311 research outputs found
Modelling trip distribution with fuzzy and genetic fuzzy systems
No full textThis paper explores the potential capabilities of fuzzy and genetic fuzzy system approaches in urban trip distribution modelling with some new features. First, a simple fuzzy rule-based system (FRBS) and a novel genetic fuzzy rule-based system [GFRBS: a fuzzy system improved by a knowledge base learning process with genetic algorithms (GAs)] are designed to model intra-city passenger flows for Istanbul. Subsequently, their accuracy, applicability and generalizability characteristics are evaluated against the well-known gravity- and neural network (NN)-based trip distribution models. The overall results show that: traditional doubly constrained gravity models are still simple and efficient; NNs may not show expected performance when they are forced to satisfy trip constraints; simply-designed FRBSs, learning from observations and expertise, are both efficient and interpretable even if the data are large and noisy; and use of GAs in fuzzy rule-based learning considerably increases modelling performance, although it brings additional computation cost
A genetic-fuzzy system modeling of trip distribution
No full textThesis (Doctoral)--Izmir Institute of Technology, City and Regional Planning, Izmir, 2010Includes bibliographical references (leaves: 89-96)Text in English; Abstract: Turkish and Englishix, 141 leavesTrip distribution modelling is one of the most active parts of travel demand analysis. In recent years, use of soft computing techniques has introduced effective modelling approaches to the trip distribution problem. Fuzzy Rule-Based System (FRBS) and Genetic Fuzzy Rule-Based System (GFRBS: fuzzy system improved by a knowledge base learning process with genetic algorithms) modelling of trip distribution are two of these new approaches. However, much of the potential of these techniques has not been demonstrated so far. The present study explores the potential capabilities of these approaches in an urban trip distribution problem with some new features. For this purpose, a simple FRBS and a novel GFRBS were designed to model Istanbul intra-city passenger flows. Subsequently, their accuracy, applicability, and generalizability characteristics were evaluated against the well-known gravity and neural networks based trip distribution models. The overall results show that: i) traditional doubly constrained gravity models are still simple and efficient; ii) neural networks may not show expected performance when they are forced to satisfy production-attraction constraints; iii) simply-designed FRBSs, learning from observations and expertise, are both interpretable and efficient in forecasting trip interchanges even if the data is large and noisy; and iv) use of genetic algorithms in fuzzy rule base learning considerably increases modelling performance, although it brings additional computation costs
A Genetic-Fuzzy System Modeling of Trip Distribution
No full textTrip distribution modelling is one of the most active parts of travel demand analysis. In recent years, use of soft computing techniques has introduced effective modelling approaches to the trip distribution problem. Fuzzy Rule-Based System (FRBS) and Genetic Fuzzy Rule-Based System (GFRBS: fuzzy system improved by a knowledge base learning process with genetic algorithms) modelling of trip distribution are two of these new approaches. However, much of the potential of these techniques has not been demonstrated so far. The present study explores the potential capabilities of these approaches in an urban trip distribution problem with some new features. For this purpose, a simple FRBS and a novel GFRBS were designed to model Istanbul intra-city passenger flows. Subsequently, their accuracy, applicability, and generalizability characteristics were evaluated against the well-known gravity and neural networks based trip distribution models. The overall results show that: i) traditional doubly constrained gravity models are still simple and efficient; ii) neural networks may not show expected performance when they are forced to satisfy production-attraction constraints; iii) simply-designed FRBSs, learning from observations and expertise, are both interpretable and efficient in forecasting trip interchanges even if the data is large and noisy; and iv) use of genetic algorithms in fuzzy rule base learning considerably increases modelling performance, although it brings additional computation costs
Modeling Retail Structural Change of Izmir Using a Dynamic Spatial Interaction Model
