Forecasting in Uncertainity MKmetric Presentation Cracow 20110309-Final

Air Transport Market Forecastingin Dynamic Market Environment

Air Transport Market Forecastingin Dynamic Market Environmentwith Uncertain Data

C O N F I D E N T I A L | www.mkm.de

in Dynamic Market Environmentwith Uncertain Data

System Approach (x-via, SONAR) ® MKmetric 1992

Dr. Benedikt MandelKarlsruhe, 28.02.2011

with Uncertain Data

System Approach (x-via, SONAR) ® MKmetric 1992 Dr. Benedikt MandelCracow, 10-11.03.2011

Agenda

�MKmetric

�Methodology

�Application x-via web

�Applikation SONAR

11st Polish Regional Airport Association Conference, Cracow 10-11.03.2011

�Examples from former MKmetric studies

�Results of network simulations for Airport Poznań (POZ)

MKmetricCompany profile

� MKmetric was founded 1993 as spin-off of the Karlsruhe Institute of Technology based on the idea to apply science. The organisation is an independent institute.

� Special fields of business:- air transport analysis and forecasting,- simulation of strategic, tactical and political decisions in air transport,- transport systems consulting,- provision of software systems for transport forecasting and strategic analysis,- provision of online solutions and tools for tactical air transport system analysis,- development of web applications.

� Experience: 20 years research, 17 years transport consulting.


� Experience: 20 years research, 17 years transport consulting.

� Special fields of scientific interest are the development and application of: - level & discrete choice algorithms, - OR routines for process optimisation, - programs to encounter system interdependencies.

� Major qualification: - data and data gap handling,- multimodal demand & supply modelling, - analysis & simulation as well as - the development & test of policy instruments and forecasts,- design, programming and establishment of related software and - assignment of tailor made hardware components.

MKmetricProject References / Clients

� Know how in EC Framework Program work (DG TREN):STEMM, BRIDGES, ASSEMBLING, Spotlights, TEN PAN, Forecast 2020, APRON, STAC, ETIS-Base, -Agent, -Link, ETISplus, Worldnet - global air cargo, Toolqit, Interconnect;i.g. responsible for data/network/models/analysis/forecast/scenarios, pax (all modes), air cargo

� Know how in Interreg Program work (DG Regio): SEABIRD (Baltic Sea), SEAPLANE (North Sea), EUROPLANE (CEE) - air transport market potential and route potential forecast and EC policy issues.

� Air transport market potential and route potential analyses and forecasts for several airports (hubs, intl. network, regional), airlines (network, regional, charter, LCC) in 20 European countries (since 1993)

� Numerous projects for railway operators (high speed, airport connectivity, line service, track),


� Numerous projects for railway operators (high speed, airport connectivity, line service, track), consultancies (assistance, data) and universities (research, data) as well as Ministries of Transport(national, federal) and regional authorities

� Active as: Project-Coordinator, WP-leader, Task-leader and Trustee.

� Air transport projects in Poland:

- Airport Poznań > Route potential forecast ex-post (2005), update with scenarios (2007/2008)- Airport Łódź > Route potential forecast ex-post (2008)- LOT Polish Airlines > Route potential forecast ex-post for Warsaw

Task 1 (2007-2008) forecast split for PLL LOT and CENTRALWINGS

- Ministry of Infrastructure > Analyses of the Polish air transport system with scenarios (2009/2010)Forecast all airports 2015, 2025, 2035 with simulation of 18 scenarios

For further details please visit our web site: www.mkm.de

Agenda

�MKmetric

�Method


�Application SONAR




MethodThe situation of the travellers and their behaviour are the main issue.

Car, train or plane?STR, FRA or MUC?Departure, when?By Metro to Airport

or ...?

Trip yes or no?Where to?

Which modality?What carrier?

When?


