174,205 research outputs found
Modeling Partially Reliable Information Sources: A General Approach Based on Dempster-Shafer Theory
No full textCombining testimonial reports from independent and partially reliable information sources is an important problem of uncertain reasoning. Within the framework of Dempster-Shafer theory, we propose a general model of partially reliable sources which includes several previously known results as special cases. The paper reproduces these results, gives a number of new insights, and thereby contributes to a better understanding of this important application of reasoning with uncertain and incomplete information.Articl
A learning Dempster-Shafer model for automated building detection
No full textThis paper presents a learning Dempster-Shafer model for the detection of buildings in aerial image and range data. The process of evidence assignment in the Dempster-Shafer method is implemented through membership functions in an adaptive network-based fuzzy inference system, where a back propagation learning rule is employed to tune the evidence assignment functions using training samples. The advantage of this method is that it incorporates our knowledge about various features that can be extracted from multi-source aerial data, and the evidence that these features provide for buildings and other objects in urban and suburban areas. Experimental results show that the proposed learning model improves the performance of the Dempster-Shafer classifier in detecting buildings in multi- source aerial data.Remote SensingAerospace Engineerin
Shafer - Edward C. Shafer (1886)
No full textHandwritten on back: ""Yours in 86. Ed. Clay Shafer. Burkittsville, MD. Pa College. June. 21. '86."
Sharon Shafer, Doctor of Musical Arts recital, voice, May 20, 1972
No full textDie Liebe auf dem Lande (Hiller, Johann Adam); Nonnelied (Bach, C. P. E.); Rastlose Liebe (Zelter, Carl Friedrich); Des Glockenthürmers Töchterlein, Op. 112a (Loewe, Carl); Frühlingslied, Op. 47, No. 3 (Mendelssohn, Felix); Three Songs, Op. 20 (Schubert, Franz); Five Greek Folk Songs (Ravel, Maurice); Night Songs (Shafer, Robert); There cam a wind like a bugle (Copland, Aaron); Heart, we will not forget him (Copland, Aaron); Dear March, come in! (Copland, Aaron); Sleep is supposed to be (Copland, Aaron); I felt a funeral in my brain (Copland, Aaron); Going to Heaven! (Copland, Aaron); The Chariot (Copland, Aaron). Instrumentation: piano; sopran
Photograph of entrance to Camp Shafer Butte, P-233 C-290
No full textPhotograph of entrance to spike camp P-233, C-290, Camp Shafer Butte, showing tents in a forest setting. Handwriting on back says: Shafer Butte IdahoP-233C-29
Data classification using the Dempster-Shafer method
No full textIn this paper, the Dempster-Shafer method is employed as the theoretical basis for creating data classification systems. Testing is carried out using three popular (multiple attribute) benchmark datasets that have two, three and four classes. In each case, a subset of
the available data is used for training to establish thresholds, limits or likelihoods of class membership for each attribute, and hence create mass functions that establish probability of class membership for each attribute of the test data. Classification of each data item
is achieved by combination of these probabilities via Dempster’s Rule of Combination. Results for the first two datasets show extremely high classification accuracy that is competitive with other popular methods. The third dataset is non-numerical and difficult to classify, but good results can be achieved provided the system and mass functions are designed carefully and the right attributes are chosen for combination. In all cases the Dempster-Shafer method provides comparable performance to other more popular algorithms, but the overhead of generating accurate mass functions increases the complexity with the addition of new attributes. Overall, the results suggest that the D-S approach provides a suitable framework for the design of classification systems and that automating the mass function design and calculation would increase the viability of the algorithm for complex classification problems
Correspondance. À propos du nationalisme
No full textShafer Boyd C., Godechot Jacques. Correspondance. À propos du nationalisme. In: Annales historiques de la Révolution française, n°220, 1975. pp. 329-333
Formulating partner selection criteria for agile supply chains: A Dempster-Shafer belief acceptability optimisation approach
No full textNational Natural Science Foundation of China [70921001]Today's more dynamic business environment increases the need for greater agility in supply chains, which increases both the importance and frequency of partner selection decision-making. Previous research has suggested that the application of the Dempster-Shafer and optimisation theories offers a way of solving this problem under conditions of resource constraints. This paper advances this approach by offering a simplified yet thorough, rigorous yet still practical method for formulating criteria to use in partner selection decision-making in agile supply chains. An empirical illustrative example is used to demonstrate the approach, obtain insights into its application and identify issues for future research. (C) 2010 Elsevier B.V. All rights reserved
Cadet John C. Shafer, Jr. Class of 1890
No full textCadet John Clements Shafer, Jr., Class of 1890. Part of the John P. Moorman Album, #0000270
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