標(biāo)題: Titlebook: Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research; Chao Shang Book 2018 Springer Nature Singa [打印本頁] 作者: Flippant 時間: 2025-3-21 16:05
書目名稱Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research影響因子(影響力)
書目名稱Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research影響因子(影響力)學(xué)科排名
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書目名稱Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research被引頻次
書目名稱Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research被引頻次學(xué)科排名
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書目名稱Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research年度引用學(xué)科排名
書目名稱Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research讀者反饋
書目名稱Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research讀者反饋學(xué)科排名
作者: 說笑 時間: 2025-3-21 21:45 作者: immunity 時間: 2025-3-22 00:41
Chao ShangNominated as an outstanding PhD thesis by Tsinghua University.Develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle.Proposes an e作者: HARP 時間: 2025-3-22 06:50 作者: GULF 時間: 2025-3-22 11:11
Rohstoffwirtschaftliche EntwicklungshilfeThis chapter summarizes the whole work of this thesis, and some challenges on data-driven modeling methodologies and industrial applications are pointed out as the future work.作者: 彎曲道理 時間: 2025-3-22 15:07
Conclusions and Recommendations,This chapter summarizes the whole work of this thesis, and some challenges on data-driven modeling methodologies and industrial applications are pointed out as the future work.作者: 彎曲道理 時間: 2025-3-22 20:11 作者: 危險 時間: 2025-3-23 00:11
Problemstellung und Zielsetzung,ondition is detected, an alarm is triggered based on classical monitoring methods. Consequently, they cannot distinguish real faults incurring dynamics anomalies from normal deviations in operating conditions. In this chapter, a new process monitoring strategy based on slow feature analysis (SFA) is作者: scotoma 時間: 2025-3-23 02:34
O. Frankl,K. Kaufmann,O. Schult?-Braunsdynamics described by SFA essentially is related to control performance. Then we propose a new data-driven control performance monitoring approach based on SFA. In addition, by employing the contribution plot techniques, we further develop a new control performance diagnosis method to locate potenti作者: Contracture 時間: 2025-3-23 08:05 作者: 記憶法 時間: 2025-3-23 13:16
https://doi.org/10.1007/978-3-642-47993-9 process data. In this chapter, we develop a new soft sensor model called probabilistic slow feature regression (PSFR). Slow features as temporally correlated LVs are first derived using probabilistic slow feature analysis (PSFA). Probabilistic slow features that evolve in a state-space form effecti作者: excursion 時間: 2025-3-23 17:44
Rohstoffwirtschaftliche Entwicklungshilfeng process dynamics appropriately. Hence, a series of limitations in practice are incurred, such as sensitivity to temporal noises and inadequate descriptions to process dynamics. Because of these concerns, static models have been extended to dynamic counterparts such dynamic partial least squares (作者: 陰謀小團(tuán)體 時間: 2025-3-23 19:09
Rohstoffwirtschaftliche Entwicklungshilfee whole model has a Wiener structure, in which nonlinearity and dynamics are described separately. In addition, a novel four-level Bayesian framework is developed to probabilistically illustrate and iteratively optimize the proposed model, which helps alleviating the over-fitting phenomenon automati作者: 顯微鏡 時間: 2025-3-23 22:51 作者: 坦白 時間: 2025-3-24 05:20 作者: 一再困擾 時間: 2025-3-24 08:28
2190-5053 ocesses in keeping with the slowness principle.Proposes an e.This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle. Using said framework as a point of departure, it then proposes novel strategies for dealing with cont作者: expunge 時間: 2025-3-24 11:41
Problemstellung und Zielsetzung,ensor modeling is given. Third, the opportunities and challenges in advancing industrial applications of process data analytics are highlighted. Finally, the main contents and the layout of this thesis are provided.作者: 無思維能力 時間: 2025-3-24 14:58
Book 2018framework as a point of departure, it then proposes novel strategies for dealing with control monitoring and quality prediction problems in industrial production contexts..The thesis reveals the slowly varying nature of industrial production processes under feedback control, and integrates it with p作者: 強化 時間: 2025-3-24 20:34 作者: 珍奇 時間: 2025-3-24 23:40 作者: Trypsin 時間: 2025-3-25 04:29
