@article{Hodge:2014:10.1007/s00521-014-1646-5, author = {Hodge, VJ and Krishnan, R and Austin, J and Polak, J and Jackson, T}, doi = {10.1007/s00521-014-1646-5}, journal = {NEURAL COMPUTING & APPLICATIONS}, pages = {1639--1655}, title = {Short-term prediction of traffic flow using a binary neural network}, url = {http://dx.doi.org/10.1007/s00521-014-1646-5}, volume = {25}, year = {2014} }
TY - JOUR AU - Hodge,VJ AU - Krishnan,R AU - Austin,J AU - Polak,J AU - Jackson,T DO - 10.1007/s00521-014-1646-5 EP - 1655 PY - 2014/// SN - 0941-0643 SP - 1639 TI - Short-term prediction of traffic flow using a binary neural network T2 - NEURAL COMPUTING & APPLICATIONS UR - http://dx.doi.org/10.1007/s00521-014-1646-5 UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000344775800010&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb VL - 25 ER -
Transition to Zero Pollution is a flagship initiative of the Imperial's Academic Strategy, with a vision to realise a sustainable zero pollution future. The initiative brings researchers from different disciplines together to take a systems approach to tackling pollution in all its forms.