Browsing by Author "Wen, YH"

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Airline flight frequency determination in response to competitive interactions using fuzzy logic
(2005-12-01)
Hsu, CI
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Wen, YH
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This study determines the flight frequencies on an airline network in response to anticipated airline competitive interactions using fuzzy logic. It is expressed as an optimization problem to be solved in the medium-term airline network-planning phase, and it deals with tactical decisions made one season or one year in advance. The proposed model includes three submodels-an airline market share model, a flight-frequency programming model, and a fuzzy-logic-based competitive interaction model. Flight frequencies on an airline network with competitive interactions are analyzed by combining these three submodels. A case study, demonstrating the feasibility of applying the proposed model, confirms that the competitive interactions will converge. The results of this study confirm the accuracy of the proposed model and their flexibility of the decision-making involved in determining flight frequencies on an airline network in competitive and uncertain environments. (c) 2005 Elsevier Ltd. All rights reserved.
Application of Grey theory and multiobjective programming towards airline network design
(2000-11-16)
Hsu, CI
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Wen, YH
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
Airline network design encompasses decisions on an airline network shape and route flight frequencies. Related investigations handle the trade-off between enhancing passengers' service levels and lowering the airline's operating costs by applying deterministic optimization methods. In contrast with other conventional methods, Grey theory is a feasible mathematical device capable of forecasting airline traffic with minimum data and resolving problems containing uncertainty and indetermination. In the light of these developments, this study develops a series of models capable of forecasting airline city-pair passenger traffic, designing a network of airline routes and determining Eight frequencies on individual routes by applying Grey theory and multiobjective programming. A case study demonstrates the feasibility of applying the proposed models. Results in this study not only confirm the practical nature of the preposed models, but also their ability to provide high flexibility in decision making for airlines. (C) 2000 Elsevier Science B.V. All rights reserved.
Determining flight frequencies on an airline network with demand-supply interactions
(2003-11-01)
Hsu, CI
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Wen, YH
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This paper determines flight frequencies on an airline network with demand-supply interactions between passenger demand and flight frequencies. The model consists of two submodels, a passenger airline flight choice model and an airline flight frequency programming model. The demand-supply interactions relevant to determining flight frequency on an airline's network are analyzed by integrating these two submodels. The necessary condition for the convergence of the demand-supply interaction is discussed. An example demonstrates the feasibility of applying the proposed models. The results are more accurate than those obtained without considering demand-supply interactions, and the models provide ways to consider demand-supply interactions well in advance to determine flight frequencies on an airline network. (C) 2003 Elsevier Ltd. All rights reserved.
Forecasting Trans-Pacific air traffic by grey model
(1999)
Hsu, CI
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Wen, YH
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
The rapid economic growth of Asia-Pacific countries continues to result in faster travel growth in the Trans-Pacific air passenger market. Grey theory is used to develop time series GM(1,1) models for forecasting: total passenger and 10 country-pair passenger traffic flows. The GM(1,1) models are shown to yield better accurate prediction results than ARIMA and multiple regression models. The results indicate that the total number of air passengers for Trans-Pacific market will increase at an average annual growth rate of approximately 11% up to year 2000.
Fuzzy data mining and grey recurrent neural network forecasting for traffic information systems
(2005)
Wen, YH
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Lee, TT
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交大名義發表
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National Chiao Tung University
This study presents a systematic process combining trajfic forecasting and data mining models for traffic information systems. Fuzzy c-means clustering model was developed for mining traffic flow-speed-occupancy relationships, then to extrapolate traffic information. The hybrid grey-based recurrent neural network (G-RNN) was developed for traffic parameter forecasting. G-RNN integrates grey modeling into recurrent neural networks that is capable of dealing with both randomness and spatial-temporal properties in trajfic data implicitly. Field data from Taiwan national freeway was used as an example for testing the proposed models. Study results were shown that the G-RNN model is capable of predicting traffic parameters with a high degree of accuracy. The application presents three clusters built from data and recognized three types of traffic conditions. Study results also showed feasibility of the method for advanced traffic information systems.
