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Horse Racing Simulation System Presented By Ting Hin Chau Supervised By Professor Michael R. Lyu

Horse Racing Simulation System Presented By Ting Hin Chau Supervised By Professor Michael R. Lyu April 2004. Agenda. Objectives of Project Background of Horse Racing Major Business Functions of Objects System Design Simulation Algorithm Conclusion Q & A.

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Horse Racing Simulation System Presented By Ting Hin Chau Supervised By Professor Michael R. Lyu

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  1. Horse Racing Simulation System Presented By Ting Hin Chau Supervised By Professor Michael R. Lyu April 2004

  2. Agenda • Objectives of Project • Background of Horse Racing • Major Business Functions of Objects • System Design • Simulation Algorithm • Conclusion • Q & A

  3. Objectives / Background / Business Functions / System Design / Simulation Algorithm Objectives • To demonstrate CORBA implementation • To demonstrate horse racing simulation

  4. Objectives / Background / Business Functions / System Design / Simulation Algorithm Background of Horse Racing • Jockey Club • Stable • Gambler

  5. Objectives / Background / Business Functions / System Design / Simulation Algorithm Background of Horse Racing Inefficient Procedures • Race Registration: Paper Work • Betting: Off-course betting branches

  6. Objectives / Background / Business Functions / System Design / Simulation Algorithm Background of Horse Racing Difficult Result Prediction • Personal Judgement

  7. Objectives / Background / Business Functions / System Design / Simulation Algorithm Business Functions Jockey Club • Formulating Horse Racing Schedule • Schedule Query by Stable • Processing Horse Registration for a Race by Stable

  8. Objectives / Background / Business Functions / System Design / Simulation Algorithm Business Functions Jockey Club • Race Query by Gamblers • Accepting Bets from Gamblers • Calculating Odds (Appendix 1) • Running Races • Dividend Payout

  9. Objectives / Background / Business Functions / System Design / Simulation Algorithm Business Functions Stable • Horse Query by Gamblers • Horse Registration for a Race

  10. Objectives / Background / Business Functions / System Design / Simulation Algorithm Business Functions Gambler • Depositing Money to Betting Account • Placing Bets

  11. Database (Oracle 8i) Server Object 1 Server Object N Object Request Broker (VisiBroker for Java 4.0) Client Object 1 Client Object N Java Applet Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design • Interaction

  12. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design Object Request Broker • VisiBroker for Java 4.0 • Service Lookup • Object Instantiation • Connection Setup between Client and Server Objects

  13. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design Object Request Broker

  14. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design Server Objects • Interfaces defined in CORBA/IDL interface Buyer { attribute unsigned longBuyerID; attribute stringBuyerPassword; attribute stringBuyerName; attribute floatBalance; attribute stringAccountNumber; exception NotEnoughMoneyInAccount { }; void deposit(in float amount); void withdraw(in unsigned long amount) raises(NotEnoughMoneyInAccount); void edit(in string buyerName, in string buyerPassword, in string accountNumber); };

  15. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design CORBA/IDL to Java Mapping

  16. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design idl2java • Interface file • Helper file • Holder file • Stub file • POA file

  17. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design Server Objects • Buyer • BuyerProcessor • Stable • StableProcessor • Race

  18. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design Client GUI • RaceAdminClient • StableClient • BuyerClient

  19. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design Client GUI • RaceAdminClient

  20. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design Client GUI • StableClient

  21. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design Client GUI • BuyerClient

  22. Objectives / Background / Business Functions / System Design / Simulation Algorithm System Design Database Server • Oracle 8i • Persistent storage of data • Maintaining data integrity • E-R diagram (Appendix 2)

  23. Objectives / Background / Business Functions / System Design / Simulation Algorithm Simulation Algorithm Monte Carlo Simulation • Simulation with a built-in random process • Different possible outcomes

  24. Objectives / Background / Business Functions / System Design / Simulation Algorithm Simulation Algorithm Steps of Simulation (Appendix 3) 1. Data Input • Gather data on historical ranks of a horse • Transform these ranks to a value R/N, which is rank/number of horses in the race

  25. Objectives / Background / Business Functions / System Design / Simulation Algorithm Simulation Algorithm Steps of Simulation 2. Distribution Construction • Form frequency distribution • Form probability distribution • Form cumulative probability distribution

  26. Objectives / Background / Business Functions / System Design / Simulation Algorithm Simulation Algorithm Steps of Simulation

