A Least Squares Ensemble Model Based on Regularization and Augmentation Strategy

Surrogate models are often used as alternatives to considerably reduce the computational burden of the expensive computer simulations that are required for engineering designs. The development of surrogate models for complex relationships between the parameters often requires the modeling of high-dimensional functions with limited information, and it is challenging to choose an effective surrogate model over the unknown design space. To this end, the ensemble models—combined with different surrogate models—offer effective solutions. This paper presents a new ensemble model based on the least squares method, which is a regularization strategy and an augmentation strategy; we call the model the regularized least squares ensemble model (RLS-EM). Three individual surrogate models—Kriging, radial basis function, and support vector regression—are used to compose the RLS-EM. Further, the weight factors are estimated by the least squares method without using the global or local error metrics, which are used in most existing methods. To solve the collinearity in the least squares calculation process, a regularization strategy and an augmentation strategy are developed. The two strategies help explore the unknown regions and improve the accuracy on one hand; on the other hand, the collinearity can be reduced, and the overfitting phenomenon that may occur can be avoided. Six numerical functions, from two-dimensional to 12-dimensional, and a computer numerical control (CNC) milling machine bed design problem are used to verify the proposed method. The results of the numerical examples show that RLS-EM saves a considerable amount of computation time while ensuring the same level of robustness and accuracy compared with other ensemble models. The RLS-EM used for the CNC milling machine bed design problem also shows good accuracy characteristics compared with other ensemble methods

Energy and exergy co-optimization of IGCC with lower emissions based on fuzzy supervisory predictive control

This paper presents an energy and exergy co-optimization method of integrated gasification combined cycle (IGCC) based on Fuzzy Supervisory Predictive Control (FSPC). Firstly, a green IGCC process is proposed which contains three principle couplings: air separation unit (ASU), heat recovery steam generator (HRSG) and CO2 capture/storage unit (CCS). From law of thermodynamics, using substance thermophysical parameters, the energy efficiency and exergy efficiency of IGCC are successively defined. The IGCC power station has features such as closed coupling, large time lag and non-linearity, however, faster response speed and lower overshoot are always the unremitting pursuits. Therefore, the Fuzzy Supervisory Predictive Control (FSPC) method is proposed to implement robust control under complex disturbances by pre-considering unmeasurable disturbance and measurable disturbance. The fuzzy rules extracted from historical bigdata are employed in supervisory layer to make the precise control decisions. Finally, the energy and exergy co-optimization model is built and solved for higher efficiency and economic effectiveness. Taking the large-scale (300MW) IGCC for example, after using FSPC, the efficiency of water recovery is increased from 40.7% to 62.1% with the ratio of 52.6% because of waste water recovery (WWR) system. The net efficiency of proposed IGCC system is increased from 37.6% to 41.7% with the ratio of 10.9%. The exergy efficiency of IGCC system is increased from 36.5% to 39.2% with the ratio of 7.4%. The proposed method has great significance for the energy-saving and Near-zero emissions (NZEC) IGCC with high safety and robust control under supercritical (SC) or ultra-super critical (USC) state

Estimating the influencing factors for T1b/T2 gallbladder cancer on survival and surgical approaches selection

Abstract Background The influencing factors, especially time to treatment (TTT), for T1b/T2 gallbladder cancer (GBC) patients remain unknown. We aimed to identify the influencing factors on survival and surgical approaches selection for T1b/T2 GBC. Methods We retrospectively screened GBC patients between January 2011 and August 2018 from our hospital. Clinical variables, including patient characteristics, TTT, overall survival (OS), disease‐free survival (DFS), surgery‐related outcomes, and surgical approaches were collected. Results A total of 114 T1b/T2 GBC patients who underwent radical resection were included. Based on the median TTT of 7.5 days, the study cohort was divided into short TTT group (TTT ≤7 days, n = 57) and long TTT group (TTT >7 days, n = 57). Referrals were identified as the primary factor prolonging TTT (p  0.05) between both groups. Decreased referrals (p = 0.005), fewer positive lymph nodes (LNs; p = 0.004), and well tumor differentiation (p = 0.004) were all associated with better OS, while fewer positive LNs (p = 0.049) were associated with better DFS. Subgroup analyses revealed no significant difference in survival between patients undergoing laparoscopic or open approach in different TTT groups (all p > 0.05). And secondary subgroup analyses found no significance in survival and surgery‐related outcomes between different TTT groups of incidental GBC patients (all p > 0.05). Conclusions Positive LNs and tumor differentiation were prognostic factors for T1b/T2 GBC survival. Referrals associating with poor OS would delay TTT, while the prolonged TTT would not impact survival, surgery‐related outcomes, and surgical approaches decisions in T1b/T2 GBC patients

Hepatopancreatoduodenectomy for advanced biliary malignancies

Abstract. Background:. Hepatopancreatoduodenectomy (HPD) has been considered the only curative treatment for metastatic cholangiocarcinoma and some locally advanced gallbladder cancers (GBCs). However, HPD has not yet been included in treatment guidelines as a standard surgical procedure in consideration of its morbidity and mortality rates. The aim of this study was to evaluate the safety and effectiveness of HPD in treating biliary malignancies. Methods:. The medical records of 57 patients with advanced biliary cancer undergoing HPD from January 2009 to December 2019 were retrospectively retrieved. A case-control analysis was conducted at our department. Patients with advanced GBC who underwent HPD (HPD-GBC group) were compared with a control group (None-HPD-GBC group). Baseline characteristics, preoperative treatments, tumor pathologic features, operative results, and prognosis were assessed. Results:. Thirteen patients with cholangiocarcinoma and 44 patients with GBC underwent HPD at our department. Significant postoperative complications (grade III or greater) and postoperative pancreatic fistula were observed in 24 (42.1%) and 15 (26.3%) patients, respectively. One postoperative death occurred in the present study. Overall survival (OS) was longer in patients with advanced cholangiocarcinoma than in those with GBC (median survival time [MST], 31 months vs. 11 months; P < 0.001). In the subgroup analysis of patients with advanced GBC, multivariate analysis demonstrated that T4 stage tumors (P = 0.012), N2 tumors (P = 0.001), and positive margin status (P = 0.004) were independently associated with poorer OS. Patients with either one or more prognostic factors exhibited a shorter MST than patients without those prognostic factors (P < 0.001). Conclusion:. HPD could be performed with a relatively low mortality rate and an acceptable morbidity rate in an experienced high- volume center. For patients with advanced GBC without an N2 or T4 tumor, HPD can be a preferable treatment option