Estimation of target behavior tendencies using dezert-smarandache theory

Tchamova, Albena; Semerdjiev, Tzvetan; Dezert, Jean

doi:10.1109/icif.2003.177394

Cited by 9 publications

(7 citation statements)

References 12 publications

(7 reference statements)

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“…It introduces a novel approach to information processing and our work is an offshoot of this idea. Each variable state obtained from the CTC fermentation process is considered as a frame of discernment, namely source evidence, in which three elementary propositions are defined, which constitute seven focal elements with union operators [16][17][18][19]. Primitive contamination information is represented as a mass function of seven focal elements for each source, explored from the latent information, using the self-recursive wavelet neural network (SRWNN) calculation [20].…”

Section: Introductionmentioning

confidence: 99%

Online prediction for contamination of chlortetracycline fermentation based on Dezert–Smarandache theory

Yang

Chen

Jin

2015

Chinese Journal of Chemical Engineering

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Self-recursive wavelet neural network Unscented kalman filter Fermentative production of chlortetracycline is a complex fed-batch bioprocess. It generally takes over 90 h for cultivation and is often contaminated by undesired microorganisms. Once the fermentation system is contaminated to certain extent, the product quality and yield will be seriously affected, leading to a substantial economic loss. Using information fusion based on the Dezer-Smarandache theory, self-recursive wavelet neural network and unscented kalman filter, a novel method for online prediction of contamination is developed. All state variables of culture process involving easy-to-measure and difficult-to-measure variables commonly obtained with soft-sensors present their contamination symptoms. By extracting and fusing latent information from the changing trend of each variable, integral and accurate prediction results for contamination can be achieved. This makes preventive and corrective measures be taken promptly. The field experimental results show that the method can be used to detect the contamination in time, reducing production loss and enhancing economic efficiency.

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Section: Introductionmentioning

confidence: 99%

Online prediction for contamination of chlortetracycline fermentation based on Dezert–Smarandache theory

Yang

Chen

Jin

2015

Chinese Journal of Chemical Engineering

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“…The DSmT deals directly with paradoxical/conflicting sources of information into this new formalism and proposes a new and very simple (associative and commutative) rule of combination for conflicting sources of informations (corpus/bodies of evidence). Some interesting results based on DSmT approach can be found in [24,4]. Before going deeper into the DSmT it is necessary to briefly present first the foundations of the DST and DSmT for a better understanding of the important differences between these two theories.…”

Section: Introductionmentioning

confidence: 99%

On the generation of hyper-powersets for the DSmT

Dezert

Smarandache

2003

Sixth International Conference of Information Fusion, 2003. Proceedings of The

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The recent theory of plausible and paradoxical reasoning (DSmT) developed by the authors appears to be a nice promising theoretical took to solve many information fusion problems where the Shafer's model cannot be used due to the intrinsic parad&-cal nature of the elements of the frame of discernment and where a strong internal conflict between sources arise. The main idea of DSmT is to work on the hyper-powerset of the frame of discernment of the problem under consideration. Although the definition of hyper-powerset is well established, the major dificulty in practice is to generate such hyper-powersets in order to implement DSmTfusion rule on computers. We present in this paper a simple algorithm for generating hyper-powersets and discuss the limitations of our actual computers to generate such hyper-powersets when the dimension of the problem increases.

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“…In this paper, we focus our attention, on how to order them in a clever way in order to get a very interesting matrix representation of belief functions defined over D Θ .The DSmT deals directly with paradoxical/conflicting sources of information into this new formalism and proposes a new and very simple (associative and commutative) rule of combination for conflicting sources of informations (corpus/bodies of evidence). Some interesting results based on DSmT approach can be found in [16,1]. Before going deeper into the DSmT it is necessary to briefly present first the foundations of the DST and DSmT for a better understanding of the important differences between these two theories based on Shafer model and DSm model.…”

Section: Introductionmentioning

confidence: 99%