No full textRetailing, one of the most important sectors in all developed economies, has always been the prominent element of urban morphology, and evolves as the city evolves and expands. The last two decades have witnessed considerable changes in retailing throughout developed countries such as, the emergence of new store formats, the increased prevalence of retail chains, the development of out-of-town and edge-of-town retail parks accompanying with the changing conditions of globalized world. Since the sector has undergone major changes in scale, organization, and geography, the urban spaces have been the scene of these ongoing changes.Under the influence of global economic transformation after 80's, there have also been dramatic changes in retail industry and retail environment in Turkey. Despite the sector in Turkey is still dominated by large number of small, independent, and single location retailers, market share and spatial prevalence of large-scale retailers' have been increasing rapidly. Especially in major cities of the country, both international and domestic retail chains have been imposing a transformation and restructuring the urban retail environment. Among all the areas of retailing, food retailing stands out as having seen the most profound changes in Turkey. With respect of this, the study explores the spatial consequences of the structural change of food retailing system in Izmir. The prevalence of large-scale food retailers such as hypermarkets and supermarkets has negative effects on the survival of many small-independent retailers. The increasing competition has led to a changing retail structure with the dominance of organized retailers where the number of small-scale retailers and their total size are decreasing. As the trends continue, this will have important and unpredictable spatial influences on urban retail environment and urban geography. Obviously, there is a strong need for a study exploring changes in retail structure and its influences in urban spaces so that policy makers and planners could take into consideration and help restructuring of this transformation process better. For this purpose, the study explores if the ongoing restructuring process of retailing and its possible geographical consequences can be modeled using a dynamic spatial interaction model as a device to be able to predict the future transformations
Modeling retail structural change of İzmir using a dynamic spatial interaction model
No full textThesis (Master)--Izmir Institute of Technology, City and Regional Planning, Izmir, 2004Includes bibliographical references (leaves: 104)Text in English; Abstract: Turkish and Englishvii, 106 leavesRetailing, one of the most important sectors in all developed economies, has always been the prominent element of urban morphology, and evolves as the city evolves and expands. The last two decades have witnessed considerable changes in retailing throughout developed countries such as, the emergence of new store formats, the increased prevalence of retail chains, the development of out-of-town and edge-of-town retail parks accompanying with the changing conditions of globalized world. Since the sector has undergone major changes in scale, organization, and geography, the urban spaces have been the scene of these ongoing changes.Under the influence of global economic transformation after 80's, there have also been dramatic changes in retail industry and retail environment in Turkey. Despite the sector in Turkey is still dominated by large number of small, independent, and single location retailers, market share and spatial prevalence of large-scale retailers' have been increasing rapidly. Especially in major cities of the country, both international and domestic retail chains have been imposing a transformation and restructuring the urban retail environment. Among all the areas of retailing, food retailing stands out as having seen the most profound changes in Turkey. With respect of this, the study explores the spatial consequences of the structural change of food retailing system in Izmir. The prevalence of large-scale food retailers such as hypermarkets and supermarkets has negative effects on the survival of many small-independent retailers. The increasing competition has led to a changing retail structure with the dominance of organized retailers where the number of small-scale retailers and their total size are decreasing. As the trends continue, this will have important and unpredictable spatial influences on urban retail environment and urban geography. Obviously, there is a strong need for a study exploring changes in retail structure and its influences in urban spaces so that policy makers and planners could take into consideration and help restructuring of this transformation process better. For this purpose, the study explores if the ongoing restructuring process of retailing and its possible geographical consequences can be modeled using a dynamic spatial interaction model as a device to be able to predict the future transformations
A genetic-fuzzy system modeling of trip distribution
No full textThesis (Doctoral)--Izmir Institute of Technology, City and Regional Planning, Izmir, 2010Includes bibliographical references (leaves: 89-96)Text in English; Abstract: Turkish and Englishix, 141 leavesTrip distribution modelling is one of the most active parts of travel demand analysis. In recent years, use of soft computing techniques has introduced effective modelling approaches to the trip distribution problem. Fuzzy Rule-Based System (FRBS) and Genetic Fuzzy Rule-Based System (GFRBS: fuzzy system improved by a knowledge base learning process with genetic algorithms) modelling of trip distribution are two of these new approaches. However, much of the potential of these techniques has not been demonstrated so far. The present study explores the potential capabilities of these approaches in an urban trip distribution problem with some new features. For this purpose, a simple FRBS and a novel GFRBS were designed to model Istanbul intra-city passenger flows. Subsequently, their accuracy, applicability, and generalizability characteristics were evaluated against the well-known gravity and neural networks based trip distribution models. The overall results show that: i) traditional doubly constrained gravity models are still simple and efficient; ii) neural networks may not show expected performance when they are forced to satisfy production-attraction constraints; iii) simply-designed FRBSs, learning from observations and expertise, are both interpretable and efficient in forecasting trip interchanges even if the data is large and noisy; and iv) use of genetic algorithms in fuzzy rule base learning considerably increases modelling performance, although it brings additional computation costs
