Path selection method of intelligent vehicle based on fuzzy big data game

2018 ◽  
Vol 14 (1) ◽  
pp. 62
Author(s):  
Zhiwu Huang
Keyword(s):  
Big Data ◽  
Selection Method ◽  
Path Selection ◽  
Intelligent Vehicle

scholarly journals BELIEF: A distance-based redundancy-proof feature selection method for Big Data

2021 ◽  
Vol 558 ◽  
pp. 124-139
Author(s):  
D. López ◽  
S. Ramírez-Gallego ◽  
S. García ◽  
N. Xiong ◽  
F. Herrera
Keyword(s):  
Feature Selection ◽  
Big Data ◽  
Feature Selection Method ◽  
Selection Method

scholarly journals Routing Optimization Algorithms Based on Node Compression in Big Data Environment

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Lifeng Yang ◽  
Liangming Chen ◽  
Ningwei Wang ◽  
Zhifang Liao
Keyword(s):  
Big Data ◽  
Shortest Path ◽  
Optimization Algorithms ◽  
Real Life ◽  
Large Data ◽  
Path Selection ◽  
Shortest Path Problem ◽  
Limited Time ◽  
Starting Point ◽  
Data Environment

Shortest path problem has been a classic issue. Even more so difficulties remain involving large data environment. Current research on shortest path problem mainly focuses on seeking the shortest path from a starting point to the destination, with both vertices already given; but the researches of shortest path on a limited time and limited nodes passing through are few, yet such problem could not be more common in real life. In this paper we propose several time-dependent optimization algorithms for this problem. In regard to traditional backtracking and different node compression methods, we first propose an improved backtracking algorithm for one condition in big data environment and three types of optimization algorithms based on node compression involving large data, in order to realize the path selection from the starting point through a given set of nodes to reach the end within a limited time. Consequently, problems involving different data volume and complexity of network structure can be solved with the appropriate algorithm adopted.

Candidate Path Selection Method for TCP Performance Improvement in Fixed Robust Routing

2016 ◽  
Vol 5 (6) ◽  
pp. 445-453
Author(s):  
Yukinobu Fukushima ◽  
Takashi Matsumura ◽  
Kazutaka Urushibara ◽  
Tokumi Yokohira
Keyword(s):  
Performance Improvement ◽  
Selection Method ◽  
Path Selection ◽  
Tcp Performance ◽  
Robust Routing ◽  
Candidate Path
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