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Many uncertainty factors exist in the process of building the student model in Intelligent CAI. This article adopts Bayesian Network to deal with these uncertainties. The paper emphatically analyzes the constructive process of Bayesian network in the student model and optimize the Bayesian Network by applying a algorithm to search cluster nodes, which improves the adaptability of the Intelligent CAI...
In this paper, we propose a novel, effective and efficient probabilistic pruning criterion for probabilistic similarity queries on uncertain data. Our approach supports a general uncertainty model using continuous probabilistic density functions to describe the (possibly correlated) uncertain attributes of objects. In a nutshell, the problem to be solved is to compute the PDF of the random variable...
Subject matter expert assessments can include both assignment and linguistic uncertainty. This paper examines assessments containing linguistic uncertainty associated with a qualitative description of a specific state of interest and the assignment uncertainty associated with assigning the state to a particular qualitative value. A Bayesian approach is examined to simultaneously quantify both assignment...
Qualitative reasoning makes use of qualitative assessments provided by subject matter experts to model factors such as security risk. Confidence in a result is important and useful when comparing competing results. Quantifying the confidence in an evidential reasoning result must be consistent and based on the available information. A novel method is proposed to relate confidence to the available...
In the USA, in the last decade, standards have been adapted for each grade level. These standards are annually checked by state-wide tests. The results of these tests often determine the school's funding and even the school's future existence. Due to this importance, a large amount of time is spent on teaching to the tests. Most teachers believe that this testing approach is detrimental to student...
In trustable networks, the process that nodes submit service satisfaction degree to form reputation of service provider has uncertainties of fuzziness and randomness. A cloud theory based model is proposed for the computation of node reputation. Weights of service satisfaction degrees in the model include an attenuation coefficient part and a certainty degree part. The certainty degree part is obtained...
In many application areas, we encounter heavy-tail distributions - for example, such distributions are ubiquitous in financial applications. These distributions are often described by Pareto law. There exist techniques for estimating the parameters of such corresponding Pareto distributions based on the sample x1, ..., xn. In practice, we often only know the values xi with interval (or, more generally,...
The process of human's blink expressing deep information of mind has uncertainties of fuzziness and randomness. A cloud theory-based method is proposed to realize uncertainty control of virtual human's blink. Eyes' maximal open angle cloud and blink interval cloud are designed. A cloud-based blink control algorithm is proposed. Results of comparing it with certainty method show that the proposed algorithm...
Accurate situational assessment is key to any decision making especially crucial in military command and control, air traffic control, and complex system decision making. Endsley describes three dependent levels of situational awareness, (1) perception, (2) understanding, and (3) projection. This research is focused on Endsley's second-level situational awareness (understanding) as it applies to service-oriented...
This paper describes a methodology for incorporating human observations into a hard+soft information fusion process for counterinsurgency intelligence analysis. The goal of incorporating human observations into the information fusion process is important as it extends the ability of the fusion algorithms to associate and merge disparate pieces of information by allowing for information collected from...
In this paper, an indirect adaptive fuzzy sliding mode control approach is proposed for anti-swing and position control of overhead cranes taking into account the uncertainty of load mass. The approach employs a sliding surface that couples the trolley motion and load swing dynamics to regulate the trolley position and guarantee the stability of swing dynamics, and applies the fuzzy logic systems...
There are many uncertainties during logistics operation. It's the best way for coping with influences of uncertainties and increasing the efficiency and effect of logistics system to maintain proper flexibility. Evaluation on flexibility of logistics system is precondition and key for building and holding the flexibility of logistics system. In this paper, the flexible indexes of three stages including...
Aiming at the invalidation of Dempster's rule for combining belief functions with high conflict, this paper proposes a new combination rule. Firstly, the limitation of classical conflict measure is pointed out, and improved measure for degree of conflict is presented and proved. Based on this improved measure, a new combination rule which is composed of three steps is proposed. The first step is to...
We have recently introduced new generative semi supervised mixtures with more fine-grained class label generation mechanisms than previous methods. Our models combine advantages of semi supervised mixtures, which achieve label extrapolation over a component, and nearest-neighbor (NN)/nearest-prototype (NP) classification, which achieves accurate classification in the vicinity of labeled samples. Our...
This paper applies the theory of information space for a study of dialogue management in major approaches, ranging from the classical approach based upon finite state machine to the most recent approach using partially observable Markov decision process (POMDP). After identifying the problems of current approaches, this paper proposes a modified approach of POMDP-based dialogue management. This new...
Cooperative spectrum sensing for cognitive radio is recently being studied to minimize uncertainty in primary user detection. In order to improve the detection probability under a sustainable false alarm probability, a reliable scheme for cooperative spectrum sensing based on double threshold energy detection and Dempster-Shafer (D-S) theory is proposed in this paper. In the algorithm, the double...
In this paper the Dempster-Shafer theory of evidence is utilized in comprehensive assessment of the reliability enhancement testing (RET). The basic concept of the D-S theory and the rule of evidence-combination are introduced. Moreover, the approach to the assessment of the RET utilizing the D-S theory of evidence is presented. Firstly a recognition frame for all possible effects of RET programs...
We consider a stochastic simulation with correlated inputs represented by a multivariate normal distribution. The objectives are to (i) account for parameter uncertainty (i.e., the uncertainty around the multivariate normal distribution parameters estimated from finite historical input data) in the mean performance estimate and the confidence interval of the simulation; and (ii) decompose the total...
This paper studies robust knapsack problems, for which solutions are, up to a certain point, immune to data uncertainty. We complement the works found in the literature where uncertainty affects only the profits or only the weights of the items by studying the complexity and approximation of the general setting with uncertainty regarding both the profits and the weights, for multiple objective functions...
This paper proposes an approach for clustering belief functions. The approach is composed of agglomerative clustering and how to determine the cluster number. The former one is achieved by taking belief distance as dissimilarity measure between two belief functions and selecting complete-link algorithm to measure the dissimilarity between two clusters. The latter one is completed by utilizing metaconflict...
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