標(biāo)題: Titlebook: Smart Meter Data Analytics; Electricity Consumer Yi Wang,Qixin Chen,Chongqing Kang Book 2020 Science Press and Springer Nature Singapore Pt [打印本頁(yè)] 作者: Magnanimous 時(shí)間: 2025-3-21 19:05
書目名稱Smart Meter Data Analytics影響因子(影響力)
書目名稱Smart Meter Data Analytics影響因子(影響力)學(xué)科排名
書目名稱Smart Meter Data Analytics網(wǎng)絡(luò)公開度
書目名稱Smart Meter Data Analytics網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Smart Meter Data Analytics被引頻次
書目名稱Smart Meter Data Analytics被引頻次學(xué)科排名
書目名稱Smart Meter Data Analytics年度引用
書目名稱Smart Meter Data Analytics年度引用學(xué)科排名
書目名稱Smart Meter Data Analytics讀者反饋
書目名稱Smart Meter Data Analytics讀者反饋學(xué)科排名
作者: 反抗者 時(shí)間: 2025-3-22 00:16 作者: 偽善 時(shí)間: 2025-3-22 00:56
http://image.papertrans.cn/s/image/868878.jpg作者: 影響帶來(lái) 時(shí)間: 2025-3-22 04:59
https://doi.org/10.1007/978-981-15-2624-4Smart Grid; Data Analytics; Smart Meter; Machine Learning; Consumer Behavior; Consumer Segmentation; Price作者: 放肆的你 時(shí)間: 2025-3-22 12:11 作者: 彎彎曲曲 時(shí)間: 2025-3-22 16:12 作者: 試驗(yàn) 時(shí)間: 2025-3-22 20:29
Yi Wang,Qixin Chen,Chongqing Kangth at universities and companies worldwide. All chapters have been drawn up specifically for self-study. They aim, however, at different levels of understanding. All the chapters start with elementary material, but most also contain advanced material. .978-1-4899-7915-5978-0-387-71713-5Series ISSN 1558-9412 Series E-ISSN 1558-9420 作者: 去才蔑視 時(shí)間: 2025-3-23 00:07
Yi Wang,Qixin Chen,Chongqing Kangth at universities and companies worldwide. All chapters have been drawn up specifically for self-study. They aim, however, at different levels of understanding. All the chapters start with elementary material, but most also contain advanced material. .978-1-4899-7915-5978-0-387-71713-5Series ISSN 1558-9412 Series E-ISSN 1558-9420 作者: 武器 時(shí)間: 2025-3-23 04:19
Yi Wang,Qixin Chen,Chongqing Kangth at universities and companies worldwide. All chapters have been drawn up specifically for self-study. They aim, however, at different levels of understanding. All the chapters start with elementary material, but most also contain advanced material. .978-1-4899-7915-5978-0-387-71713-5Series ISSN 1558-9412 Series E-ISSN 1558-9420 作者: committed 時(shí)間: 2025-3-23 07:04
Yi Wang,Qixin Chen,Chongqing Kangth at universities and companies worldwide. All chapters have been drawn up specifically for self-study. They aim, however, at different levels of understanding. All the chapters start with elementary material, but most also contain advanced material. .978-1-4899-7915-5978-0-387-71713-5Series ISSN 1558-9412 Series E-ISSN 1558-9420 作者: GRIPE 時(shí)間: 2025-3-23 11:01 作者: 把…比做 時(shí)間: 2025-3-23 16:59
Yi Wang,Qixin Chen,Chongqing Kangth at universities and companies worldwide. All chapters have been drawn up specifically for self-study. They aim, however, at different levels of understanding. All the chapters start with elementary material, but most also contain advanced material. .978-1-4899-7915-5978-0-387-71713-5Series ISSN 1558-9412 Series E-ISSN 1558-9420 作者: nocturia 時(shí)間: 2025-3-23 20:21
Yi Wang,Qixin Chen,Chongqing Kangth at universities and companies worldwide. All chapters have been drawn up specifically for self-study. They aim, however, at different levels of understanding. All the chapters start with elementary material, but most also contain advanced material. .978-1-4899-7915-5978-0-387-71713-5Series ISSN 1558-9412 Series E-ISSN 1558-9420 作者: PLAYS 時(shí)間: 2025-3-23 23:22
Yi Wang,Qixin Chen,Chongqing Kangth at universities and companies worldwide. All chapters have been drawn up specifically for self-study. They aim, however, at different levels of understanding. All the chapters start with elementary material, but most also contain advanced material. .978-1-4899-7915-5978-0-387-71713-5Series ISSN 1558-9412 Series E-ISSN 1558-9420 作者: 尖酸一點(diǎn) 時(shí)間: 2025-3-24 06:09 作者: apropos 時(shí)間: 2025-3-24 08:13
Yi Wang,Qixin Chen,Chongqing Kangth at universities and companies worldwide. All chapters have been drawn up specifically for self-study. They aim, however, at different levels of understanding. All the chapters start with elementary material, but most also contain advanced material. .978-1-4899-7915-5978-0-387-71713-5Series ISSN 1558-9412 Series E-ISSN 1558-9420 作者: 愛(ài)花花兒憤怒 時(shí)間: 2025-3-24 11:06 作者: Calculus 時(shí)間: 2025-3-24 17:49 作者: 上坡 時(shí)間: 2025-3-24 19:51 作者: amplitude 時(shí)間: 2025-3-25 02:39 作者: 脾氣暴躁的人 時(shí)間: 2025-3-25 05:32 作者: 使顯得不重要 時(shí)間: 2025-3-25 11:03
Partial Usage Pattern Extraction,he extracted patterns. Comprehensive comparisons with the results of .-means clustering, the discrete wavelet transform (DWT), principal component analysis (PCA), and piecewise aggregate approximation (PAA) are conducted on real datasets in Ireland. The results show that our proposed technique outpe作者: 調(diào)情 時(shí)間: 2025-3-25 15:21 作者: 古老 時(shí)間: 2025-3-25 16:17 作者: 富饒 時(shí)間: 2025-3-25 21:22
