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Kernel partial least squares(KPLS) is widely adopted for soft-sensing in nonlinear industrial process. For KPLS method, the determination of central nodes and kernel width in the kernel function will affects generalization ability and predictiability. This paper proposes an entropy-clustering and K-means based KPLS regression method. First of all, it divides the original data into several clusters...
Dissolved oxygen directly affects the growth status of fishes in intensive aquaculture, thus we set up a prediction model to determine the future changing trend of dissolved oxygen. The dissolved oxygen prediction model we proposed was based on the least squares support vector regression (LSSVR) model with fruit fly optimization algorithm (FOA) to find optimal parameters (γ and σ) of LSSVR. Because...
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