
基 金:河南省教育厅科学技术研究项目(14A520059)资助
摘 要:对嵌入式系统进行电气节能控制具有重要的应用价值。利用传统算法进行嵌入式系统的电气节能控制过程中,无法根据嵌入式操作系统中的工作属性确定嵌入式系统工作过程中物理进程时间的精确值,降低了嵌入式系统的运行效率。提出一种基于模糊神经网络算法的嵌入式系统的智能电气节能控制方法,根据嵌入式系统中的电量与时间的非线性关系,建立嵌入式的智能电气节能控制模型。在模糊神经网络中,通过电压调节的时间误差和误差变化率这两个输入变量,能够得到电气节能控制的优化策略,最终获得电气控制最优解。实验结果表明,利用改进算法进行嵌入式系统的电气节能控制,能够极大提高嵌入式系统的运行效率,降低了电量损耗,效果令人满意。An embedded system for electric energy saving control has important application value.Using traditional algorithms in the process of the embedded system of electric energy saving control,could not be determined according to the properties of embedded operating system of the working process of the embedded system in the physical process of the precise value of time,which reduces the efficiency of embedded system.For this,a kind of embedded system based on fuzzy neural network algorithm of intelligent electric energy saving control method was put forward,according to the nonlinear relationship of the power in the embedded system and time embedded intelligent electric energy saving control model is established,in the fuzzy neural network,by the time error and error change rate of voltage regulation the two input variables,and can get the optimization of electric energy saving control strategy,finally get electric control optimal solution.The experimental results show that the improved algorithm for electric energy saving control of embedded system,can greatly enhance the efficiency of embedded system,reduces the power loss,the effect is satisfactory.
分 类 号:TP301.6[自动化与计算机技术—计算机系统结构]
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