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The Power of Computational Intelligence Case study: iTRAQ

The Power of Computational Intelligence Case study: iTRAQ. Benjamin N. Passow , David Elizondo, Eric Goodyer and Simon Witheridge De Montfort University Leicester, UK. Benjamin N. Passow [benpassow@ieee.org] De Montfort University Leicester, UK. Decision Making. Computational.

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The Power of Computational Intelligence Case study: iTRAQ

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  1. The Power of Computational IntelligenceCase study: iTRAQ Benjamin N. Passow, David Elizondo,Eric Goodyerand Simon Witheridge De Montfort University Leicester, UK Benjamin N. Passow [benpassow@ieee.org]De Montfort University Leicester, UK

  2. Decision Making Computational Intelligence Efficient Searchand Optimisation Fuzzy Logic Computing with words Evolutionary Computation Artificial Immune Systems Learning Artificial Neural Networks Swarm Intelligence Adaptation

  3. &

  4. Overview Traffic data(in-situ) Optimised Traffic Management Strategy GNSS Floating Car Data Computational Intelligence Module Chrono. data feedback for iterative optimisation process Met. data Air quality model Traffic Simulator In-situAir Quality City Plan& O/D MACC modelled AQ EO AQ data (OMI,GOME-2)

  5. Actual Forecast Results Traffic Flow (veh/hr) Air Quality NO2 (ugm-3)

  6. Results Flow % Delay % Hour of day Hour of day • Strong increase in traffic flow • Substantial decrease in delay • While simultaneously managing air quality

  7. Conclusions Initial Study Conclusions • iTRAQ is operationally feasible • The system demonstrated: • increase in traffic flow 89% of the time (avg +0.6%) • reduction of delay every time (avg -3%) • (using only two neighbouring junctions) • iTRAQ provides additional information: • forecasts • suggest enhanced strategies • The iTRAQ system can • inform and support operator decision-making • have autonomous control over both objectives (when fully tested)

  8. Initial Study Conclusions What can Computational Intelligence do for you?

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