Neural network model based on travel planning for travel time prediction

Neural Network Based Traffic Flow Model for Urban Arterial Travel Time Prediction

Many research efforts on travel time prediction focus predominantly on freeways, while limited work has been done on urban arterials. Among the latter, data driven models, particularly neural networks, have demonstrated promising performance. In most cases, the inputs from spatially separated sources (volumes/speeds collected by loop detectors from different locations) are combined in one singl...

Real-time Travel Time Prediction on Urban Arterial Network

Travel time is one of the most desired operational variables serving as a key measure of effectiveness for evaluating the system performance of freeways and urban arterials. With accurate travel time information, decision makers, road users, and traffic engineers can make informed decisions. However, retrieving network-level travel time information has several challenges, such as traffic data c...

Nanofluid Thermal Conductivity Prediction Model Based on Artificial Neural Network

Heat transfer fluids have inherently low thermal conductivity that greatly limits the heat exchange efficiency. While the effectiveness of extending surfaces and redesigning heat exchange equipments to increase the heat transfer rate has reached a limit, many research activities have been carried out attempting to improve the thermal transport properties of the fluids by adding more thermally c...

Prediction of Variable Travel Time Components in Distribution Planning

Urban Road Travel Time Prediction based on ELM

The Travel Time Prediction (TTP) is an important element in the study of the advanced transportation guidance system and control system. In this paper, an advanced method with Extreme Learning Machine algorithm(ELM) has been discussed by analyzing the various travel time prediction method. The feasibility and advantages of Extreme Learning Machine in travel time prediction has been studied, and...