On the development of a web-based system for transportation services

Karacapilidis, Nikos; Lazanas, Alexis; Megalokonomos, George; Moraïtis, Pavlos

doi:10.1016/j.ins.2005.05.007

Cited by 21 publications

(14 citation statements)

References 17 publications

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“…We set that the threshold of jitter error is 1.5 in our experiment. Currently, there are two kinds of existing approaches of web services selection: (a) one is the web services selection algorithm based on genetic algorithm and fuzzy logic (shortly called GAFLSS) (Hei-Chia, Chang-Shing, & Tsung-Hsien, 2007;Karacapilidis et al, 2006), where genetic algorithm is adapted to learn user preferences and fuzzy logic is applied for making decisions; another is the web services selection algorithm based on trust-mechanism (shortly called TMSS) (Marco & Alberto, 1992;Yuliang, Guang-an, Liang, & Baile, 2006), where collected and calculated reputation values of web services are used to guide user selecting the optimum web service candidates. The system performance comparison the service selection system without neural network control (including TMSS and GAFLSS) with the system with neural network control (namely ANNSS) is shown in Fig.…”

Section: Results and Performance Analysismentioning

confidence: 99%

See 1 more Smart Citation

A novel intelligent service selection algorithm and application for ubiquitous web services environment

Cai

Lü

et al. 2009

Expert Systems with Applications

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Section: Results and Performance Analysismentioning

confidence: 99%

“…So we expand the traditional definition of service (Christensen, Curbera, Meredith, & Weerawarana, 2001;Feng, Jian, & Wei, 2003;Karacapilidis, Lazanas, Megalokonomos, & Moraitis, 2006) to a new service definition by adding new items to service definition for ubiquitous computing environment.…”

Section: Definition Of Servicementioning

confidence: 99%

A novel intelligent service selection algorithm and application for ubiquitous web services environment

Cai

Lü

et al. 2009

Expert Systems with Applications

View full text Add to dashboard Cite

“…As well as Lemer (2007) [11] described research conducted to develop a knowledge-based expert system decision-support tool for recommending speed limits in speed zones on highways and local roads, which are considered credible and enforceable. Particularly interesting is A. Lazans, N. Karacapilidis and Y. Pirovolakis (2006) [12] that integrated recommendation technique, which combines the advantages of collaborative filtering and knowledge based recommendation in a web-based platform as well as N. Karacapilidis (2005) [13] that developed web-based on the cooperate of customer, carrier and broker that act as intermediate party.…”

Section: Literature Reviewmentioning

confidence: 99%

Intelligent System for Transportation Mode Selection in ASEAN Countries

Janthongpan¹,

Rattanawong²,

Suthikarnnarunai³

2016

TOCIEJ

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Association of Southeast Asian Nations: ASEAN is an organization of ten countries in Southeast Asia consisting of Indonesia, Malaysia, the Philippines, Singapore, Brunei, Myanmar, Cambodia, Laos, Vietnam and Thailand. One of the major purposes of Asean is to create the Asean Economic Community: AEC as an economic organization. The mission of the AEC is to develop a single market and develop production base to be stable prosperous, highly competitive and economically, integrated with effective facilitation for trade and investment including a free flow of goods, services, investment, skilled labors and capital . This paper focuses on investigating the constraint within the three major modes of transportation (Air Sea and Truck) and reviewing the major factor influenced mode selection of the trading organization in Asean countries. Whilst constraints and complexities exist particularly within different countries, products values, lead time, a lack of knowledge on the condition of each transportation mode of the Small and Medium Enterprise (SME). At the time for those requirements can result in business limitation and restrictions. The results of research will lead to the design of an intelligent transportation system program that will not only illustrate solution for the trading organization in Asean countries but also provide variable costing and accurate transit time as management tools for users.

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“…It implements the resources registry and discovery mechanism, and develops from web services to grid services, which implement the dynamic resources discovery [15,30,31]. Grid computing has many excellent advantages, with a more advanced resources sharing model than the ordinary distributed resources sharing model [8,18]. In this paper, we adopt its resources sharing method to serve our RSIDP system and easily share our resources.…”

Section: Grid Computing and Web Services Technologymentioning

confidence: 99%