The MKL subnetwork was highly enriched with these processes, outperforming the ANAT and the Steiner subnetworks (Table 2).
Compared to the results of traditional statistical testing (PFER=2.5596, FDR=0.01), our results show that the coupled statistical process outperforms the sensitivity of a parametric traditional statistical test that requires strong and sometimes untenable data assumptions since it is non-parametric and requires no assumption about the distribution under the null hypothesis.
For a realistic scenario constructed using historical data, optimization results indicate that both advanced processes outperform MEA in both objectives, and the mixed-salt process in turn outperforms the piperazine process.
The optimal purification processes discovered outperform the industrial standard with, e.g. savings in COG/g of up to 10%.
The results show that the personalized occupancy profiles acquired through time-series modeling, pattern recognition modeling and stochastic process modeling outperform the fixed design profiles and observation-based profiles currently used in building energy simulations.
In general, the centralized AS process outperformed those decentralized processes (i.e., CW, SP and MP) and a higher removal of E1, EE2, NP and BPA in the AS process was observed in summer (>70%) than in winter.
Therefore, the proposed solution, leveraging the fusion based on the distributions and the learning process, is able to outperform the other realistic distributed decoders.
We find that the proposed extension of the Gaussian process regression outperforms the benchmark model in most regions, especially for intermediate forecast horizons.
The resultant composite membrane exhibited a k0 of 18.3 ± 1.3 × 10−7 m/s in an aqueous-aqueous extractive process, significantly outperforming the commercial counterpart with 45% increment.
In addition, as mentioned earlier, the OP process clearly outperforms the WW route in terms of water usage.