Transparency taken from the presentation: „Data for network planing in air transport“;IVT-Seminar; Dr. Karl Echtermeyer; DLH AGJune 2000; ETH Zürich

decision

MethodData background - IATA Strategy Symposium 2010


!�

MethodPoor data supply background - SITA Trends Survey 2010 (Airline IT)

� Today 40,8 % of tickets are direct sales from the airline to the traveller. Thereof- 25,8% by internet- 10,7% by call centre- 4,3% by interlining

� In 2013 the following targets are envisaged:- 55,1% direct sales whereby - 33,9% are by internet but - call centre and interlining remains stable

� Increasing activities by airlines using ‘Smartphones’ features in 2013 for- ticket sales - 70% of all airlines / 85% of the big airlines (today)- flight status information - 86%

All activities

listed will

reduce

within

2 years

further the

sample size,


- flight status information - 86%- mobile online check-in - 80% (today 28%)- mobile electronic boarding pass - 76%- travel offers - 68%

� Increasing self service up to 2013- agent check-in reducing from today 50,7% to 28,9%- kiosk check-in remains stable at 20%- kiosk ticket sales - 80%- more kiosks - 47%

� Introduction of booking portals by airlines up to 2013- for travel agencies - 84% (today 41%)- for business clients - 82% (today 44%) - social networking functions - 55% (today 21%)

sample size,

coverage

and quality

of the

database

used by

classical

forecast

models!

Classic air transport forecast

Trend

MethodData background

Air transport market informationMarketing Information Data Tapes / Billing and Settlement Process

100%

50%

Ticket / Coupon data

Why?- direct sales, e.g. internet

- cost reduction- consolidators- GDS (Global Distribution System*)


Ticket/Coupon,Booking data

Up to 1995 Today

50%

Up to 1995 Today

Booking data

Size, type and structureof the market are well known.

Fragmented market, new products, type, structure, faster shock waves, global drivers, new sales structure, limited rights using airline ticket sales data.

* Global Distribution System, z.B. AMADEUS, GALILEO, SABRE, TRAVELPORT

MethodMarket dynamics and Data supply

� The market situation changed

- differentiation inside the airline world (network, charter, LCC, all business)

- consolidation by mergers and acquisitions (Lufthansa, BA & Iberia, AF & KLM, etc.)

- development of global airline alliances (North & South America, Gulf, Asia, Russia?)

- growing influence of Gulf Arab Airlines (huge aircraft orders)

- new aircraft types (A380, B787, A350, A320 neo, B797?, CS-Series …)

- new products on board (new classes, changes in fare structure, tariff decomposition)

- new markets (short trips, migrations, multiple leisure trips, VF&R trips)

� Stable markets are going unstable

- change of schedule faster (try & error)

- growing power of economic drivers (GDP, kerosene, bank crises)


- growing power of economic drivers (GDP, kerosene, bank crises)

- global disease effects (SARS, bird flue)

- environmental catastrophes (volcano, hurricanes, earth quakes, flooding)

- regulations (taxes, emission trading, environmental fees)

� New links to the customer

- changing distribution channels (direct sales, GDS, non- GDS, Google -ITA)

- new customer behaviour (social media – Facebook, Twitter, YouTube)

� Changing competition

- between airlines, alliances on flight segments and routes, between airports (hub, spoke)

- with other modes (HSR, car, bus)

Trend based forecasts neither reflect the changes nor cope with the data leakage.

MethodData background for all MKmetric systems (VIA, SONAR, x-via web)

Consumer elasticity e.g.- airport surveys across Europe, - DE - KONTIV survey, mobility survey,- DK - national mobility survey,- CH - national travel survey,- EU - Dateline mobility survey, ...

Volume observations e.g.

- detailed Eurostat, national statistics(on flight, on stage)

- airport, airline publications, IATA samples,- associations of airports and airlines,- link counting for road- transport figures for rail, ...


Mode networks e.g.

- air schedules (OAG, Cedion, ...),- information from the air transport industry,- surface networks (road, bus),- railway, ferry schedules ,- MKm extensions, ...

Regional attractors e.g.

- socio-economy (UN, IWF, OECD, EZB, ...),- satellite data (Corine aggregates), - tourist information- land use data, - meteorological data, ...

MethodThe point of view turns from the airport to the region as starting point of the trip decision. Therefore the traditional static view becomes a consumer oriented dynamic one.

Conventional / Traditional Modelling (Airport-Airport with fixed Isochrones)


Enriched point of view (System approach: Region-Region via multiple Routes)

Air transport model

Method – MKmetric system approachMKmetric explains transport in a consistent way. No transport activity appears or vanishes unexplained.

Transport is embedded in its determinants


Model layers

Determinants

Scenarios

• MultimodalityFor a trip from Poznan to Brussels use- the plane- the train- the private car or a coach

• IntermodalityFor a trip from Poznan to Brussels by air starting from an airport in Berlin - and use the train to Berlin Zoo (+ Bus)

Forms of modality*

Multi-modality

Multi-modality

Method – MKmetric system approachWhich modality? - Which mode? - Which route?

