检索结果-内蒙古大学图书馆

data-driven approach for measuring and curbing Green House Gases (GHG) emissions in the supply chain of India

JOURNAL OF CLEANER PRODUCTION 2025年 504卷

作者： Pandey, Amitesh Choubey, Vikas Natl Inst Technol Patna India

Global warming has caused significant negative consequences for developing countries like India. The carbon market was considered as an effective solution for curbing Green House Gases (GHG) emissions, which is considered as the primary reason for global warming. Carbon market was established in the Kyoto protocol among developed economies and later extended to developing economies through the Paris Agreement. The international carbon market did not return satisfactory results. However, the Chinese domestic carbon market returned good results motivating the Indian government to create a strategy, policy, and plan for the Indian domestic carbon market. Through a strategic conceptual framework, this research has tried to establish a hypothetical theory that success of carbon market in the supply chain of India would require data-driven approach to measuring and curbing GHG emissions caused by the polluting entities. data-driven approach helps in policy making and actions based on actual measurements instead of speculations. The strategic conceptual framework shows interfacing between the domains of Indian carbon credits policy and the data-driven approach through two government-sponsored and controlled systems: a market exchange and a blockchain. Other components proposed are an accounting system of carbon credits on big data systems and entity-specific cloud-hosted data systems supported by Artificial Intelligence. This research proposed that carbon credits should not be traded as an alternative to implementing technologies and innovations for GHG emissions, and should not have expiry dates. The model may perform better than the European model as it is based on the top-down approach (based on China), adopts Industry 4.0 technologies, active measurements and accounting, smart contracts, and data-driven enforcements. The practical implications of the model may be higher involvement of manufacturing entities in curbing GHG emissions with government-controlled governance

关键词： Carbon trading policy GHG emissions data-driven approach Big data analytics Blockchain

来源：评论

学校读者我要写书评

暂无评论

Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Hybrid Ensembles Allied with data-driven approach

引用

ENERGIES 2025年第5期18卷 1114-1114页

作者： Zhao, Shuai Sun, Daming Liu, Yan Liang, Yuqi Shandong Lab Vocat & Tech Coll Intelligent Mfg Dept Jinan 250300 Peoples R China South China Normal Univ Sch Math Sci Guangzhou 510631 Peoples R China

Capacity fade in lithium-ion batteries (LIBs) poses challenges for various industries. Predicting and preventing this fade is crucial, and hybrid methods for estimating remaining useful life (RUL) have become prevalent and achieved significant advancements. In this paper, we introduce a hybrid voting ensemble that combines Gradient Boosting, Random Forest, and K-Nearest Neighbors to forecast the fading capacity trend and knee point. We conducted extensive experiments using the CALCE CS2 datasets. The results indicate that our proposed approach outperforms single deep learning methods for RUL prediction and accurately identifies the knee point. Beyond prediction, this innovative method can potentially be integrated into real-world applications for broader use.

关键词： lithium-ion battery reaming useful life ensemble learning data-driven approach

来源：评论

学校读者我要写书评

暂无评论

A material handling system modeling framework: a data-driven approach for the generation of discrete-event simulation models

引用

FLEXIBLE SERVICES AND MANUFACTURING JOURNAL 2025年第1期37卷 67-96页

作者： Soufi, Zakarya Mestiri, Slaheddine David, Pierre Yahouni, Zakaria Fottner, Johannes Univ Grenoble Alpes CNRS Grenoble INP G SCOP F-38000 Grenoble France Univ Grenoble Alpes Inst Engn Grenoble France Tech Univ Munich Chair Mat Handling Mat Flow Logist Boltzmannstr 15 D-85748 Munich Germany

The design and reconfiguration of Material Handling Systems (MHSs) at the factory scale are known to be complex. Various design and reconfiguration alternatives have to be considered and evaluated through indicators such as: On Time Delivery (OTD) within the plant, number of material shortages or product waiting time, etc. Due to the dynamic behavior of MHS, simulation-based approaches play an essential role in such analysis. However, developing simulation models for MHS can be time-consuming (especially for modeling Large Scale Systems) and difficult to build (some skills and knowledge are required to use simulation software). To overcome these challenges, data-driven approaches have been proposed in the literature for the generation of MHS simulation models. Nevertheless, the available approaches focus on specific domains and may not always account for all the necessary data, including MHS control policies. Therefore, this paper aims to propose a framework that employs a data catalog regrouping five data categories (layout, product features, production process, material handling process, and MHS control methods) to support the generation of MHS simulation models using SIMIO. The article details the data structure used to gather MHS simulation data, the selection of a simulation tool, the modeling patterns integrated into the simulations, and the application of the transformation rules. The whole approach is implemented to form the generation framework. The framework is designed to assist decision-makers (who have basic simulation knowledge) in the evaluation of MHS design/reconfiguration alternatives. The paper finally presents a validation of the framework on two case studies.

