Integrative, Rapid, Data Analysis
Methods that bring together data from many sources and turn it into timely, usable insight.
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Electric Energy Consumption Prediction by Deep Learning with State Explainable Autoencoder
JY Kim, SB Cho. Cited by 147
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A Data-Driven Predictive Prognostic Model for Lithium-ion Batteries based on a Deep Learning Algorithm
P Khumprom, N Yodo. Cited by 296
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Daily Stress and Mood Recognition System Using Deep Learning and Fuzzy Clustering for Promoting Better Well-Being
W Lawanot, M Inoue, T Yokemura, P Mongkolnam, C Nukoolkit. Cited by 27
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Topic-Aware Neural Keyphrase Generation for Social Media Language
Y Wang, J Li, HP Chan, I King, MRT Lyu, S Shi. Cited by 81
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Data-driven Prognostic Model of Li-ion Battery with Deep Learning Algorithm
P Khumprom, N Yodo. Cited by 33
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Enhancing Predictive Power of Cluster-Boosted Regression With Text-Based Indexing
W Kongburan, M Chignell, N Charoenkitkarn, JH Chan. Cited by 5
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Big Data in Smart-Cities: Current Research and Challenges
D Pal, T Triyason, P Padungweang. Cited by 24
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Data-Driven Adaptation in Memetic Algorithms
A Gupta, YS Ong. Cited by 2
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Memetic Computation: The Mainspring of Knowledge Transfer in a Data-Driven Optimization Era
A Gupta, YS Ong. Cited by 42
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A review and empirical analysis of neural networks based exchange rate prediction
TN Pandey, AK Jagadev, S Dehuri, SB Cho. Cited by 14
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RelDenClu: A Relative Density based Biclustering Method for identifying non-linear feature relations
N Jain, S Ghosh, CA Murthy
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Proprties of biclustering algorithms and a novel biclustering technique based on relative density.
N Jain, S Ghosh, AK Ghosh, CA Murthy. Cited by 1