  27. Objectives / Background / Business Functions / System Design / Simulation Algorithm Simulation Algorithm Steps of Simulation 3. Draw a sample from distribution • Generate a random number N from 0 to 1 • N refers to P(X <= x), where X is R/N

  28. Objectives / Background / Business Functions / System Design / Simulation Algorithm Simulation Algorithm Steps of Simulation

  29. Objectives / Background / Business Functions / System Design / Simulation Algorithm Simulation Algorithm Steps of Simulation 4. Compare R/N across horses • Sort the R/N values of the horses in a race • A horse with a smaller R/N beats out a horse with a higher R/N

  30. Objectives / Background / Business Functions / System Design / Simulation Algorithm Simulation Algorithm Assumptions of Simulation • Independent distribution of R/N • Factors including location of racecourse, lane, and jockey are insignificant • Data from the 10 most recent races are used

  31. Objectives / Background / Business Functions / System Design / Simulation Algorithm Conclusion CORBA • Language independent • Different platforms • ORB expensive

  32. Objectives / Background / Business Functions / System Design / Simulation Algorithm Conclusion Simulation • Mimics the “random” factor in horse racing • Choice of size of distribution is hard to determine • Error of prediction can be estimated

  33. Objectives / Background / Business Functions / System Design / Simulation Algorithm Appendix 1 Calculation of Odds 1. Win Odds • dw = bi / bw 2. Place Odds • dw1 = (bi - bw1 - bw2 - bw3) /( 3 * bw1) + 1

  34. BetAccountBal GamblerName Status AccountNum Status Password SID Password GID Stable_t Gambler_t Gambler-bet BetType Horse_t Race_t Bet_t BetAmount Owns Race-bet TxnStatus Birthday HID RaceDate Weight Status RaceEventNumber HLane Joins HorseRank Objectives / Background / Business Functions / System Design / Simulation Algorithm Appendix 2

  35. Objectives / Background / Business Functions / System Design / Simulation Algorithm Appendix 3 Simulation Calculation

  36. Objectives / Background / Business Functions / System Design / Simulation Algorithm Appendix 3 Simulation Calculation

  37. Objectives / Background / Business Functions / System Design / Simulation Algorithm Appendix 3 Simulation Calculation

  38. Objectives / Background / Business Functions / System Design / Simulation Algorithm Appendix 3 Simulation Calculation • Two points on the cumulative distribution (x1, y1) and (x2, y2), for instance, for horse 1, they correspond to (0.25, 0.5) and (0.25, 0.6), will be used to calculate the final score of a horse by linear equation , based on the random number generated.

  39. Objectives / Background / Business Functions / System Design / Simulation Algorithm Appendix 3 Simulation Calculation • For horse 1, point 1 (x1, y1) is (0.4, 0.2) and point 2 (x2, y2) is (0.5, 03) • R/N of horse 1 = (rand1-y1)*((x2-x1)/(y2-y1)) + x1 = (0.5379783655654367 – 0.2)* (0.25 – 0.25)/(0.6-0.5) + 0.25 = 0.25

  40. Objectives / Background / Business Functions / System Design / Simulation Algorithm Appendix 3 Simulation Calculation • For horse 2, point 1 (x1, y1) is (0.4, 0.2) and point 2 (x2, y2) is (0.5, 0.3). • R/N of horse 2 = (rand2-y1)*((x2-x1)/(y2-y1)) + x1 = (0.21096296234313094 – 0.2)* (0.5 – 0.4)/(0.3-0.2) + 0.4 = 0.410962962

  41. Objectives / Background / Business Functions / System Design / Simulation Algorithm Appendix 3 Simulation Calculation • For horse 3, point 1 (x1, y1) is (0, 0) and point 2 (x2, y2) is (0.125, 0.1). • R/N of horse 3 = (rand2-y1)*((x2-x1)/(y2-y1)) + x1 = (0.02229991816731558 – 0)* (0.125 – 0)/(0.1-0) + 0 = 0.027874898

  42. Objectives / Background / Business Functions / System Design / Simulation Algorithm Appendix 3 Simulation Calculation • For horse 4, point 1 (x1, y1) is (0.5355, 0.4) and point 2 (x2, y2) is (0.545455, 0.5). • R/N of horse 3 = (rand2-y1)*((x2-x1)/(y2-y1)) + x1 = (0.4920612612595172 – 0.4) * (0.545455 – 0.5355)/(0.5-0.4) + 0.5355 = 0.544664699

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