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zhu j data enabled analytics dea big data 2021

Type:: E-books
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Size:: 7.6 MB
Uploaded On:: Feb. 21, 2022, 12:36 p.m.
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Textbook in PDF format This book brings Data Envelopment Analysis (DEA) based techniques and big data together to explore the novel uses and potentials of DEA under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework. Data Envelopment Analysis and Big Data: A Systematic Literature Review with Bibliometric Analysis Acceleration of Large-Scale DEA Computations Using Random Forest Classification The Estimation of Productive Efficiency Through Machine Learning Techniques: Efficiency Analysis Trees Hybrid Data Science and Reinforcement Learning in Data Envelopment Analysis Aggregation of Outputs and Inputs for DEA Analysis of Hospital Efficiency: Economics, Operations Research and Data Science Perspectives Parallel Processing and Large-Scale Datasets in Data Envelopment Analysis Network DEA and Big Data with an Application to the Coronavirus Pandemic Hierarchical Data Envelopment Analysis for Classification of High-Dimensional Data Dominance Network Analysis: Hybridizing Dea and Complex Networks for Data Analytics Value Extracting in Relative Performance Appraisal with Network DEA: An Application to U.S. Equity Mutual Funds Measuring Chinese Bank Performance with Undesirable Outputs: A Slack-Based Two-Stage Network DEA Approach Using Network DEA and Grey Prediction Model for Big Data Analysis: An Application in the Global Airline Efficiency

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Zhu J. Data-Enabled Analytics. DEA for Big Data 2021.pdf 7.6 MB

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zhu j data enabled analytics dea big data 2021

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