关键词： Manufacturing systems Material handling systems Performance analysis data-driven approach Discrete event simulation

来源：评论

学校读者我要写书评

暂无评论

Multisource data-driven approach for Predicting the Deterioration of High Mast Light Poles along Highways

引用

JOURNAL OF INFRASTRUCTURE SYSTEMS 2025年第1期31卷

作者： Wang, Xin Bai, Yun Rutgers State Univ Dept Civil & Environm Engn Piscataway NJ 08854 USA Hong Kong Univ Sci & Technol Guangzhou Intelligent Transportat Thrust Guangzhou 511458 Guangdong Peoples R China

Predicting the deterioration of high mast light poles (HMLPs) can support capital planning and asset management for highway agencies, such as inspection and maintenance prioritization decisions. This paper aims to develop a data-driven framework for predicting the performance of in-service HMLPs along highways by considering multiple factors including structural and environmental factors. The proposed framework consists of a pipeline of machine learning techniques including data cleaning, feature engineering and data integration, model development, and feature importance identification. Two data-driven models (XGBoost and logistic regression) are developed with the implementation of data oversampling to address imbalanced data issues. The importance level of selected factors is identified to provide insight into the underlying influential mechanism of various factors on the deterioration of HMLP elements because of both fatigue and corrosion effects. The proposed framework is implemented for one element of HMLP as an illustrative example using structural data from manual inspection reports, climatological data (e.g., wind and snow events) from the National Oceanic and Atmospheric Administration (NOAA), and geographical locations from the Geographical Information Systems (GIS) database. The results show that XGBoost with oversampling outperforms other methods. With the implementation of oversampling, the balanced accuracy of the XGBoost model increases from 0.69 to 0.74. The average precision of the best-fit model is 0.88, representing a high level of precision in predicting positive instances correctly across all classes. Feature importance analysis indicates that cumulative time of natural wind with speed from 5 to 15 m/s (days) is the most significant factor affecting the deterioration of HMLPs (797, 1,316, and 1,716 days on average in the data set for condition states 1, 2, 3+4 respectively), followed by the cumulative time of natural wind with speed over 15 m/s

关键词： High mast light poles Condition state data-driven approach Environmental factors Feature importance identification

来源：评论

学校读者我要写书评

暂无评论

Characterization and modeling of GNSS site-specific unmodeled errors under reflection and diffraction using a data-driven approach

引用

SATELLITE NAVIGATION 2025年第1期6卷 1-24页

作者： Zhang, Zhetao Wang, Li Li, Xuezhen Hohai Univ Sch Earth Sci & Engn Nanjing 211100 Peoples R China

Due to the signal reflection and diffraction, site-specific unmodeled errors like multipath effect and Non-Line-of-Sight reception are significant error sources in Global Navigation Satellite System since they cannot be easily mitigated. However, how to characterize and model the internal mechanisms and external influences of these site-specific unmodeled errors are still to be investigated. Therefore, we propose a method for characterizing and modeling site-specific unmodeled errors under reflection and diffraction using a data-driven approach. Specifically, we first consider all the popular potential features, which generate the site-specific unmodeled errors. We then use the random forest regression to comprehensively analyze the correlations between the site-specific unmodeled errors and the potential features. We finally characterize and model the site-specific unmodeled errors. Two 7-consecutive datasets dominated by signal reflection and diffraction were conducted. The results show that there are significant differences in the correlations with potential features. They are highly related to the application scenarios, observation types, and satellite types. Notably, the innovation vector often shows a strong correlation with the code site-specific unmodeled errors. For the phase site-specific unmodeled errors, they have high correlations with elevation, azimuth, number of visible satellites, and between-frequency differenced phase observations. In the environments of reflection and diffraction, the sum of the correlations of the top six potential features can reach approximately 88.5 and 87.7%, respectively. Meanwhile, these correlations are stable for different observation types and satellite types. With the integration of a transformer model with the random forest method, a high-precision unmodeled error prediction model is established, demonstrating the necessity to include multiple features for accurate and efficient characterization and modeling of site-s

