1 research outputs found
No show passengers prediction system based on computational inteligence techniques
Π’Π΅ΠΌΠ° ΠΎΠ²ΠΎΠ³ ΡΠ°Π΄Π° ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ° ΠΏΡΠ΅Π΄Π»ΠΎΠ³ ΡΠΈΡΡΠ΅ΠΌΠ° Π·Π° ΠΏΡΠ΅Π΄Π²ΠΈΡΠ°ΡΠ΅ ΠΏΡΡΠ½ΠΈΠΊΠ° ΠΊΠΎΡΠΈ
ΡΠ΅ Π½Π΅ΡΠ΅ ΠΏΠΎΡΠ°Π²ΠΈΡΠΈ Π½Π° Π»Π΅ΡΡ (βno-showβ), ΠΊΠΎΡΠΈ ΡΠ΅ Π·Π°ΡΠ½ΠΈΠ²Π° Π½Π° ΡΠ΅Ρ
Π½ΠΈΠΊΠ°ΠΌΠ° ΡΠ°ΡΡΠ½Π°ΡΡΠΊΠ΅
ΠΈΠ½ΡΠ΅Π»ΠΈΠ³Π΅Π½ΡΠΈΡΠ΅. ΠΡΠ΅Π΄Π²ΠΈΡΠ°ΡΠ΅ Π±ΡΠΎΡΠ° βno-showβ ΠΏΡΡΠ½ΠΈΠΊΠ° ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ° ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ°Π½ ΠΈ
ΡΡΠΊΠΎ ΡΠΎΡΠΌΡΠ»ΠΈΡΠ°Π½ ΠΏΡΠΎΠ±Π»Π΅ΠΌ ΠΊΠΎΡΠΈ ΡΠ΅ Π²Π΅Ρ Π΄ΡΠΆΠΈ Π½ΠΈΠ· Π³ΠΎΠ΄ΠΈΠ½Π° Π²Π΅ΠΎΠΌΠ° Π°ΠΊΡΡΠ΅Π»Π°Π½ Ρ Π°Π²ΠΈΠΎ
ΠΈΠ½Π΄ΡΡΡΡΠΈΡΠΈ ΠΊΠ°ΠΊΠΎ ΡΠ° ΡΠ΅ΠΎΡΠΈΡΡΠΊΠΎΠ³, ΡΠ°ΠΊΠΎ ΠΈ ΡΠ° ΠΏΡΠ°ΠΊΡΠΈΡΠ½ΠΎΠ³ Π°ΡΠΏΠ΅ΠΊΡΠ°. ΠΠ° ΠΎΡΠ½ΠΎΠ²Ρ
ΠΎΡΠ΅ΠΊΠΈΠ²Π°Π½ΠΎΠ³ Π±ΡΠΎΡΠ° βno showβ ΠΏΡΡΠ½ΠΈΠΊΠ°, ΠΊΠ°ΠΎ ΠΈ Π΄ΡΡΠ³ΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠ°, Π°Π²ΠΈΠΎ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΡΠ΅ Π΄ΠΎΠ½ΠΎΡΠ΅
ΠΎΠ΄Π»ΡΠΊΡ ΠΎ Π΄ΠΎΠ΄Π°ΡΠ½ΠΎΠΌ Π±ΡΠΎΡΡ ΠΌΠ΅ΡΡΠ° ΠΊΠΎΡΠΈ ΡΠ΅ Π±ΠΈΡΠΈ Π΄ΠΎΡΡΡΠΏΠ°Π½ ΠΊΡΠΎΠ· ΡΠ΅Π·Π΅ΡΠ²Π°ΡΠΈΠΎΠ½ΠΈ ΡΠΈΡΡΠ΅ΠΌ.
ΠΠ° ΠΎΠ²Π°Ρ Π½Π°ΡΠΈΠ½, Π°Π²ΠΈΠΎ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΡΠ΅ ΠΌΠΎΠ³Ρ ΠΎΡΡΠ²Π°ΡΠΈΡΠΈ Π΄ΠΎΠ΄Π°ΡΠ°Π½ ΠΏΡΠΎΡΠΈΡ, ΠΏΠΎΠ³ΠΎΡΠΎΠ²Ρ ΠΊΠ°Π΄Π° ΡΠ΅
ΡΠ°Π΄ΠΈ ΠΎ Π»Π΅ΡΠΎΠ²ΠΈΠΌΠ° ΠΊΠΎΡΠΈ ΡΡ ΠΏΠΎΠΏΡΡΠ΅Π½ΠΈ Ρ ΠΏΠΎΡΠΏΡΠ½ΠΎΡΡΠΈ.
ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΈ ΡΠΈΡΡΠ΅ΠΌ Π·Π° ΠΏΡΠ΅Π΄Π²ΠΈΡΠ°ΡΠ΅ βno-showβ ΠΏΡΡΠ½ΠΈΠΊΠ° ΡΠ΅ ΡΠ°ΡΡΠΎΡΠΈ ΠΎΠ΄ Π΄Π²Π΅
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ΅. ΠΡΠ²Π° ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ° ΡΠ΅ ΠΎΠ΄Π½ΠΎΡΠΈ Π½Π° ΠΈΠ·Π±ΠΎΡ Π½Π°ΡΠΏΡΠ΅ΡΠΈΠ·Π½ΠΈΡΠ΅Π³ ΠΌΠΎΠ΄Π΅Π»Π° Π·Π°
ΠΏΡΠ΅Π΄Π²ΠΈΡΠ°ΡΠ΅, Π° Π΄ΡΡΠ³Π° Π½Π° ΠΏΡΠΈΠΌΠ΅Π½Ρ ΠΈ Π²Π°Π»ΠΈΠ΄Π°ΡΠΈΡΡ ΡΠΈΡΡΠ΅ΠΌΠ°. ΠΠΎΠ΄Π΅Π» Π·Π° ΠΏΡΠ΅Π΄Π²ΠΈΡΠ°ΡΠ΅ ΡΠ΅
ΡΠ°ΡΡΠΎΡΠΈ ΠΈΠ· Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° ΠΊΠΎΡΠΈ ΡΠ΅ Π·Π°ΡΠ½ΠΈΠ²Π° Π½Π° ΡΠ΅Ρ
Π½ΠΈΡΠΈ Π·Π°ΠΊΡΡΡΠΈΠ²Π°ΡΠ° Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΡΠ»ΡΡΠ°ΡΠ° ΠΈ
ΠΈΠ½ΡΠ΅ΡΠΏΠΎΠ»Π°ΡΠΈΠ²Π½Π΅ ΠΡΠ»ΠΎΠ²Π΅ Π°Π»Π³Π΅Π±ΡΠ΅. ΠΠ°ΡΠ΅, ΠΌΠΎΠ΄Π΅Π» ΠΊΠΎΠΌΠ±ΠΈΠ½ΡΡΠ΅ ΠΏΡΠ΅Π΄Π»ΠΎΠ³ ΠΊΠΎΡΠΈ ΡΠ΅ Π³Π΅Π½Π΅ΡΠΈΡΠ°Π½
ΠΎΠ΄ ΡΡΡΠ°Π½Π΅ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° ΠΈ ΠΏΡΠ΅Π΄Π»ΠΎΠ³ ΠΊΠΎΡΠΈ ΠΏΡΠ΅ΠΏΠΎΡΡΡΡΡΠ΅ Π΅ΠΊΡΠΏΠ΅ΡΡ. ΠΠ° ΠΎΠ²Π°Ρ Π½Π°ΡΠΈΠ½
ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΈ ΡΠΈΡΡΠ΅ΠΌ ΠΎΠ±ΡΠ΅Π΄ΠΈΡΡΡΠ΅ ΠΈ ΡΠ·ΠΈΠΌΠ° Ρ ΠΎΠ±Π·ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½Ρ ΠΈ ΡΡΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½Ρ
Π΄ΠΈΠΌΠ΅Π½Π·ΠΈΡΡ ΠΏΡΠΈΠ»ΠΈΠΊΠΎΠΌ ΠΏΡΠ΅Π΄Π²ΠΈΡΠ°ΡΠ°. Π‘Π»ΠΈΡΠ½ΠΎΡΡ ΠΈΠ·ΠΌΠ΅ΡΡ Π»Π΅ΡΠΎΠ²Π° ΡΠ΅ ΠΈΠ·ΡΠ°ΡΡΠ½Π°Π²Π°
ΠΊΠΎΡΠΈΡΡΠ΅ΡΠ΅ΠΌ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π°Π»Π½ΠΈΡ
ΠΌΠ΅ΡΠ° (EΡΠΊΠ»ΠΈΠ΄ΡΠΊΠ° ΠΈ MΠ΅Π½Ρ
Π΅ΡΠ½) ΠΈ ΠΠΠ ΠΌΠ΅ΡΠ΅
ΡΠ»ΠΈΡΠ½ΠΎΡΡΠΈ. Π’Π°ΠΊΠΎΡΠ΅, ΠΠΠ ΠΏΡΠΈΡΡΡΠΏ ΡΠΏΠΎΡΠΏΡΡΡΡΠ΅ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π°Π»Π½ΠΈ Π°Π»Π³ΠΎΡΠΈΡΠ°ΠΌ ΡΠ΅Ρ
Π½ΠΈΠΊΠ΅
Π·Π°ΠΊΡΡΡΠΈΠ²Π°ΡΠ° Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΡΠ»ΡΡΠ°ΡΠ° ΠΊΡΠΎΠ· ΠΎΠΌΠΎΠ³ΡΡΠ°Π²Π°ΡΠ΅ Π»ΠΎΠ³ΠΈΡΠΊΠ΅ Π°Π³ΡΠ΅Π³Π°ΡΠΈΡΠ΅ Π²ΡΠ΅Π΄Π½ΠΎΡΡΠΈ,
ΠΎΠ΄Π½ΠΎΡΠ½ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΎΠ²Π°ΡΠ΅ΠΌ ΠΏΠΎΡΡΠΎΡΠ΅ΡΠΈΡ
Π½Π΅Π»ΠΈΠ½Π΅Π°ΡΠ½ΠΈΡ
Π·Π°Π²ΠΈΡΠ½ΠΎΡΡΠΈ ΠΈΠ·ΠΌΠ΅ΡΡ ΠΏΠΎΠ΄Π°ΡΠ°ΠΊΠ°.
ΠΡΠΈΠΌΠ΅Π½Π° ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎΠ³ ΡΠΈΡΡΠ΅ΠΌΠ° ΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½Π° ΠΊΠΎΡΠΈΡΡΠ΅ΡΠ΅ΠΌ ΠΏΠΎΠ΄Π°ΡΠ°ΠΊΠ° ΠΎ
Π»Π΅ΡΡ Π½Π° ΡΠ΅Π»Π°ΡΠΈΡΠΈ ΠΠ΅ΠΎΠ³ΡΠ°Π΄ - ΠΠΌΡΡΠ΅ΡΠ΄Π°ΠΌ, Π·Π° ΠΏΠ΅ΡΠΈΠΎΠ΄ ΠΎΠ΄ Π³ΠΎΠ΄ΠΈΠ½Ρ Π΄Π°Π½Π°. ΠΠΎΠ±ΠΈΡΠ΅Π½ΠΈ
ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠΈ ΠΏΠΎΠΊΠ°Π·ΡΡΡ Π΄Π° ΡΠ΅ Π½Π΅ΠΎΠΏΡ
ΠΎΠ΄Π½ΠΎ ΡΠΊΡΡΡΠΈΡΠΈ ΠΏΡΠ΅ΠΏΠΎΡΡΠΊΡ Π΅ΠΊΡΠΏΠ΅ΡΡΠ° Ρ ΠΏΡΠΎΡΠ΅Ρ
ΠΏΡΠ΅Π΄Π²ΠΈΡΠ°ΡΠ°, ΠΊΠ°ΠΎ ΠΈ Π΄Π° ΡΠ°ΠΌ Π°Π»Π³ΠΎΡΠΈΡΠ°ΠΌ Π½ΠΈΡΠ΅ Π΄ΠΎΠ²ΠΎΡΠ°Π½ Π΄Π° Π±ΠΈ ΡΠ΅ Π΄ΠΎΠ±ΠΈΠ»ΠΈ Π΄ΠΎΠ²ΠΎΡΠ½ΠΎ
ΠΏΡΠ΅ΡΠΈΠ·Π½ΠΈ ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠΈ. Π’Π°ΠΊΠΎΡΠ΅, Π΄ΠΎΠ±ΠΈΡΠ΅Π½ΠΈ ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠΈ ΡΠΊΠ°Π·ΡΡΡ Π΄Π° ΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΊΠΎΡΠΈ ΡΡ
Π·Π°ΡΠ½ΠΎΠ²Π°Π½ΠΈ Π½Π° ΠΠΠ ΠΏΡΠΈΡΡΡΠΏΡ ΠΈ ΠΊΠΎΡΠΈ ΠΊΠΎΠΌΠ±ΠΈΠ½ΡΡΡ ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠ΅ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° ΠΈ ΠΏΡΠ΅ΠΏΠΎΡΡΠΊΡ
Π΅ΠΊΡΠΏΠ΅ΡΡΠ°, ΠΏΡΠ΅ΡΠΈΠ·Π½ΠΈΡΠΈ ΠΎΠ΄ ΠΌΠΎΠ΄Π΅Π»Π° ΠΊΠΎΡΠΈ ΠΊΠΎΡΠΈΡΡΠ΅ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π°Π»Π½Π΅ ΠΌΠ΅ΡΠ΅ Π·Π°
ΠΈΠ·ΡΠ°ΡΡΠ½Π°Π²Π°ΡΠ΅ ΡΠ»ΠΈΡΠ½ΠΎΡΡΠΈ. Π‘Ρ
ΠΎΠ΄Π½ΠΎ ΡΠΎΠΌΠ΅, ΠΏΠΎΡΠ²ΡΡΠ΅Π½ΠΎ ΡΠ΅ Π΄Π° Π»ΠΎΠ³ΠΈΡΠΊΠΈ ΠΏΡΠΈΡΡΡΠΏ
ΠΌΠΎΠ΄Π΅Π»ΠΎΠ²Π°ΡΡ ΡΠ»ΠΈΡΠ½ΠΎΡΡΠΈ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ° ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π°Π½ ΠΏΡΠ°Π²Π°Ρ ΠΏΡΠΈΠΌΠ΅Π½Π΅ Ρ ΠΎΠΊΠ²ΠΈΡΡviii
ΡΠ΅Ρ
Π½ΠΈΠΊΠ΅ Π·Π°ΠΊΡΡΡΠΈΠ²Π°ΡΠ° Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΡΠ»ΡΡΠ°ΡΠ°. Π‘Π° ΠΏΡΠ°ΠΊΡΠΈΡΠ½Π΅ ΡΡΡΠ°Π½Π΅, ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ
ΡΠ΅ΡΠ΅ΡΠ΅ ΡΠ΅ ΡΠ΅Π΄Π½ΠΎΡΡΠ°Π²Π½ΠΎ Π·Π° ΡΠ°Π·ΡΠΌΠ΅Π²Π°ΡΠ΅ Ρ ΠΏΠΎΠ³Π»Π΅Π΄Ρ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠ°ΡΠ°, ΠΈ ΠΌΠΎΠΆΠ΅ ΡΠ΅ Π΄ΠΎΡΡΠ°
ΡΠ΅Π΄Π½ΠΎΡΡΠ°Π²Π½ΠΎ ΠΈΠΌΠΏΠ»Π΅ΠΌΠ΅Π½ΡΠΈΡΠ°ΡΠΈ ΠΈ ΠΏΡΠΈΠ»Π°Π³ΠΎΠ΄ΠΈΡΠΈ ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΎΡΡΠΈΠΌΠ° ΠΈ ΠΎΠΏΠ΅ΡΠ°ΡΠΈΡΠ°ΠΌΠ°
Π°Π²ΠΈΠΎ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΡΠ΅.In this doctorial dissertation no-show passengers prediction system based on
computational intelligence techniques is proposed. Predicting no-show passengers
represents a specific and concisely formulated problem that actively persists for a longer
period of time in the airline industry from both theoretical and practical perspective.
