4,320 research outputs found
Induced aggregation operators in decision making with the Dempster-Shafer belief structure
No full textWe study the induced aggregation operators. The analysis begins with a revision of some basic concepts such as the induced ordered weighted averaging (IOWA) operator and the induced ordered weighted geometric (IOWG) operator. We then analyze the problem of decision making with Dempster-Shafer theory of evidence. We suggest the use of induced aggregation operators in decision making with Dempster-Shafer theory. We focus on the aggregation step and examine some of its main properties, including the distinction between descending and ascending orders and different families of induced operators. Finally, we present an illustrative example in which the results obtained using different types of aggregation operators can be seen.aggregation operators, dempster-shafer belief structure, uncertainty, iowa operator, decision making
Supplemental Material for Martchenko, Chikhi, and Shafer, 2020
No full textSupplemental Material for Martchenko, Chikhi, and Shafer, 202
Market consistent bid-ask option pricing under Dempster-Shafer uncertainty
No full textWe refer to the discrete-time market model under ambiguity introduced in [Cinfrignini, A., Petturiti, D. and Vantaggi, B., Dynamic bid–ask pricing under Dempster-Shafer uncertainty. J. Math. Econ., 2023a, 107, 102871], formed by a frictionless risk-free bond and a non-dividend paying stock with bid-ask spread. For a European derivative, we generalize the classical binomial pricing formula by allowing for bid-ask prices and investigate the properties of the ensuing replicating strategies. Next, for an American derivative, we propose a backward bid-ask pricing procedure and prove that the resulting discounted price processes are the bid-ask Choquet-Snell envelopes of the discounted payoff process, respectively. Moreover, for an American call option, we prove a generalization of the well-known Merton's theorem holding for both the bid and the ask price processes. Finally, we introduce a market consistent calibration procedure and show the use of the calibrated model in bid-ask option pricing
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
Rating the Significance of Detected Network Events
No full textExisting anomaly detection systems do not reliably produce accurate severity ratings for detected network events, which results in network operators wasting a large amount of time and effort in investigating false alarms. This project investigates the use of data fusion to combine evidence from multiple anomaly detection methods to produce a consistent and accurate representation of the severity of a network event. Four new detection methods were added to Netevmon, a network anomaly detection framework, and ground truth was collected from a latency training dataset to calculate the set of probabilities required for each of the five data fusion methods chosen for testing. The evaluation was performed against a second test dataset containing manually assigned severity scores for each event and the significance ratings produced by the fusion methods were compared against the assigned severity score to determine the accuracy of each data fusion method.
The results of the evaluation showed that none of the data fusion methods achieved a desirable level of accuracy for practical deployment. However, Dempster-Shafer was the most promising of the fusion methods investigated due to correctly classifying more significant events than the other methods, albeit with a slightly higher false alarm rate. We conclude by suggesting some possible options for improving the accuracy of Dempster-Shafer that could be investigated as part of future work
Jane Shepherd (Hobson) with Ted Shafer, Dec. 10, 1955
No full textJane B. Shepherd, and Ted Shafer, Dec. 10, 1955 b&w.https://mds.marshall.edu/jane_shepherd_hobson/1027/thumbnail.jp
Carlton Shafer, Alumnus and New Market veteran, ca. 1890
No full textCarlton Shafer, Class of 1864 & New Market cadet. He served as cadet captain, B Compan
Market consistent bid-ask option pricing under Dempster-Shafer uncertainty
No full textWe refer to the discrete-time market model under ambiguity introduced in [Cinfrignini, A., Petturiti, D. and Vantaggi, B., Dynamic bid-ask pricing under Dempster-Shafer uncertainty. J. Math. Econ., 2023a, 107, 102871], formed by a frictionless risk-free bond and a non-dividend paying stock with bid-ask spread. For a European derivative, we generalize the classical binomial pricing formula by allowing for bid-ask prices and investigate the properties of the ensuing replicating strategies. Next, for an American derivative, we propose a backward bid-ask pricing procedure and prove that the resulting discounted price processes are the bid-ask Choquet-Snell envelopes of the discounted payoff process, respectively. Moreover, for an American call option, we prove a generalization of the well-known Merton's theorem [Merton, R.C., Theory of rational option pricing. Bell J. Econ. Manage. Sci., 1973, 4, 141-183] holding for both the bid and the ask price processes. Finally, we introduce a market consistent calibration procedure and show the use of the calibrated model in bid-ask option pricing
Dynamic bid–ask pricing under Dempster-Shafer uncertainty
No full textWe deal with the problem of pricing in a multi-period binomial market model, allowing for frictions in the form of bid–ask spreads. We introduce and characterize time-homogeneous Markov multiplicative binomial processes under Dempster-Shafer uncertainty together with the induced conditional Choquet expectation operator. Given a market formed by a frictionless risk-free bond and a non-dividend paying stock with frictions, we prove the existence of an equivalent one-step Choquet martingale belief function. We then propose a dynamic Choquet pricing rule with bid–ask spreads showing that the discounted lower price process of a European derivative contract on the stock is a Choquet super-martingale. We finally provide a normative justification in terms of a dynamic generalized no-arbitrage condition relying on the notion of partially resolving uncertainty due to Jaffray
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