关键词： GNSS Site-specific unmodeled error Reflection Diffraction data-driven approach

来源：评论

学校读者我要写书评

暂无评论

Model predictive control for space robot manipulator modeled by switched systems: A data-driven approach

引用

OPTIMAL CONTROL APPLICATIONS & METHODS 2025年第2期46卷 564-582页

作者： Chen, Qixin Zhu, Yanzheng Zhang, Jian Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Shandong Peoples R China

This article investigates the data-driven based model predictive control (MPC) problem for a class of space robot manipulator (SRM). First, the SRM system is modeled as a class of discrete-time switched system to reflect more system characteristics. Second, only the input-state data are used for end-to-end controller design, and the system identification process is avoided. In order to meet the real-time requirements of the manipulator arm angles, a kind of constrained predictive control method is designed to prevent the overheating or damage of SRM motor, optimizing the cost function for each decision cycle under the safe control input constraints. Then, based on the average dwell time method, the asymptotic stability is assured for the presented SRM system. The design conditions for data-driven based MPC are provided in the form of linear matrix inequalities. Finally, the effectiveness and advantage for the developed data-driven based MPC strategy are validated via a case study of SRM system. This article investigates data-driven model predictive control (MPC) for space robot manipulators (SRM). The SRM is modeled as a discrete-time switched system, using input-state data for controller design without system identification. A constrained predictive control method prevents motor overheating while optimizing the cost function within safe limits. The average dwell time method ensures asymptotic stability, and design conditions for the data-driven MPC are provided as linear matrix inequalities. image

关键词： average dwell time data-driven approach model predictive control space robot manipulator switched systems

来源：评论

学校读者我要写书评

暂无评论

A Tensor-Based data-driven approach for Multidimensional Harmonic Retrieval and Its Application for MIMO Channel Sounding

引用

IEEE INTERNET OF THINGS JOURNAL 2025年第3期12卷 2854-2865页

作者： Zhang, Yanming Xu, Wenchao Jin, A-Long Li, Min Yuan, Ping Jiang, Lijun Gao, Steven Chinese Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China Xian Jiaotong Liverpool Univ Dept Commun & Networking Suzhou 215000 Peoples R China Tianjin Univ Sch Microelect Tianjin 300200 Peoples R China Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65409 USA

In wireless channel sounding, accurately estimating multiple parameters within a multipath signal, such as azimuth, elevation, Doppler shift, and delay, necessitates addressing the challenges posed by the multidimensional harmonic retrieval (MHR) problem. To overcome these complexities, we propose a framework based on high-order dynamic mode decomposition (HODMD) that designed for robustly estimating frequencies of interest from high-dimensional sinusoidal signals, particularly in additive white Gaussian noise conditions. The HODMD approach, a hybrid algorithm amalgamating high-order singular value decomposition (HOSVD) and dynamic mode decomposition (DMD), operates by initially decomposing observed tensorial data into a core tensor and R mode matrices through HOSVD. Subsequently, DMD is applied to analyze each mode matrix individually, decomposing it into dynamic modes and DMD eigenvalues. The imaginary component of the DMD eigenvalues yields frequencies along the rth dimension. By uniformly applying this analysis to all mode matrices, multiple frequencies of interest are efficiently obtained. Furthermore, the integration of HOSVD, DMD, and moving average techniques in the proposed method is designed to mitigate noise interference during the MHR process. We conduct several numerical experiments and present a real-life example, i.e., the double-direction multiple-input and multiple-output (MIMO) channel sounding, to validate the effectiveness of the proposed HODMD approach. Results demonstrate that HODMD outperforms comparable approaches, particularly in scenarios characterized by high-signal-to-noise ratios. Notably, the proposed method exhibits the capability to estimate the number of tones in undamped cases during the decomposition process. Hence, our work contributes a practical and effective tensor-based solution to the MHR problem, particularly in the context of channel parameter estimation for MIMO systems.