Based on the expected number of no-show passengers, as well as some other factors,
airlines are making decisions about how many additional seats will be allowed for
overbooking through reservation system. This way, airlines could make additional
profit, especially when it comes to the high demanding flights that are fully booked.
Proposed prediction system for no-show passengers consists of two major
components. First component considers selecting the best performing prediction model
from the available model pool, and the second component is related to the model
validation and application. Prediction model is based on the algorithm that combines
case based reasoning technique and interpolative Boolean algebra (IBA) approach.
Furthermore, model combines prediction recommendation generated by algorithm and
recommendation provided from the domain expert. This way, the proposed system
considers and takes into account both objective and subjective dimension. Similarity
between flights is determined using traditional metrics (Euclidean and Manhattan) and
IBA similarity measure. Also, IBA approach is enhancing the conventional CBR
algorithm by enabling logical aggregation of values, i.e. capturing existing nonlinear
dependencies in the data.
The usage of the proposed system is illustrated in the numerical example
regarding a single leg flight on the Belgrade-Amsterdam route and covers a one-year
period. The obtained results show the necessity to include expert knowledge in
prediction process, i.e. the CBR algorithm used alone is insufficient to produce results
that are accurate enough. Furthermore, the results are indicating that the IBA-based
models that combine the results of the CBR algorithm and expert recommendations
perform better than distance-based models. Therefore, it is confirmed that the logicbased approach of similarity modelling is the prospective direction within the CBR
algorithm. From a practical side, proposed solution is easy for understanding from thex
functional aspect, and could be easily implemented and adjusted according to airline
operations