Clustering of Consumption Behavior Dynamics,y carried out to obtain the typical dynamics of consumer behavior, with the difference between any two consumption patterns measured by the Kullback–Liebler (K–L) distance, and to classify the customers into several clusters. To tackle the challenges of big data, the CFSFDP technique is integrated i作者: Soliloquy 時(shí)間: 2025-3-26 03:11
Aggregated Load Forecasting with Sub-profiles,ing the number of clusters. Finally, an optimal weighted ensemble approach is employed to combine these forecasts and provide the final forecasting result. Case studies are conducted on two open datasets and verify the effectiveness and superiority of the proposed method.作者: cogent 時(shí)間: 2025-3-26 06:28 作者: 起波瀾 時(shí)間: 2025-3-26 09:19 作者: defeatist 時(shí)間: 2025-3-26 14:36
Book 2020umer behavior modeling and distribution system operations. It begins with an overview of recent developments in smart meter data analytics. Since data management is the basis of further smart meter data analytics and its applications, three issues on data management, i.e., data compression, anomaly 作者: STALE 時(shí)間: 2025-3-26 18:26 作者: 加強(qiáng)防衛(wèi) 時(shí)間: 2025-3-26 21:29 作者: 削減 時(shí)間: 2025-3-27 04:18 作者: Exclude 時(shí)間: 2025-3-27 06:00
Electricity Theft Detection,nd more difficult to detect. Thus, a data analytics method for detecting various types of electricity thefts is required. However, the existing methods either require a labeled dataset or additional system information which is difficult to obtain in reality or have poor detection accuracy. In this c作者: BABY 時(shí)間: 2025-3-27 11:52 作者: 不可知論 時(shí)間: 2025-3-27 15:45
Partial Usage Pattern Extraction,ommunication and storage of big data from smart meters at a reduced cost which has been discussed in Chap. .. The other one is the effective extraction of useful information from this massive dataset. In this chapter, the K-SVD sparse representation technique, which includes two phases (dictionary l作者: resuscitation 時(shí)間: 2025-3-27 21:30 作者: 正面 時(shí)間: 2025-3-28 01:45
Socio-demographic Information Identification, automatically extracts features from massive load profiles. A support vector machine (SVM) then identifies the characteristics of the consumers. Comprehensive comparisons with state-of-the-art and advanced machine learning techniques are conducted. Case studies on an Irish dataset demonstrate the e作者: hematuria 時(shí)間: 2025-3-28 02:56 作者: 種族被根除 時(shí)間: 2025-3-28 07:10
Clustering of Consumption Behavior Dynamics, customers’ electricity consumption behaviors via load profiling. Instead of focusing on the shape of the load curves, this chapter proposes a novel approach for the clustering of electricity consumption behavior dynamics, where “dynamics” refer to transitions and relations between consumption behav作者: Endoscope 時(shí)間: 2025-3-28 11:18
Probabilistic Residential Load Forecasting,forecasting possible. Compared to aggregated loads, load forecasting for individual consumers is prone to non-stationary and stochastic features. In this chapter, a probabilistic load forecasting method for individual consumers is proposed to handle the variability and uncertainty of future load pro作者: muster 時(shí)間: 2025-3-28 16:27 作者: Oscillate 時(shí)間: 2025-3-28 21:02 作者: remission 時(shí)間: 2025-3-29 02:40 作者: bizarre 時(shí)間: 2025-3-29 04:07 作者: 完成 時(shí)間: 2025-3-29 09:37 作者: Spongy-Bone 時(shí)間: 2025-3-29 14:12
Probabilistic Residential Load Forecasting,sed point forecasting is extended to probabilistic forecasting in the form of quantiles. Numerical experiments are conducted on an open dataset from Ireland. Forecasting for both residential and commercial consumers is tested. Results show that the proposed method has superior performance over traditional methods.作者: 抱狗不敢前 時(shí)間: 2025-3-29 17:09
Socio-demographic Information Identification,rehensive comparisons with state-of-the-art and advanced machine learning techniques are conducted. Case studies on an Irish dataset demonstrate the effectiveness of the proposed deep CNN-based method, which achieves higher accuracy in identifying the socio-demographic information about the consumers.作者: 言外之意 時(shí)間: 2025-3-29 23:24 作者: 變色龍 時(shí)間: 2025-3-30 03:33
engineers.Low Power Design Essentials contains all the topics of importance to the low power designer. The book lays the foundation with background chapters entitled “Advanced MOS Transistors and Their Models” and “Power Basics”. These chapters are followed by chapters on the design process includi作者: Interdict 時(shí)間: 2025-3-30 05:11 作者: relieve 時(shí)間: 2025-3-30 08:15 作者: Loathe 時(shí)間: 2025-3-30 14:58 作者: 畸形 時(shí)間: 2025-3-30 19:29 作者: Nomogram 時(shí)間: 2025-3-31 00:00
Yi Wang,Qixin Chen,Chongqing Kang engineers.Low Power Design Essentials contains all the topics of importance to the low power designer. The book lays the foundation with background chapters entitled “Advanced MOS Transistors and Their Models” and “Power Basics”. These chapters are followed by chapters on the design process includi