Monitoring of Operating Condition and Process Dynamics with Slow Feature Analysis,, two novel indices are proposed to detect anomalies in process dynamics through the slowness of LVs. The proposed approach can distinguish whether normal changes in operating conditions or real faults occur. Two case studies show the validity of the SFA-based process monitoring approach.作者: 慢跑 時間: 2025-3-25 10:07
Recursive SFA Algorithm and Adaptive Monitoring System Design, statistics related to process dynamics, which provides an intelligent maintenance mechanism of monitoring systems. The efficacy of the proposed schema is finally evaluated on a industrial crude heating furnace system.作者: 觀察 時間: 2025-3-25 13:25
Introduction,ensor modeling is given. Third, the opportunities and challenges in advancing industrial applications of process data analytics are highlighted. Finally, the main contents and the layout of this thesis are provided.作者: Indent 時間: 2025-3-25 19:00
Rohstoffwirtschaftliche Entwicklungshilfecally. Case studies based on a numerical example and an industrial application in propylene melt index prediction are presented to demonstrate the advantages of the proposed method over classic dynamic soft sensing models.作者: 品牌 時間: 2025-3-25 23:05 作者: insecticide 時間: 2025-3-26 01:16 作者: 小鹿 時間: 2025-3-26 08:16 作者: 貿(mào)易 時間: 2025-3-26 09:21
Probabilistic Slow Feature Regression for Dynamic Soft Sensing,on performance of soft sensors when used as inputs. An efficient expectation maximization algorithm is proposed to estimate parameters of the PSFA model, and two alternative criteria are put forward to select quality-relevant SFs in the PSFR model. The validity and advantages of the proposed method are demonstrated via two case studies.作者: acheon 時間: 2025-3-26 14:50
Introduction,agnosis in industrial processes is introduced. Then an extensive review of existing research on multivariate statistical process monitoring and soft sensor modeling is given. Third, the opportunities and challenges in advancing industrial applications of process data analytics are highlighted. Final作者: Unsaturated-Fat 時間: 2025-3-26 20:10
Monitoring of Operating Condition and Process Dynamics with Slow Feature Analysis,ondition is detected, an alarm is triggered based on classical monitoring methods. Consequently, they cannot distinguish real faults incurring dynamics anomalies from normal deviations in operating conditions. In this chapter, a new process monitoring strategy based on slow feature analysis (SFA) is作者: esoteric 時間: 2025-3-26 21:24 作者: 阻塞 時間: 2025-3-27 03:09 作者: 微塵 時間: 2025-3-27 05:33 作者: 戰(zhàn)勝 時間: 2025-3-27 13:08
Enhanced Dynamic PLS with Temporal Smoothness for Soft Sensing,ng process dynamics appropriately. Hence, a series of limitations in practice are incurred, such as sensitivity to temporal noises and inadequate descriptions to process dynamics. Because of these concerns, static models have been extended to dynamic counterparts such dynamic partial least squares (作者: 擁擠前 時間: 2025-3-27 15:35
Nonlinear Dynamic Soft Sensing Based on Bayesian Inference,e whole model has a Wiener structure, in which nonlinearity and dynamics are described separately. In addition, a novel four-level Bayesian framework is developed to probabilistically illustrate and iteratively optimize the proposed model, which helps alleviating the over-fitting phenomenon automati作者: 的染料 時間: 2025-3-27 18:53 作者: 裝勇敢地做 時間: 2025-3-27 23:17
2190-5053 zing the information underlying the data. One of the strengths of this thesis is its integration of insights from statistics, machine learning, control theory and engineering to provide a new scheme for industr978-981-13-3889-2978-981-10-6677-1Series ISSN 2190-5053 Series E-ISSN 2190-5061 作者: myopia 時間: 2025-3-28 02:32
Enhanced Dynamic PLS with Temporal Smoothness for Soft Sensing,which is used as a valid prior knowledge. In this manner, abrupt changes in model dynamics are properly penalized and the DPLS-based soft sensors enjoy better generalizations and interpretations. A numerical example and the Tennessee Eastman process case study are provided to show the feasibility as作者: ACRID 時間: 2025-3-28 08:52 作者: 流行 時間: 2025-3-28 12:36
Rohstoffwirtschaftliche Entwicklungshilfewhich is used as a valid prior knowledge. In this manner, abrupt changes in model dynamics are properly penalized and the DPLS-based soft sensors enjoy better generalizations and interpretations. A numerical example and the Tennessee Eastman process case study are provided to show the feasibility as作者: FLACK 時間: 2025-3-28 16:42 作者: 牙齒 時間: 2025-3-28 20:53 作者: Resection 時間: 2025-3-29 00:46
