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Routing in Internet of Vehicles: A Review
This work aims to provide a review of the routing protocols in the Internet of Vehicles (IoV) from routing algorithms to their evaluation approaches. We provide five different taxonomies of routing
Long-Term Traffic Speed Prediction Based on Multiscale Spatio-Temporal Feature Learning Network
TLDR
The presented results demonstrate that the proposed multiscale spatio-temporal feature learning network (MSTFLN) approach outperforms the state-of-the-art work and it can effectively predict the long-term speed information.
Dendritic Neuron Model With Effective Learning Algorithms for Classification, Approximation, and Prediction
TLDR
Six learning algorithms including biogeography-based optimization, particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, and population-based incremental learning are used to train a new dendritic neuron model (DNM) and are suggested to make DNM more powerful in solving classification, approximation, and prediction problems.
Chaotic Local Search-Based Differential Evolution Algorithms for Optimization
TLDR
A novel JADE variant is presented by incorporating chaotic local search (CLS) mechanisms into JADE to alleviate this problem and has a superior performance in comparison with JADE and some other state-of-the-art optimization algorithms.
Automatic Composition of Semantic Web Services Based on Fuzzy Predicate Petri Nets
TLDR
This paper presents an automatic Web service composition method that deals with both input/output compatibility and behavioral constraint compatibility of fuzzy semantic services.
Traffic sign detection based on cascaded convolutional neural networks
TLDR
A new approach to detect traffic signs based on cascaded convolutional neural networks (CNNs), where the local binary pattern (LBP) feature detector and the AdaBoost classifier are combined to extract regions of interest (ROI) for coarse selection.
Vehicle license plate recognition using visual attention model and deep learning
TLDR
Two classifiers, which combine the advantages of convolutional neural network-based feature learning and support vector machine for multichannel processing, are designed to recognize Chinese characters, numbers, and alphabet letters, respectively.
Incorporation of Solvent Effect into Multi-Objective Evolutionary Algorithm for Improved Protein Structure Prediction
TLDR
The results suggest the necessity to incorporate the effect of solvent into a multi-objective evolutionary algorithm to improve protein structure prediction in terms of accuracy and efficiency.
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