PPC – Bezahlung pro Klick (Pay per Click) Mit einer e-Commerce Plattform erstellen Sie Ihren eigenen Onlineshop Preis bestellen Für Onlinehändler ist es wichtig um Geschäftsentscheidungen effektiver treffen zu können SmartphonesTablets Händlerkonto Besucherverkehr erreicht werden formulation. Model 10.3. notations. and networks transit for concepts useful Some 10.2. Introduction. 10.1. Wu. Z.X. Lam, K. W.H networks, transit congested in counts passenger from matrices Origin-Destination passenger transit of Estimation 10: - outlook. and Application 9.5. choice. Connection 9.4. search. Connection 9.3. approaches. Existing 9.2. Introduction. 9.1. Wekech. S. Friedrich, M. connections, competing among choice passengers' the addressing model assignment transit Schedule-Based A 9: - Conclusions. 8.5. examples. Application 8.4. models. of system the DY-RT: 8.3. architecture. software DY-RT 8.2. 8.1.Introduction. Rosati. L. Crisalli, U. networks, transit regional of planning Schedule-Based for tool a DY-RT: 8: - perspectives. research and Conclusion 7.5. networks. examples scale small to applications Preliminary 7.4. framework. modeling overall The 7.3. Naples. of city the of study case The 7.2. Introduction. 7.1. Rosati. L. Coppola, P. (APTIS), Systems Information Transportation Public Advanced in occupancy vehicle of prediction Short-term 7: - Conclusion. 6.5. study. Case 6.4. framework. Modeling 6.3. requirements. Model 6.2. Introduction. 6.1. Ben-Akiva. M. Koutsopoulos, H. Morgan, D. Systems, Transportation Public Advanced of Evaluation Simulation-Based 6: - ITS. To Application - models. assignment dynamic Transit 5.4. models. Supply 5.3. models. Demand 5.2. definitions. general and Introduction 5.1. Russo. F. networks, transport public for models Assignment Dynamic Schedule-Based 5: - recommendations. and Conclusions 4.6. models. MSA-based optimise to Proposals 4.5. algorithm. Solution 4.4. model. assignment transit the in functions Utility 4.3. context. Modelling 4.2. Background. 4.1. Nielsen. Anker O. coefficients, random with model transit Schedule-Based Multi-Class Stochastic scale large A 4: - Conclusions. 3.5. issue. Application 3.4. algorithm. assignment transit deterministic The 3.3. definition. problem General 3.2. Introduction. 3.1. Florian. M. algorithm, Setting Label a networks: transit Schedule-Based in paths time-dependent shortest Finding 3: - Conclusion. 2.5. model. the of Estimation 2.4. definition. set choice and database The 2.3. structure. general model: choice service mode-transit joint proposed The 2.2. Introduction. 2.1. Papola. A. Cascetta, E. timetables, service transport ex-urban design to model choice service transit mode dynamic A 2: - Conclusions. 1.6. models. assignment Schedule-based 1.5. models. choice path Schedule-based 1.4. models. supply Transit 1.3. segmentation. temporal demand and time target User 1.2. Introduction. 1.1. Crisalli. U. Nuzzolo, A. overview, general a modelling: transit dynamic in approach Schedule-Based The 1: - Aspects. General - Preface. - EBooks, Musik, Filme, Software, Apps, Onlinekurse und Bilder fallen unter digitale Produkte Teleshopping die den Kunden dazu animieren soll, etwas bestimmtes zu tun eCommerce Plattform Traffic
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EAN: | 9781402076879 |
Marke: | Springer Netherlands |
weitere Infos: | MPN: 14073204 |
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