The paper aims to study the importance of low-carbon landscape design based on rural tourism landscape. First of all, after sorting out and researching the relevant reviews of low-carbon landscapes, taking rural landscapes as the research object, a rural landscape planning and design framework based on the perspective of low-carbon construction is proposed. Then, Xiwuli Village is used as an example to carry out the application practice of specific strategies and the carbon emissions before and after the planning and design are calculated and compared. After the low-carbon planning and design of the rural landscape, the net carbon footprint and the total carbon footprint were significantly reduced, confirming the low-carbon effect of the planning and design strategy. Finally, according to the actual situation of the scenic spot, it points out the principles and policy suggestions that must be followed in the development of low-carbon rural tourism. Experiments show that: the net carbon footprint and total carbon footprint are significantly reduced, which proves the actual effect of low-carbon design and the effect of low-carbon planning and design strategy.
Aiming at the disadvantage that traditional PID controller parameter canâ??t be adjusted online timely, control effect is not ideal. this paper introduces a PID control algorithm based on the BP neural network by melting the regular PID controller and the self-turning learning neural network. The algorithm uses the BP neural network to build system parameter model, is able to track the changes of the controlled object, achieves a higher recognition accuracy. It amends the BP neural network weight coefficients by the BP algorithm, realizes adjustment of the PID parameters online. The results of the simulation show that these formulae has fast convergence ?high precision? and robustness.
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