Java 重启mycat服务 reload

引入新型调频资源和应用先进控制方法是提升频率调节质量和效率的重要手段。首先，分析总结了大规模可再生能源接入对电力系统频率响应性能和调频需求两方面的影响。然后，从新型调频资源参与自动发电控制的可行性、经济性、有效性及控制策略等多个角度，综述了新型调频资源参与自动发电控制的关键问题和研究动态。归纳并讨论了几类先进控制技术应用于自动发电控制中的研究现状和应用前景。最后，对大规模可再生能源接入条件下自动发电控制的研究挑战和方向进行了总结和展望。(Introducing new FM resources and applying advanced control methods are important means to improve the quality and efficiency of frequency regulation. Firstly, the impact of large-scale renewable energy access on power system frequency response performance and frequency modulation requirements is analyzed and summarized. Then, the key issues and research trends of the new FM resources participating in the automatic generation control are summarized from the aspects of feasibility, economy, effectiveness and control strategy of the new FM resources participating in the automatic generation control. The research status and application prospects of several kinds of advanced control technologies applied in automatic generation control are summarized and discussed. Finally, the research challenges and directions of automatic generation control under the condition of large-scale renewable energy access are summarized and prospected.)

利用matlab仿真的雷达方向图程序，该程序仿真了和波束，差波束等，程序真实有效。(Radar direction map program using MATLAB simulation)

Hot plug state machine master detection in verified protocols in training the transmission during reset has implementation under the design in integration during runtime

基于MATLAB的simulink的交流电机单相交交变频调速系统(Simulink- based AC motor single- phase AC variable frequency speed regulation system based on)

说明：  地理信息系统开发简要文档说明和使用说明。GIS开发(Geographic Information System Development Brief Document Description and Use Description. Development of GIS)

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运用圆组合阵列定位噪声源，里面有几种简单的算法(There are several simple algorithms for locating noise sources using circular array.)

Nobel Prize Winner s Paper-Nobel Prize Winner"s Paper

说明：  在FPGA内利用verilog实现数字上变频(apply the verilog to implement the digital up frequency)

说明：  极限学习机（ELM）用来训练单隐藏层前馈神经网络（SLFN）与传统的SLFN训练算法不同，极限学习机随机选取输入层权重和隐藏层偏置，输出层权重通过最小化由训练误差项和输出层权重范数的正则项构成的损失函数，(Extreme here means to move beyond conventional artificial learning techniques and to move toward brain alike learning. ELM aims to break the barriers between the conventional artificial learning techniques and biological learning mechanism.)