Types of modality


- and use the train to Berlin Zoo (+ Bus)- the private car to Berlin-Tegel

• IntramodalityFor a trip from Poznan to Brussels usethe plane either on the route - POZ - FRA - BRU or- POZ - WAW - BRU or- WAW - BRU or- THF - BRU or ...

MKmetric

Inter-modality

Inter-modality

Intra-modality

Intra-modality

Method – MKmetric system approach APC Bielefeld - Hong Kong (business)


Method – MKmetric system approach Display of consumer cost elasticity for a specific route.


Method – MKmetric system approach Travellers‘ consumer behaviour is non-linear. Thresholds influence the decision and activate changes in product choice. Thus consumers‘ elasticity is a key issue to understand.


Method – MKmetric system approach Travellers‘ consumer behaviour is non-linear. Thresholds influence the decision and activate changes in product choice. Thus consumers‘ elasticity is a key issue to understand.

i, j∈Cn

Logit

−

=)ln(

)1(: )(

x

xx k

k λλλ

0

0

=≠

k

k

λλ

∑=

j jnUinU

nP(i)


Cross elasticity

Point elasticityCeteris paribus variation of the demand for alternative i by a 1% change of the characteristic value of alternative i.

Ceteris paribus variation of the demand for alternative j by a 1% change of the characteristic value of alternative i.

nP(i)kinx

kinxnP(i)

)kinx,n(P(i)∂∂=η

nP(i)

kjnx

kjnxnP(i)

)kjnx,n(P(i)∂∂=η

Method – MKmetric system approach - ExcursusThe price elasticity diversified by markets in the year 1991.

20%

40%

40%

60%

80%

60%

80%

100%

Change o

f pass

enger

dem

and

Hamburg 1991 Hamburg 1991Hamburg 1991

Vacation VacationVacation

Europe IntercontinentalDomestic

Travel market (Hamburg base year 1991) – research results from 1992/93

World-wide first scientific explanation for LCC- success


-80%

-60%

-40%

-20%

0%

-100 -50 0 50 100 150 200

-80%

-60%

-40%

-20%

0%

20%

-100 -50 0 50 100 150 200

-80%

-60%

-40%

-20%

0%

20%

40%

-100 -50 0 50 100 150 200

Price variation per passenger in DM

Change o

f pass

enger

dem

and

Private

Business

Private

Business

Private

Business

Price

Generation/distribution

Modal split total sum of utilities over all modes

Method – MKmetric system approach Linking the model steps by a quasi-direct format (QDF) in the forecasting system

Each change in one layer of the econometric model will be re-calculated and considered in the next layer.


Airport choice

Access/egress choicetotal sum of utilities over all modes

total sum of utilities over all alternatives

Slot choicetotal sum of utilities over all alternatives

Logical sequence but computed in reverse order

Method – MKmetric system approach MKmetric approach to market investigation using multi level econometric models for simulation.Procedure to establish the reference case and its use for the simulation of scenarios.

Detailed information about the MKmetric System Approach can be found at www.mkm.de

Socio-economy

Infrastructure Urbanisation

Reference Status Statistics,observations,

Transportpolicy

Scenario


System Approach- generation- distribution- mode choice- airport/route choice- assignment

observations,surveys, ...

Assessment, evaluation, analyses of results

Ex postEx ante

Scenariodefinition

Method – MKmetric system approach Iterative calibration process.

Distribution

Generation

Modal split

Matrix evaluation

Mode choice assessment

Base statistic evaluation

Matrix Bounding

Model / Input adjustment


Route choice

Assignment Link load assessment

Airport / Route choice Assessment

Statistic evaluation

The calibration is an iterative process where data from various sources and model results are assessed to detect irregularities, inconsistencies and errors. The arrows symbolise the principle process flow but due to the complexity the recursive parts and their nesting can not be displayed.

Generation of traffic:

�Socio-economic framework data (e.g. population, structure, GDP)

�Political decisions (e.g. taxes, security, noise charges)

Distribution of traffic :

�Regional attractivities (e.g. type of region, temperature, sea, mountains)

�Political decisions (e.g. traffic rights, subsidies)

Mode choice:

�Network / Service characteristics (e.g. time, cost, frequency, transfer, operation days)

Method – MKmetric system approach Principle scenario types at the different model stages.


