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Applying the fuzzy analytical hierarchy process in cognitive cities

Published: 27 October 2014 Publication History

Abstract

This paper introduces a mobile application (app) as the first part of an interactive framework. The framework enhances the interaction between cities and their citizens, introducing the Fuzzy Analytical Hierarchy Process (FAHP) as a potential information acquisition method to improve existing citizen management endeavors for cognitive cities. Citizen management is enhanced by advanced visualization using Fuzzy Cognitive Maps (FCM). The presented app takes fuzziness into account in the constant interaction and continuous development of communication between cities or between certain of their entities (e.g., the tax authority) and their citizens. A transportation use case is implemented for didactical reasons.

References

[1]
Al-Subhi Al-Harbi, K. M. 2001. Application of the AHP in project management. International Journal of Project Management 19, 19--27.
[2]
Caragliu, A., Del Bo, C., and Nijkamp, P. 2009. Smart cities in Europe (No. 0048).
[3]
Dzhusupova, Z., Ojo, A., and Janowski, T. Organizing and managing knowledge for e-government. In Proceedings of the International Conference on Knowledge Management and Information Sharing, 206--211.
[4]
Finger, M. and Langenberg, T. 2006. Electronic Governance. In Encyclopedia of Digital Government 2, Anttiroikko, A. V. and Mälkiä M., Eds. Hershey: Idea Group Reference, 629--633.
[5]
Finger, M. Forthcoming. A critical analysis of the potential of the ICTs for democracy and governance. In E-Government and Websites: A Public Solutions Handbook, A. Manoharan, Ed. Armonk, NY: M. E. Sharpe.
[6]
Goldstein, J. 1999. Emergence as a construct: History and issues. Emergence, (1), 49--72.
[7]
Hollands, R. 2009. Will the real smart city please stand up?, City, 12(3), 303--320.
[8]
Johannesson, P. and Perjons, E. 2012. A Design Science Primer. CreateSpace.
[9]
Kaufmann, M., Portmann, E., and Fathi, M. 2012. A concept of semantics extraction from web data by induction of fuzzy ontologies. In International Workshop on Uncertainty Reasoning for the Semantic Web.
[10]
Lin, T. Y. 1997. Granular computing: From rough sets and neighborhood systems to information granulation and computing in words. In European Congress on Intelligent Techniques and Soft Computing, 1602--1606.
[11]
Lin, T. Y. 2003. Granular computing. In Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. Springer, Berlin Heidelberg, 16--24.
[12]
Mostashari, A., Arnold, F., Mansouri, M., and Finger, M. 2011. Cognitive Cities and Intelligent Urban Governance. Network Industries Quarterly, 13(3).
[13]
Portmann, E., Kaufmann, M. A., and Graf, C. 2012. A distributed, semiotic-inductive, and human-oriented approach to web-scale knowledge retrieval. In Proceedings of the 2012 international workshop on Web-scale knowledge representation, retrieval and reasoning, 1--8.
[14]
Portmann, E. and Kaltenrieder, P. 2015. The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases In Information Granularity, Big Data, and Computational Intelligence, Pedrycz, W. and Chen, S. M., Eds. Springer Verlag, Berlin Heidelberg, 325--346.
[15]
Saaty, T. L. 2008. Decision making with the analytic hierarchy process. International Journal of Services Sciences, 83--95.
[16]
Tusnovics, D. A. 2007. Cognitive Cities: interdisciplinary approach reconsidering the process of (re) inventing urban habitat. na.
[17]
Vaidya, O. S. and Kumar, S. 2006. Analytic hierarchy process: An overview of applications. European Journal of Operational Research 169, 1--29.
[18]
Van Laarhoven, P. J. M. and Pedrycz, W. 1983. A fuzzy extension of Saaty's priority theory. Fuzzy Sets and Systems, (11), 229--241.
[19]
Washburn, D. and Sindhu, U. 2009. Helping CIOs Understand "Smart City" Initiatives. Growth.
[20]
Yao, Y. Y. and Zhong, N. 1999. Potential applications of granular computing in knowledge discovery and data mining. In Proceedings of World Multiconference on Systemics, Cybernetics and Informatics 5, 573--580.
[21]
Yao, Y. Y. 2000. Granular computing: basic issues and possible solutions. In Proceedings of the 5th Joint Conference on Information Sciences 1, 186--189.
[22]
Yao, Y. Y. 2005. Perspectives of granular computing. In 2005 IEEE International Conference on Granular Computing 1, IEEE, 85--90.
[23]
Zadeh, L. A. 1965. Fuzzy Sets. Information and Control 8(3), 338--353.
[24]
Zadeh, L. A. 1979. Fuzzy sets and information granulation, Advances. In Fuzzy Set Theory and Applications, M. Gupta, R. K. Ragade, R. R. Yager, Eds. North-Holland Publishing Company, 3--18.
[25]
Zadeh, L. A. 1988. Fuzzy logic. Computer, 21(4), 83--93.
[26]
Zadeh, L. A. 1998. Some reflections on soft computing, granular computing and their roles in the conception, design and utilization of information/intelligent systems. Soft Computing-A fusion of foundations, methodologies and applications, 2(1), 23--25.

