为了优化气象装备的管理效率和保障能力,加强气象装备应急储备管理,提出一种基于RFID(Radio Frequency Identification)技术、手持设备和Web开发相结合的气象装备全寿命跟踪系统平台。该系统根据气象装备在全国范围内的调配和仓储等业...为了优化气象装备的管理效率和保障能力,加强气象装备应急储备管理,提出一种基于RFID(Radio Frequency Identification)技术、手持设备和Web开发相结合的气象装备全寿命跟踪系统平台。该系统根据气象装备在全国范围内的调配和仓储等业务需求,实现全国气象装备管理一体化和业务统一化,为装备的管理及有效利用提供了方便;通过跟踪气象装备的状态信息(包括仓储信息、基本设备信息、业务状态等),为装备管理提供了更加详细的参考依据。结合气象装备编码规则的研究成果,为每个气象设备进行唯一标识,同时也为气象装备寿命的预测提供了实际参考数据。展开更多
Aiming at the disadvantages of BP model in artificial neural networks applied to intelligent fault diagnosis, neural network fault diagnosis optimization method with rough sets and genetic algorithms are presented. Th...Aiming at the disadvantages of BP model in artificial neural networks applied to intelligent fault diagnosis, neural network fault diagnosis optimization method with rough sets and genetic algorithms are presented. The neural network nodes of the input layer can be calculated and simplified through rough sets theory; The neural network nodes of the middle layer are designed through genetic algorithms training; the neural network bottom-up weights and bias are obtained finally through the combination of genetic algorithms and BP algorithms. The analysis in this paper illustrates that the optimization method can improve the performance of the neural network fault diagnosis method greatly.展开更多
文摘为了优化气象装备的管理效率和保障能力,加强气象装备应急储备管理,提出一种基于RFID(Radio Frequency Identification)技术、手持设备和Web开发相结合的气象装备全寿命跟踪系统平台。该系统根据气象装备在全国范围内的调配和仓储等业务需求,实现全国气象装备管理一体化和业务统一化,为装备的管理及有效利用提供了方便;通过跟踪气象装备的状态信息(包括仓储信息、基本设备信息、业务状态等),为装备管理提供了更加详细的参考依据。结合气象装备编码规则的研究成果,为每个气象设备进行唯一标识,同时也为气象装备寿命的预测提供了实际参考数据。
文摘Aiming at the disadvantages of BP model in artificial neural networks applied to intelligent fault diagnosis, neural network fault diagnosis optimization method with rough sets and genetic algorithms are presented. The neural network nodes of the input layer can be calculated and simplified through rough sets theory; The neural network nodes of the middle layer are designed through genetic algorithms training; the neural network bottom-up weights and bias are obtained finally through the combination of genetic algorithms and BP algorithms. The analysis in this paper illustrates that the optimization method can improve the performance of the neural network fault diagnosis method greatly.