�Network / Service characteristics (e.g. time, cost, frequency, transfer, operation days)

� Political decisions (e.g. „PSO“, infrastructure investments)

Airport / Route choice:

�Service-Structure (e.g. new route / closure, „MCT“, airline base, transfer node)

� Infrastructure (e.g. access / egress by surface modes, inter-modal routes)

Assignment:

� Infrastructure networks (e.g. new airports, new HSR services) and/or changes of network attributes (e.g. capacity, speed, charges, tolls, fees)

Please note that the examples may as well be applicable in other model stages.

Method – MKmetric system approach Excursus: Complexity and coverage.

Regions:

�Europe on NUTS 3 level

�World (aggregates of administrative units)

Relations:

�Region to Region demand matrix

�About 1900 x 1900 relationships

Airports:

�Europe – all scheduled services (e.g. delivered by OAG, HAFAS, web sites, own research)

�World - representative airports with scheduled services for all world regions


�World - representative airports with scheduled services for all world regions

Surface modes (Feeders / Competitors):

�Road - network ca. 2,8 Mio. links, up to county road level

�Rail – whole network with real Europe-wide schedule data

Alternatives:

� Intercontinental destinations represented by 16 alternatives per relation

�European destinations represented by 10 alternatives per relation

�National destinations represented by 7 alternatives per relation

Trip purposes:

�business

�non-business (private u. vacation trips)

Agenda

�MKmetric

�Method

�MKmetric applications SONAR, x-via web





x-via web - Online analyse and simulations tool Approach and focus.

MKmetric approach :�Best possible consistent reflection of the market

based on determined information in an uncertain environment.�Understanding of consumer reaction

by their elasticities (price, time, frequency, alliance, comfort, ...).�Assistance for independent analyses

by an easy to use intuitive interfaceand download of all tables and graphs to the own desktop for further use.

�Tool optimised for „online“ usage by clients with no browser restrictions, mobile access and fast response time.

Focus of the x-via web tool: �Concentration on the mode air transport.


�Coverage of commercial air traffic inbound, outbound, across and within Europe for all air service types (FSC, LCC, Charter carrier).

�Exploring the problem of intra-modality, the competition in the air transport system.�Enhancing the transparency of the air transport market

by own data maintenance, harmonisation and processing embedding multiple data sources (socio-economic, survey, mobility data, ...)circumventing GDS gaps e.g. due to internet salesproviding full scaled interregional demand matrices matching latest statistics.

�Analyses of the competition among airports.�Analyses of the competition among routes.�Flexible scenario definition and conservative simulation.� Benchmarking demand effects at the objective reference case displaying a full market

picture of the previous year.

x-via webScenario definition and simulation.

Flexibility in the scenario definition:

�Add / delete air services.

�Change flight schedules.

�Change air service characteristics like time, frequency, day of operation, airline, alliance, aircraft, terminal.

�Change airport characteristics minimum connecting times in general and detailed.

�Modulate market volumes by introducing your expertise and ideas.


�Modulate market volumes by introducing your expertise and ideas.

�Upload of multiple schedules (network, nodes, waves).

Simulation of:

�non-linear consumer behaviour (consideration of thresholds),

�demand effects for one route or a network,an airport or market,

� local and transfer passengers.

x-via webThe tool allows analyses out of three different point of view; the airport, the region and the route (airline).

Region:

�Airport / Route choice of the traveller by route and trip purpose.

�Diffusion diagram of competing airports.

�Accessibility of regions.

Airport:

�Catchment of the airport or a route for OD and transfer travellers.

�Proportional distribution of the demand in space.

�Airlines and air services at an airport.


�Airlines and air services at an airport.

Route:

�Demand by routes at an airport (Spider).

�Feeder-Information of a flight segment (Sheaf).

�Top transfer destinations.

Data coverage:�Analyses available for all European airports with commercial traffic and regions.

x-via webRequirements of the tool usage.

Technical standard: - Internet access,- Browser - Firefox >=1.5 or Internet Explorer 6+- or Opera mobile with UMTS.

