PPT-Defining probability-based rail station catchments for demand modelling.

Defining probabilitybased rail station catchments for demand modelling Marcus Young PhD student Transportation Research Group 7 January 2016 2 Outline Research background Developing a station choice model. PAUL STATION PEARLARTS DISTRICT STATION CITYPLACE UPTOWN STATION MOCKINGBIRD STATION WHITE ROCK STATION LAKE HIGHLANDS STATION LBJSKILLMAN STATION FORESTJUPITER STATION DOWNTOWN GARLAND STATION DOWNTOWN ROWLETT STATION 327A 329A 332A 335A 337A 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 9 10 11 12 13 14 15 16 17 18 19 20 0 1 2 3 4 5 Number in station 1Number in station 2Do not jockeyJockey 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 Number in stat Modelling for Engineering Processes. Peter Hale UWE. University of the West of England, Bristol. Abstract. Problem. -. Enable translation of human problems/representation to computer models and code.. Predictability of Change. Alberto . Montanari. (1). and . Guenter. . Bloeschl. (2). (1) . University of Bologna, . alberto.montanari@unibo.it. (2) . Vienna University of Technology, . bloeschl@hydro.tuwien.ac.at. 3.5. Demonstrate understanding of how technological modelling supports technological development. Aims for this session. To share key messages for technological modelling level 3. T. o develop understanding of how . Andrew Ardley. Transportation Manager (Policy). Devon County Council. Contents. Devon Metro – setting the scene. Strategy overview. Exeter as a network hub. New stations. Station improvements and access to them. Lina Stein. Supervisors: Ross Woods, Francesca . Pianosi. (University of Bristol). High uncertainty of flood estimates in ungauged catchments. www.wisecdt.org. Fig. . 2. : . Saharia. et al., 2017. Fig. 3: Beck et al., 2017. Lecturer in Quantitative Social Sciences. A basic linear regression model. e. Y. X. Y = B0 B1*X e. What’s the problem?. Assume that the residuals (e) are independent from each other.. Ie. that the model has accounted for everything systematic . Learning objectives. Factors . that . determine rail capacity . Line . capacity (number of trains). Person . capacity (number of passengers). Design . capacity. Generalized capacity estimation method. Tonight's agenda . Our focus is always somewhere else. A Secure Development Lifecycle?. Threat Modelling. Taking it in your STRIDE. How . to get everyone involved. How to win at Poker. Q & A. Fin. First Steps in research. State your topic as a question.. Topics. Bipolar disorder. Hip hop music. Drugs. Border region. Terrorism. Censorship. Low Riders. Death Penalty. Change this to a question?. Add one of the following. . Where do they meet? Where do they “meet”? Train #1 leaves station A and accelerates east at 0.5 m/s/s. At the same instant #1 leaves station A, train #2 leaves station B, which is 1.0 km east of A, and accelerates west at 0.25m/s/s. Relative to station A, where would the two trains pass? Assume they were on parallel tracks. DEMAND CURVE . DEMAND. Ang. . konseptong. . ito. ay . nakatuon. . sa. . gawi. . ng. . mamimili. . sa. . pamilihan. .. Ang. demand ay . tumutukoy. . sa. . dami. . ng. . produkto. CATCHMENT TRANS-FORMED DISTINCT-IVENESS CATCHMENT RICHNESS FLOW INTEGRITY COVER BD REMAINING WQ BD REMAINING EXOTIC FISH THREATENED FISH BLUE DUCK THREATENED BIRDS FLOOD FOREST THREATENED PLANTS TOTAL