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Analyzing and forecasting the global CO2 concentration - a collaborative fuzzy-neural agent network approach

机译:分析和预测全球CO2浓度-协同模糊神经代理网络方法

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In order to effectively analyze and forecast the global CO2 concentration, a collaborative fuzzy-neural agent network is constructed in this study. In the collaborative fuzzy-neural agent network, a group of autonomous agents is used. These agents are programmed to analyze and forecast the global CO2 concentration using the fuzzy back propagation network (FBPN) approach based on their local views. A collaboration mechanism is established to communicate the settings and forecasts of these agents, and to derive a single representative value from these forecasts using a radial basis function network. The real data were used to evaluate the effectiveness of the collaborative fuzzy-neural agent network approach.
机译:为了有效地分析和预测全球二氧化碳浓度,本研究建立了一个协同的模糊神经网络。在协作模糊神经代理网络中,使用了一组自治代理。这些代理程序经过编程,可根据其本地视图使用模糊反向传播网络(FBPN)方法分析和预测全球CO2浓度。建立协作机制以传达这些代理的设置和预测,并使用径向基函数网络从这些预测中得出单个代表值。真实数据用于评估协同模糊神经代理网络方法的有效性。

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