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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Bat algorithm-based back propagation approach for short-term load forecasting considering weather factors
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Day-ahead electricity price forecasting using back propagation neural networks and weighted least square technique
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Flink: Semantic Web technology for the extraction and analysis of social networks
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Machine Learning With Big Data: Challenges and Approaches
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Parallel Processing of Probabilistic Models-Based Power Supply Unit Mid-Term Load Forecasting With Apache Spark
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A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
inferredcites →https://doi.org/10.1109/cibd.2014.7011537openalex-snapshot
A scalable machine learning online service for big data real-time analysis
inferredcites →https://doi.org/10.1109/ki48306.2020.9039797openalex-snapshot
Performance Evaluation of Distributed Machine Learning for Load Forecasting in Smart Grids
inferredcites →https://doi.org/10.1109/naps.2014.6965453openalex-snapshot
Short term electrical load forecasting using back propagation neural networks
inferredcites →https://doi.org/10.1109/tbdata.2016.2622288openalex-snapshot
Fuzzy Based Scalable Clustering Algorithms for Handling Big Data Using Apache Spark
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i $^2$ MapReduce: Incremental MapReduce for Mining Evolving Big Data
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Deep Learning for Household Load Forecasting—A Novel Pooling Deep RNN
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Statistical Load Forecasting Using Optimal Quantile Regression Random Forest and Risk Assessment Index
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Classification and regression
inferredcites →https://doi.org/10.26599/tst.2019.9010054openalex-snapshot
Balance resource allocation for spark jobs based on prediction of the optimal resource
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MLlib: Machine Learning in Apache Spark
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Core Vector Machines: Fast SVM Training on Very Large Data Sets
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Dynamic data replacement and adaptive scheduling policies in spark
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