[AISWorld] Most Cited and Read (2022) Articles - Connection Science, Taylor & Francis

[Editorial Manager]

** Most Cited Articles **



Developmental robotics: a survey

MAX LUNGARELLA, GIORGIO METTA, ROLF PFEIFER & GIULIO SANDINI



Error Correlation and Error Reduction in Ensemble Classifiers

KAGAN TUMER & JOYDEEP GHOSH



On Combining Artificial Neural Nets

AMANDA J. C SHARKEY



Catastrophic Forgetting, Rehearsal and Pseudorehearsal

ANTHONY ROBINS



Using Relevance to Reduce Network Size Automatically

MICHAEL C. MOZER & PAUL SMOLENSKY



How to do the Right Thing

PATTIE MAES



Dynamic Node Creation in Backpropagation Networks

TIMUR ASH



Actively Searching for an Effective Neural Network Ensemble

DAVID W OPITZ & JUDE W SHAVLIK





** Most Read Articles (2022) **



KG4Py: A toolkit for generating Python knowledge graph and code semantic search

Lu Liang et al.



Security analysis of smart contract based rating and review systems: the perilous state of blockchain-based recommendation practices

Jitendra Singh Yadav et al.



Intelligent garbage classification system based on improve MobileNetV3-Large

Yi Zhao et al.



Blockchain application in P2P energy markets: social and legal aspects

Cruz E. Borges et al.



Blockchain-based anonymous authentication for traffic reporting in VANETs

Li Zhang et al.



A Hybrid parallel deep learning model for efficient intrusion detection based on metric learning

Shaokang Cai et al.



A pricing model for subscriptions in data transactions

Bo Li et al.



A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy

R. Sudharsan et al.



A feature selection method with feature ranking using genetic programming

Guopeng Liu et al.



Multi-stream part-fused graph convolutional networks for skeleton-based gait recognition

Likai Wang et al.





Connection Science, Taylor & Francis

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