关键词： Harmonic analysis Tensors Channel estimation Frequency estimation Wireless communication Vectors Transmitting antennas Receiving antennas Matrix decomposition Estimation data-driven approach double-directional multiple-input and multiple-output (MIMO) channel sounding high-order dynamic mode decomposition (HODMD) multidimensional harmonic retrieval (MHR)

来源：评论

学校读者我要写书评

暂无评论

A data-driven approach to Optimize Internal Software Quality and Customer Value Delivery 25th

A Data-Driven Approach to Optimize Internal Software Quality...

引用

25th International Conference on Product Focused Software Process Improvement

作者： Paudel, Bhuwan Gonzalez-Huerta, Javier Mendez, Daniel Klotins, Eriks Blekinge Inst Technol Software Engn Res Lab SERL Karlskrona Sweden

ISBN: (纸本)9783031783913;9783031783920

The growing complexity, the ever-ending demands for new features, and the need to become faster to remain competitive force software development organizations to rethink their development and value delivery practices. While continuous delivery has become more popular, it still relies mainly on internal metrics, ad-hoc data, and expert opinions. As a result, software organizations stumble to find the balance between improving internal system quality and delivering external value. In fact, understanding and measuring customer value is on itself essential. In this PhD project, we aim for a better understanding of customer value and develop measurement instruments to be integrated with internal perspectives to drive proactive and continuous internal improvement while delivering relevant customer value.

关键词： data-driven approach Software Quality Improvement Continuous Customer Value Delivery

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous computing in a strongly-connected CPU-GPU environment: fast multiple time-evolution equation-based modeling accelerated using data-driven approach 24

Heterogeneous computing in a strongly-connected CPU-GPU envi...

引用

Proceedings of the SC '24 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis

作者： Tsuyoshi Ichimura Kohei Fujita Muneo Hori Lalith Maddegedara Jack Wells Alan Gray Ian Karlin John Linford Earthquake Research Institute The University of Tokyo RIKEN Tokyo Japan Research Institute for Value-Added-Information Generation Japan Agency for Marine-Earth Science and Technology Yokohama Japan Earthquake Res. Inst. The University of Tokyo Tokyo Japan NVIDIA Santa Clara CA USA

ISBN: (纸本)9798350355543

We propose a CPU-GPU heterogeneous computing method for solving time-evolution partial differential equation problems many times with guaranteed accuracy, in short time-to-solution and low energy-to-solution. On a single-GH200 node, the proposed method improved the computation speed by 86.4 and 8.67 times compared to the conventional method run only on CPU and only on GPU, respectively. Furthermore, the energy-to-solution was reduced by 32.2-fold (from 9944 J to 309 J) and 7.01-fold (from 2163 J to 309 J) when compared to using only the CPU and GPU, respectively. Using the proposed method on the Alps supercomputer, a 51.6-fold and 6.98-fold speedup was attained when compared to using only the CPU and GPU, respectively, and a high weak scaling efficiency of 94.3% was obtained up to 1,920 compute nodes. These implementations were realized using directive-based parallel programming models while enabling portability, indicating that directives are highly effective in analyses in heterogeneous computing environments.

关键词： data-driven approach

来源：评论

学校读者我要写书评

暂无评论

data-driven approach to iterative learning control via convex optimisation

引用

IET CONTROL THEORY AND APPLICATIONS 2020年第7期14卷 972-981页

作者： Nicoletti, Achille Martino, Michele Aguglia, Davide European Org Nucl Res CERN Dept Technol Geneva Switzerland

A new data-driven iterative learning control methodology is presented which uses the frequency response data of a system in order to avoid the problem of unmodelled dynamics associated with low-order parametric models. A convex optimisation problem is formulated to design the learning filters such that the convergence criterion is minimised. Since the frequency response data of the system is used in obtaining these filters, robustness is ensured by eliminating the uncertainty in the modelling process. The effectiveness of the method is illustrated by considering a case study where the proposed design scheme is applied to a power converter control system for a specific accelerator requirement at CERN.

关键词： control system synthesis robust control learning systems optimisation adaptive control iterative methods nonlinear control systems convex programming frequency response unmodelled dynamics low-order parametric models convex optimisation problem learning filters frequency response data power converter control system data-driven approach learning control methodology

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：