Modelling trip distribution with fuzzy and genetic fuzzy systems
No full textThis paper explores the potential capabilities of fuzzy and genetic fuzzy system approaches in urban trip distribution modelling with some new features. First, a simple fuzzy rule-based system (FRBS) and a novel genetic fuzzy rule-based system [GFRBS: a fuzzy system improved by a knowledge base learning process with genetic algorithms (GAs)] are designed to model intra-city passenger flows for Istanbul. Subsequently, their accuracy, applicability and generalizability characteristics are evaluated against the well-known gravity- and neural network (NN)-based trip distribution models. The overall results show that: traditional doubly constrained gravity models are still simple and efficient; NNs may not show expected performance when they are forced to satisfy trip constraints; simply-designed FRBSs, learning from observations and expertise, are both efficient and interpretable even if the data are large and noisy; and use of GAs in fuzzy rule-based learning considerably increases modelling performance, although it brings additional computation cost.JRC.J.1 - Economics of Climate Change, Energy and Transpor
The Development of Western-Type Large-Scale Consumption Areas in Turkey and Legal and Structural Regulation Efforts in Urban Retail Environments*
No full textThe retail sector has been experiencing a rapid and continuouschange worldwide. There have also been profoundchanges in Turkey, especially after the 1980s. Both the retailsector and the urban retail environments have been alteredradically. One of the most significant indicators of this changeis the proliferation of western-type large-scale retail developments.Past experiences in developed countries have shownthat the uncontrolled development of large-scale retail areasresults in some undesired socioeconomic and physical outcomes,such as decline in the cultural and commercial activitiesof city centers, damage in existing retail workforce structure,and change in local retail hierarchy, nearby land uses,traffic loads and original architectural identity. Many countrieshave put into practice restrictive and regulatory policiesto prevent these negative effects. As similar transformationshave also been realized in Turkish retail environments, manyinstitutions think that similar legal regulations must be implementedin Turkey as well. The present study investigates theongoing retail change within the Turkish context, explores thelegal and structural regulatory policies of the Organizationfor Economic Co-operation and Development (OECD) countries,and critically discusses the appropriate retail regulationpolicies for Turkey
A framework to analyze the vulnerability of European road networks due to Sea-Level Rise (SLR) and sea storm surges
No full textThis study proposes a framework to explore the concepts of exposure, vulnerability and
connectivity in EU road network and to assess the potential transportation infrastructure
sensitivities towards Sea-Level Rise (SLR) and storm surges. The magnitude and significance
of impacts were determined and knowledge of network robustness was built up
based on existing climate data and on future trends. Various spatial databases were integrated
and a four-stage transport model was used to explore the likely impacts of network
degradation. The pattern of the network was assessed via both node- and link-based measurements,
where different road databases, namely TRANS-TOOLS and Tele Atlas/TomTom,
were employed in order to analyze the impact of spatial resolution within network connectivity
analyses. This general framework developed for European Union, was tested on a
specific and articulated case study area; namely, the north-east coastal region of Spain.
The research conducted, yielded useful methods for the analysis of network vulnerability,
where impacts are more significant in regional accessibility patterns. Accessibility indicators
at the regional level changed drastically, with some regions showing up to a 26%
decrease. According to the results of network connectivity indicators, the changes in network
topology have reduced the number of alternative routes and placed more pressure
on the transport system. The implementation of this framework and quantitative assessment
methodologies outlined in this paper could be employed to assist policy makers to
recognize the opportunities that may arise or diminish the adverse effects.JRC.J.1 - Economics of Climate Change, Energy and Transpor
Accessibility and territorial cohesion: ex post analysis of Cohesion Fund infrastructure projects
No full text- …
