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Daganzo (1977, 1979), Daganzo and Sheffi (1977), Sheffi (1985), and Sheffi and Daganzo (1980) have used one assumption about traveler behavior in developing estimation techniques for the stochastic route-choice problem and another assumption in predicting flows on networks by using the same model. In estimation, they calculate the congested travel costs of the network links from observed flows on the network, and the network is loaded based on these costs. In prediction, they follow their stochastic user-equilibrium assumption by which travelers evaluate costs using the mean of the observed flows (or equilibrium flows). The travel-cost coefficient obtained from the loading method systematically overestimates the true travel-cost coefficient from which the observed flow data (which must be used in loading) is generated. The estimates of the same coefficient, obtained in this paper, by constraining the estimation results to conform to the equilibrium conditions are unbiased, and only marginally less efficient (have larger standard deviations). The average percentage error and inefficiency of the link flow predictions based on the loading method increases as the level of congestion on the network rises. In contrast, the average percentage error of link flow predictions based on the equilibrium estimation method declines and their efficiency remains very high as the level of congestion on the network rises. 相似文献
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Alan T. Murray 《Geographical analysis》2021,53(1):13-18
Prompted by a series of panel sessions at a recent American Association of Geographers annual meeting entitled “A Globe‐Shaped Crystal Ball: The Next Fifty Years of Geographical Analysis,” participants were asked to speculate on the future of the journal, which of course has broader implications for spatial and geographic analytics. In what follows, I provide my thoughts on the journal as a reader, contributor, referee, and former editor of Geographical Analysis. The major points touched upon include the following. First, application to address substantive concerns will come to dominate the field. Second, the spatial data deluge will continue unabated, but will lead to important advances because of better detail and less abstraction of reality. Third, analytical methods will evolve specifically for big data. Fourth, the point‐and‐click revolution will result in ever more use of spatial analytics, but also will lend itself to greater and more widespread abuse of these methods. Fifth, addressing assumptions and theoretical foundations of long utilized approaches will revolutionize a new generation of spatial analytics. Sixth, geographic uncertainty and bias will be more than an afterthought, and methods will emerge to support meaningful analysis. Finally, spatial optimization will have increased prominence in fundamental analysis, particularly associated with establishing and evaluating significance. 相似文献
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It is shown that audience members actively select amongst available programmes on television. This selection is based upon the social role and situational characteristics of the viewer and it is also directly related to the reasons given by viewers for watching television.
Patterns of programme selection are related to three clusters of needs and reasons. The two most important of these are composed of needs relating to information and diversion. The least important cluster is concerned with the self and social contact.
Escape and diversion needs are satisfied by almost any programme; selection is minimal by those viewers expressing these needs. Information needs are best satisfied by news and other informational programmes, while social and self needs are best satisfied by quiz and variety programmes, popular drama and movies. 相似文献
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Alan T. Murray 《Geographical analysis》2018,50(3):207-222
Among the wide range of geographic analysis methods are service coverage models. These location analytic approaches have been invaluable for better understanding existing (and past) conditions, deriving creative plans, and developing policy for addressing associated societal problems. Increasingly sophisticated spatial information and better knowledge about interrelated mechanisms of process and behavior have made it possible to enhance coverage models, enabling more nuanced formalizations to be devised. This has proven both important and essential in many ways. Mathematical details associated with service coverage models are derived to highlight evolving capabilities. Empirical results are presented in order to illustrate the significance and substantive importance of advanced location analytics capabilities. 相似文献