نتایج جستجو برای: modelling

تعداد نتایج: 162298  

Journal: :نقش جهان - مطالعات نظری و فناوری های نوین معماری و شهرسازی 0
farbod abed abed master of architecture, tehran university, kish international campus, tehran, iran alireza einifar associate professor in university college of fine arts university of tehran, ph.d. in the same field from university of new south wales, sydney, australia

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Journal: :international journal of business and development studies 0

this study analyses the concept of cost functions for semi-automated straddle carrier (sc), rubber tyred gantry (rtg) and automated rail mounted gantry (rmg) container yard operating cranes. it develops a generic cost based model for a pair-wise comparison, analysis and evaluation of economic efficiency and effectiveness of container yard equipment to be used for decision-making by terminal pla...

Delineation of oxide and sulfide zones in mineral deposits, especially in gold deposits, is one of the most essential steps in an exploration project that has been traditionally carried out using the drilling results. Since in most mineral exploration projects there is a limited drilling dataset, application of geophysical data can reduce the error in delineation of the sulfide and oxide zones....

Journal: تعلیم و تربیت 2020
N. Yaaftiyaan, Ph.D., S. Ahmadi,

Modelling is emphasized heavily in the national math curriculum, yet the extent to which this concept is covered in the math textbooks is, while of great importance, unknown. To discover the extent to which this issue, and real problems in general, are covered in the 10th grade math textbooks, the content of the textbook for the ‘theoretical’ (“nazari”) branch was analyzed. In doing so, the vie...

In recent years, artificial neural networks (ANNs) have become one of the most promising tools in order to model complex hydrological processes such as the rainfall-runoff process. In many studies, ANNs have demonstrated superior results compared to alternative methods. ANNs are able to map underlying relationship between input and output data without prior understanding of the process under in...

‎This paper presents a new mixture model via considering the univariate skew Laplace distribution‎. ‎The new model can handle both heavy tails and skewness and is multimodal‎. ‎Describing some properties of the proposed model‎, ‎we present a feasible EM algorithm for iteratively‎ ‎computing maximum likelihood estimates‎. ‎We also derive the observ...

Journal: :international journal of transportation engineereing 2014
krishna saw b. k. katti g. joshi

rapid urban growth is resulting into increase in travel demand and private vehicle ownership in urban areas. in the present scenario the existing infrastructure has failed to match the demand that leads to traffic congestion, vehicular pollution and accidents. with traffic congestion augmentation on the road, delay of commuters has increased and reliability of road network has decreased. four s...

2003
Eric Horvitz Susan Dumais Paul Koch

We describe the construction and use of predictive models that provide inferences about the likelihood that users will consider particular events to be memorable landmarks in time. We discuss experiments and present integration of the models of event memorability into prototype file browsing tools. Finally, we discuss ongoing research and future directions for using predictive models of human m...

1999
Mark Voorneveld

This paper considers random games, in which the actual game being played | its player set, the action spaces of the involved players, and their preferences | is determined by a stochastic state of nature. To capture the uncertainty at the planning stage whether or not a certain action choice is feasible, maximum likelihood equilibria are introduced: strategy pro ̄les that lead to equilibrium pla...

2013
David DeVault David R. Traum

This paper explores the relationship between explicit and predictive models of incremental speech understanding in a dialogue system that supports a finite set of user utterance meanings. We present a method that enables the approximation of explicit understanding using information implicit in a predictive understanding model for the same domain. We show promising performance for this method in...

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