Cooperation between client and customer to benefit the further tool development: - analyses types, simulation types,- tool-handling, format,- content of working processes and / or standard reports, „story“,


- content of working processes and / or standard reports, „story“,- statistics, airport surveys,- response about errors and difficulties.

Availability:- 365 days 24 hours, except maintenance time and “Force majeure”,- assistance during the general working hours, exclusive vacation time.

Agenda

�MKmetric

�Method






SONAR - Scan Of New Air RoutesApproach and focus.

MKmetric approach:� Best possible reflection of the market based on determined information, containing: traffic and

infrastructure data for all transport modes, socio-economic data and other determinants.� Understanding of consumer reaction by elasticity (price, time, frequency, alliance, comfort, ...).� Successive dual-scan of the demand side for air passenger potentials and the supply side for

competitive air passenger destinations.� Iterative simulation of air passenger demand potential on the identified routes by optimised procedures

under variation of the air service characteristics (e.g. carrier, schedule, frequency, ...).

� Conservative expert assessment and evaluation of each detected route after each simulation iteration.

Focus of SONAR:

� Concentration on air transport.


� Concentration on air transport.� Coverage of commercial air traffic inbound, outbound, across and within Europe

for all air service types (FSC, LCC, Charter carrier).

� Consideration of intra-modality and on request demand generation.

� Full scaled interregional demand matrices based on multiple data sources matching latest statistics and circumventing GDS data gaps (e.g. due to internet sales).

� Diversified market investigation of an airport, airline or region for the acquisition and route inauguration.

� Identification of potential new destinations, conservative assessment as base for financial calculation.

� Benchmarking demand effects at objective reference case displaying full market picture of previous year.

� Route specific analyses using standard formats for simplified comparison.

� Adaptable parameters for the definition of SONAR in respect of airline / air alliance, airport / terminal, air service types and predefined routes or networks.

SONAR - Scan Of New Air Routes The analyses is structured in four sections and are displayed in a standard format reflecting different point of views.

1. Theory (popular scientific explanation of the system approach)

2. Information and analyses of the airport location in focus- catchment, accessible GDP, population and employment, actual air services

3. Analyses for the identified and selected routes- Network sheaf - graph including successor and predecessor segments - by total pass.- Estimated demand, table - total, local, transfer, business, non-business pass. figures- Technical route information, table - distance, suggestion of airline, aircraft and schedule

including corresponding capacity, frequency and load factor


including corresponding capacity, frequency and load factor- Spatial distribution of passengers, maps - for both airports connected by the route - Top transfer destinations, table - from-via-to airport transfer connections by frequency- Airport choice - graph - identified route and competing alternative routes- Airlines market position at the destination airport, table - market shares of airlines serving

the destination airport- European destinations linked by destination airport, status quo, graph - by frequency- Destinations served outside Europe by the destination airport, list of airports

4. Effects upon the airport in focus- catchment and its changes, aircraft movements, passengers, accessibility and its change- summary with recommendations

Examples of analyses displayed by SONAR can be found at www.mkm.de.

�MKmetric

�Method






Examples - MKmetric long term forecastSelected long term forecasts for small, medium and large airports (1993, 1995 and 2003 for the period up to 2010).


Berlin Brandenburg International Airport,planned new airport, forecasted in 1993.

Hamburg Airport forecasted in 1995.

Frankfurt Airport forecasted in 2003.

Results network simulations for Airport Poznań (POZ)Example: Results of first route potential analysis for POZ (INTERREG project EUROPLANE 2004-2006)


New route POZ-DUB

MKmetric forecast for 2006: = 61.208 pax

Airport statistics POZ-DUB (04 - 12.2006): = 55.853 pax (Aer Lingus 2x7, Ryanair 3x7)

Route POZ- DUB: Forecast from 2005 = Reality 2006!

Results network simulations for Airport Poznań (POZ)Example: Historic reference from MKmetric forecast for POZ (2006) – airport statistics


1) Forecast for Barcelona BCN – scheduled Centralwings. Operation: “Barcelona” Girona - scheduled Centralwings.

2) Forecast for Paris CDG – scheduled Air France or LOT with code share Air France. Operation: “Paris” Beauvais - scheduled Centralwings.

3) Forecast for Rome FCO – scheduled AlItalia or Air One or LOT with code share Air One. Operation: Rome CIA - scheduled Centralwings.

