𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Urban traffic flow prediction using a fuzzy-neural approach

✍ Scribed by Hongbin Yin; S.C. Wong; Jianmin Xu; C.K. Wong


Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
273 KB
Volume
10
Category
Article
ISSN
0968-090X

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


A multivariate state space approach for
✍ Anthony Stathopoulos; Matthew G. Karlaftis πŸ“‚ Article πŸ“… 2003 πŸ› Elsevier Science 🌐 English βš– 195 KB

Urban traffic congestion is one of the most severe problems of everyday life in Metropolitan areas. In an effort to deal with this problem, intelligent transportation systems (ITS) technologies have concentrated in recent years on dealing with urban congestion. One of the most critical aspects of IT

A predictive model for well loss using f
✍ AbdΓΌsselam Altunkaynak πŸ“‚ Article πŸ“… 2010 πŸ› John Wiley and Sons 🌐 English βš– 125 KB πŸ‘ 1 views

## Abstract Simple methods for calculating well losses are important for well design and optimization of groundwater source operation. Well losses arise from both laminar flow within the aquifer and turbulent flow within the well, and are often ignored in theoretical aquifer test analysis. The Jaco

Estimation of time-varying origin-destin
✍ Yang Hai; T. Akiyama; T. Sasaki πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 930 KB

A dynamic model based on the error back-propagation learning principle in neural network theory ie proposed for estimating origin-destination flows from the road entering and exiting counts in a transportation network. The origin-destination flows in each short time interval are estimated through mi