使固定
发表于 2025-3-21 18:16:25
书目名称Data-Driven Prediction for Industrial Processes and Their Applications影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0263309<br><br> <br><br>书目名称Data-Driven Prediction for Industrial Processes and Their Applications影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0263309<br><br> <br><br>书目名称Data-Driven Prediction for Industrial Processes and Their Applications网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0263309<br><br> <br><br>书目名称Data-Driven Prediction for Industrial Processes and Their Applications网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0263309<br><br> <br><br>书目名称Data-Driven Prediction for Industrial Processes and Their Applications被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0263309<br><br> <br><br>书目名称Data-Driven Prediction for Industrial Processes and Their Applications被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0263309<br><br> <br><br>书目名称Data-Driven Prediction for Industrial Processes and Their Applications年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0263309<br><br> <br><br>书目名称Data-Driven Prediction for Industrial Processes and Their Applications年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0263309<br><br> <br><br>书目名称Data-Driven Prediction for Industrial Processes and Their Applications读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0263309<br><br> <br><br>书目名称Data-Driven Prediction for Industrial Processes and Their Applications读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0263309<br><br> <br><br>
Abominate
发表于 2025-3-21 23:45:07
Data Preprocessing Techniques,employed to construct a prediction model, given that such data are always mixed with high level noise, missing points, and outliers due to the possible real-time database malfunction, data transformation, or maintenance. Thereby, the data preprocessing techniques have to be implemented, which usuall
Interdict
发表于 2025-3-22 03:39:47
Industrial Time Series Prediction,dden behind the time series data of the variables by means of auto-regression. In this chapter we introduce the phase space reconstruction technique, which aims to construct the training dataset for modeling, and then a series of data-driven machine learning methods are provided for time series pred
STALE
发表于 2025-3-22 07:30:48
Factor-Based Industrial Process Prediction, of approaches construct a forecasting model by treating the process variables (not the output or target variables) called “factors” as the model inputs, rather than the auto-regression mode used in time series version. To select the factors from lots of candidates, this chapter firstly introduces s
玷污
发表于 2025-3-22 10:41:42
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拖债
发表于 2025-3-22 13:46:44
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拖债
发表于 2025-3-22 18:47:26
Parameter Estimation and Optimization,ed parameter optimization and estimation methods, such as the gradient-based methods (e.g., gradient descend, Newton method, and conjugate gradient method) and the intelligent optimization ones (e.g., genetic algorithm, differential evolution algorithm, and particle swarm optimization). In particula
Comprise
发表于 2025-3-22 23:47:41
Parallel Computing Considerations,ce a production process usually requires real-time responses. The commonly used method to accelerate the training process is to develop a parallel computing framework. In literature, two kinds of popular methods speeding up the training involves the one with a computer equipped with graphics process
混合,搀杂
发表于 2025-3-23 03:45:33
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禁令
发表于 2025-3-23 06:44:11
2510-1528 tion, multi-type prediction (time series and factor-based), This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in