W
Wei Wei
Researcher at Qilu University of Technology
Publications - 173
Citations - 4535
Wei Wei is an academic researcher from Qilu University of Technology. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 32, co-authored 124 publications receiving 3095 citations. Previous affiliations of Wei Wei include Chinese Ministry of Education & Xi'an University of Science and Technology.
Papers
More filters
Journal ArticleDOI
Imperfect Information Dynamic Stackelberg Game Based Resource Allocation Using Hidden Markov for Cloud Computing
TL;DR: A cloud resource allocation model based on an imperfect information Stackelberg game (CSAM-IISG) using a hidden Markov model (HMM) in a cloud computing environment was shown to increase the profits of service providers and infrastructure suppliers simultaneously.
Journal ArticleDOI
Intelligent Fault Diagnosis of the High-Speed Train With Big Data Based on Deep Neural Networks
TL;DR: The deep neural network is adopted to recognize faults in bogies and provides a new paradigm for fault diagnosis of the high-speed train with big data and plays an important role in this field.
Journal ArticleDOI
Gradient-driven parking navigation using a continuous information potential field based on wireless sensor network
TL;DR: The theoretical analysis proves the convergence of a proposed algorithm and efficient convergence during the first and second steps of the algorithm to effectively prevent parking navigation from a gridlock situation and demonstrates that the proposed algorithm performs more efficiently than existing algorithms.
Journal ArticleDOI
A Self-Assessment Stereo Capture Model Applicable to the Internet of Things.
TL;DR: The experimental results show that the proposed evaluation criteria can effectively predict the visual perception of stereo capture quality for long-distance shooting.
Journal ArticleDOI
Detecting Parkinson's Disease with Sustained Phonation and Speech Signals using Machine Learning Techniques
Jefferson S. Almeida,Pedro Pedrosa Rebouças Filho,Tiago Carneiro,Wei Wei,Robertas Damasevicius,Rytis Maskeliūnas,Victor Hugo C. de Albuquerque +6 more
TL;DR: It is shown that the task of phonation was more efficient than speech tasks in the detection of disease and compared with other approaches that use the same data set.