Photovoltaic fault detection method based on improved particle swarm optimization Elman network
An improved particle swarm and fault detection technology, applied in neural learning methods, biological neural network models, predictions, etc., can solve problems such as failure detection of photovoltaic systems, and achieve easy maintenance and management, high prediction efficiency, and fast speed Effect
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[0040] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.
[0041] The invention relates to a photovoltaic fault detection method based on improved particle swarm optimization Elman network, which comprises the following steps: first, initialize the particle swarm algorithm, then assign initial values to the neural network, train the network to obtain output results, and calculate individual fitness values , and get the individual extremum and the global extremum. Particles update th...
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