R) Remark:

The charter destinations Antalya, Heraklion and Tenerife (Pax 49.453) in operation show in total the charter potential indicated by the MKm forecast of 51.163 pax for all charter destinations (see next slide with orig. forecast). If vacationists can just select 3 out of 7 destinations the demand concentrates to a certain extent on the services available.

Results network simulations for Airport Poznań (POZ)Example: Historic reference from MKmetric forecast for POZ (2006) – simulation results


Examples - MKmetric route forecastSelected route forecasts for small, medium and large airports.

Final decision is with the airline.


Late but finally achieved.

Examples - MKmetric route forecastSelected route forecasts for small, medium and large airports.

Suggested

by MKm in RouteForecast

Pax [p.a.]

Airline

suggested

Actually

inaugurated in

Pax 2009

[p.a.]

Airline

flying Remarks

2004 HAJ-RJK 10.000 Charter 2005 21.000 Tuifly

2004 OST-LPA 14.000 Charter 2007 16.000 Jetairfly

2004 OST-PMI 11.000 Charter 2007 16.000 Jetairfly

2004 SVG-TRD 69.000 Braathens 2005 65.000 SAS Partly stopover flights

2006 BRE-AGP 50.000 Air Berlin 2006 56.000 Ryanair

2006 BRE-ALC 42.000 Air Berlin 2007 33.000 Ryanair

2006 POZ-DUB 61.000 Ryanair 2007 56.000 Ryanair

2006 POZ-TFS 5.000 Charter 2007 5.000 Charter Stopped 2009, alternative e.g. HRG, ATY


2007 GOA-MAD 47.000 Iberia 2008 39.000 Iberia Larger A/C and lower frequency as suggested

2007 MUC-BIO 100.000 Lufthansa 2008 140.000 Lufthansa Parallel service to OVD assumed (78000 forecast)

2007 MUC-SIN 103.000 Lufthansa 2008 114.000 Lufthansa

2007 MUC-TLL 48.000 Lufthansa 2008 57.000 Estonian

2007 POZ-EDI 61.000 Ryanair 2008 44.000 Ryanair Lower frequency, other competing UK routes

Suggested

by Mkm in RouteForecast

Pax [p.a.]

Airline

suggested

Actually

inaugurated

Pax 2009

[p.a.]

Airline

flying Remarks

2004 HAJ-CIA Air Berlin 2011 n.a. Germanwings will offer 976 seats on 4/7 frequency to FCO

2004 VXO-AGP 9.000 Charter 2011 n.a. Ryanair will offer 756 seats on 2/7 frequency to ALC

2006 BRE-OPO 32.000 dba 2011 n.a. Ryanair will offer 756 seats on 2/7 frequency

2007 MUC-TRD 39.000 Lufthansa 2011 n.a. Lufthansa will offer 432 seats on weekends

Late but finally achieved.

�MKmetric

�Method






Results network simulations for Airport Poznań (POZ)Example: Scenario v.12 – New LO flights to AMS, BRU, CDG; BZG –WAW, shuttle BZG-POZ


Results network simulations for Airport Poznań (POZ)Example: Scenario – Timetable for new LO flights (2xEMB175), BZG to WAW (LO), shuttle BZG-POZ


Results network simulations for Airport Poznań (POZ)Example: Winners and losers, demand effects across the air services at POZ


Results network simulations for Airport Poznań (POZ)Example: New destination AMS, O&D and transfer passengers


Results network simulations for Airport Poznań (POZ)Example: New destination ZRH, O&D and transfer passengers


Results network simulations for Airport Poznań (POZ)Example: New destination DUS, O&D and transfer passengers


Results network simulations for Airport Poznań (POZ)Example: Influence of new scenario for POZ on traffic in WAW


Results network simulations for Airport Poznań (POZ)Example: Demand effects across the air services at WAW due to the POZ scenario


Results network simulations for Airport Poznań (POZ)Example: Influence of new scenario for POZ on traffic in FRA


Results network simulations for Airport Poznań (POZ)Example: Influence of new scenario for POZ on traffic in MUC


Results network simulations for Airport Poznań (POZ)Example:


MKmetric Gesellschaft für Systemplanung mbH

www.mkm.de


www.mkm.de

[email protected]

Forecasting in Uncertainity MKmetric Presentation Cracow 20110309-Final

Documents

Transcript of Forecasting in Uncertainity MKmetric Presentation Cracow 20110309-Final