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  • (2020)Cognitive Systems for Urban Planning: A Literature ReviewScience and Technologies for Smart Cities10.1007/978-3-030-51005-3_22(249-270)Online publication date: 28-Jul-2020
  • (2018)A Review on the Meaning of Cognitive Cities2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)10.1109/IISA.2018.8633654(1-5)Online publication date: Jul-2018
  • (2018)A Dynamic Route Planning Prototype for Cognitive CitiesDesigning Cognitive Cities10.1007/978-3-030-00317-3_10(235-257)Online publication date: 19-Sep-2018
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cover image ACM Other conferences
ICEGOV '14: Proceedings of the 8th International Conference on Theory and Practice of Electronic Governance
October 2014
563 pages
ISBN:9781605586113
DOI:10.1145/2691195
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • Macao Foundation, Macao SAR Govt: Macao Foundation, Macao SAR Government
  • Municipio de Guimarães: Municipio de Guimarães

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 October 2014

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Author Tags

  1. cognitive city
  2. decision support system
  3. e-governance
  4. fuzzy analytical hierarchy process
  5. granular computing
  6. smart city

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ICEGOV2014
Sponsor:
  • Macao Foundation, Macao SAR Govt
  • Municipio de Guimarães

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ICEGOV '14 Paper Acceptance Rate 30 of 73 submissions, 41%;
Overall Acceptance Rate 350 of 865 submissions, 40%

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Cited By

View all
  • (2020)Cognitive Systems for Urban Planning: A Literature ReviewScience and Technologies for Smart Cities10.1007/978-3-030-51005-3_22(249-270)Online publication date: 28-Jul-2020
  • (2018)A Review on the Meaning of Cognitive Cities2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)10.1109/IISA.2018.8633654(1-5)Online publication date: Jul-2018
  • (2018)A Dynamic Route Planning Prototype for Cognitive CitiesDesigning Cognitive Cities10.1007/978-3-030-00317-3_10(235-257)Online publication date: 19-Sep-2018
  • (2016)Applying the Fuzzy Analytical Network Process in Digital MarketingBig Data10.4018/978-1-4666-9840-6.ch052(1159-1188)Online publication date: 2016
  • (2016)Applying the Fuzzy Analytical Network Process in Digital MarketingFuzzy Optimization and Multi-Criteria Decision Making in Digital Marketing10.4018/978-1-4666-8808-7.ch010(202-232)Online publication date: 2016
  • (2016)Synchronizing Mind Maps with Fuzzy Cognitive Maps for Decision-Finding in Cognitive CitiesProceedings of the 9th International Conference on Theory and Practice of Electronic Governance10.1145/2910019.2910034(363-364)Online publication date: 1-Mar-2016
  • (2016)Personal digital assistant 2.0 — A software prototype for cognitive cities2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)10.1109/FUZZ-IEEE.2016.7737872(1531-1538)Online publication date: Jul-2016
  • (2016)Digital Personal Assistant for Cognitive Cities: A Paper PrototypeTowards Cognitive Cities10.1007/978-3-319-33798-2_6(101-121)Online publication date: 10-Jun-2016
  • (2016)From Smart to Cognitive: A Roadmap for the Adoption of Technology in CitiesTowards Cognitive Cities10.1007/978-3-319-33798-2_2(13-35)Online publication date: 10-Jun-2016
  • (2015)Enhancing multidirectional communication for cognitive cities2015 Second International Conference on eDemocracy & eGovernment (ICEDEG)10.1109/ICEDEG.2015.7114476(38-43)Online publication date: 10-Apr-2015
  • Show More Cited By

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