Hybrid models toward traffic detector data treatment and data fusion
(2005)
Wen, YH
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Lee, TT
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Cho, HJ
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電控工程研究所
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Institute of Electrical and Control Engineering
This paper develops a data processing with hybrid models toward data treatment and data fusion for traffic detector data on freeways. Hybrid grey-theory-based pseudo-nearest-neighbor method and grey time-series model are developed to recover spatial and temporal data failures. Both spatial and temporal patterns of traffic data are also considered in travel time data fusion. Two travel time data fusion models are presented using a speed-based link travel time extrapolation model for analytical travel time estimation and a recurrent neural network with grey-models for real-time travel time prediction. Field data from the Taiwan national freeway no.1 were used as a case study for testing the proposed models. Study results shown that the data treatment models for faulty data recovery were accurate. The data fusion models were capable of accurately predicting travel times. The results indicated that the proposed hybrid data processing approaches can ensure the accuracy of travel time estimation with incomplete data sets.
Improved grey prediction models for the trans-Pacific air passenger market
(1998-01-01)
Hsu, CI
;
Wen, YH
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
The rapid economic growth of Asia-Pacific countries continues to result in faster travel growth in the trans-Pacific air passenger market. Grey theory is used to develop time series GM(1,1) models for forecasting total passenger and 10 country-pair passenger traffic flows in this market. The accumulated generating operation (AGO) is one of the most important characteristics of grey theory, and its main purpose is to reduce the randomness of data. The original GM(1,1) models are improved by using residual modifications with Markov-chain sign estimations. These models are shown to be more reliable by posterior checks and to yield more accurate prediction results than ARIMA and multiple regression models. The results indicate that the total number of air passengers in the trans-Pacific market will increase at an average annual growth rate of approximately 11% up to the year 2000.
Improved grey prediction models for the trans-Pacific air passenger market
(1998-01-01)
Hsu, CI
;
Wen, YH
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
The rapid economic growth of Asia-Pacific countries continues to result in faster travel growth in the trans-Pacific air passenger market. Grey theory is used to develop time series GM(1,1) models for forecasting total passenger and 10 country-pair passenger traffic flows in this market. The accumulated generating operation (AGO) is one of the most important characteristics of grey theory, and its main purpose is to reduce the randomness of data. The original GM(1,1) models are improved by using residual modifications with Markov-chain sign estimations. These models are shown to be more reliable by posterior checks and to yield more accurate prediction results than ARIMA and multiple regression models. The results indicate that the total number of air passengers in the trans-Pacific market will increase at an average annual growth rate of approximately 11% up to the year 2000.
Missing data treatment on travel time estimation for ATIS
(2003)
Jon, YJ
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Wen, YH
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Lee, TT
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Cho, HJ
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統計學研究所
This study proposes a missing data recovery method based on grey-relational nearest-neighbor substitution techniques for treating with missing data from dual-loop detectors in estimating travel time and evaluates the effects of the missing data on travel-time estimation performance. Field data from the Taiwan national freeway no. I were used as a case study for testing the proposed model. Study results shown that the travel time estimation with missing data recovery was accurate even the missing data rate zip to 33%. It is indicated that the proposed missing data treatment model can ensure the accuracy of travel time estimation with incomplete data sets.
Reliability evaluation for airline network design in response to fluctuation in passenger demand
(2002-06-01)
Hsu, CI
;
Wen, YH
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This study develops a reliability evaluation method for airline network design. Reliability evaluation in the airline network design phase is considered herein as a post-design task. A series of models for determining flight frequencies on individual routes, evaluating reliability under normal/abnormal demand fluctuations, and providing a priori adjustment of flight frequencies are presented. A case study demonstrating the feasibility of applying the proposed models is provided. Study results not only suggest a post evaluation and adjustment method for airline network design in response to future uncertain fluctuation in passenger demand, but also provide ways to improve flexibility in airline flight frequency decision-making. (C) 2002 Elsevier Science Ltd. All rights reserved.