Reasoning dynamic fuzzy systems based on adaptive fuzzy higher order Petri nets

Amin, Mohamed; Shebl, Doaa

doi:10.1016/j.ins.2014.07.011

Cited by 28 publications

(9 citation statements)

References 12 publications

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“…Numerous problems arising in engineering and scientific domains have been successfully modeled and simulated in terms of Petri net technologies [4,5,8,[14][15][16]. Particularly, we have used hybrid functional Petri net (HFPN) to create a quantitative model of molecular interactions between major regulators of fetal-to-adult hemoglobin switching network [19] and p16-mediated signaling pathway [1].…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Identifying targets for gene therapy of β-globin disorders using quantitative modeling approach

Bashirov

Mehraei

2017

Information Sciences

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Please cite this article as: Mani Mehraei , Rza Bashirov , Identifying targets for gene therapy of β-globin disorders using quantitative modeling approach, Information Sciences (2017Sciences ( ), doi: 10.1016Sciences ( /j.ins.2017 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. ACCEPTED MANUSCRIPT A C C E P T E D M A N U S C R I P T Information SciencesInformation Sciences 00 (2016) AbstractSickle cell disease and β-thalassemia are well-known genetic disorders which are caused by mutations in β-globin gene. Reactivation of fetal hemoglobin in adulthood through induction of γ-globin gene expression has proven be sufficient to ameliorate sickle cell disease and β-thalassemia. In the last few decades, substantial efforts have been made to identify potential target candidates for β-globin diseases. In the present work, we propose an innovative approach for identifying novel molecular targets of β-globin diseases. Our approach is based on quantitative modeling of fetal-to-adult hemoglobin switching network with hybrid functional Petri nets. We verify the coherence of deterministic quantitative model created in this research to be sure it is consistent with qPCR data available for known siRNA-and shRNA-based strategies. Comparison of simulation results for the proposed strategy with the ones obtained for already existing RNAi-mediated treatments shows that our strategy is optimal, as it leads to the highest level of γ-globin induction. Consequently, it has potential beneficial therapeutic effect on β-globin diseases. This study also provides an innovative strategy for the target-based treatment of many other diseases.

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Section: Accepted Manuscriptmentioning

confidence: 99%

Identifying targets for gene therapy of β-globin disorders using quantitative modeling approach

Bashirov

Mehraei

2017

Information Sciences

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“…Besides that, FPN can implement the dynamic inference process using different reasoning mechanisms. Owing to the advantages above, FPN has been applied in various fields to implement inference [18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

A Bidirectional Diagnosis Algorithm of Fuzzy Petri Net Using Inner-Reasoning-Path

Zhou

Gui

et al. 2018

Symmetry

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Fuzzy Petri net (FPN) is a powerful tool to execute the fault diagnosis function for various industrial applications. One of the most popular approaches for fault diagnosis is to calculate the corresponding algebra forms which record flow information and three parameters of value of all places and transitions of the FPN model. However, with the rapid growth of the complexity of the real system, the scale of the corresponding FPN is also increased sharply. It indicates that the complexity of the fault diagnosis algorithm is also raised due to the increased scale of vectors and matrix. Focusing on this situation, a bidirectional adaptive fault diagnosis algorithm is presented in this article to reduce the complexity of the fault diagnosis process via removing irrelevant places and transitions of the large-scale FPN, followed by the correctness and algorithm complexity of the proposed approach that are also discussed in detail. A practical example is utilized to show the feasibility and efficacy of the proposed method. The results of the experiments illustrated that the proposed algorithm owns the ability to simplify the inference process and to reduce the algorithm complexity due to the removal of unnecessary places and transitions in the reasoning path of the appointed output place.

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“…In the field of artificial intelligence, the use of Petri nets was first reported by Genrich and Thieler-Mevissen [10]. Further work on the subject was done in [11][12][13][14][15]. In [11][12][13], these papers proved that Petri net can be easily combined with other techniques and theory.…”

Section: Introductionmentioning

confidence: 99%

“…In [11][12][13], these papers proved that Petri net can be easily combined with other techniques and theory. In [14][15], the authors also proved that heavy computation burden problems can be reduced by using the fuzzy Petri net. Therefore, in this study, we combine DFS and the Petri net to alleviate the computation burden of parameter learning, but still preserve its good ability of approximating dynamic nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Direct adaptive control via decomposed fuzzy Petri net

Chen

Chien

et al. 2014

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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This paper presents a novel direct adaptive controller design via decomposed fuzzy Petri net to solve the control tracking problem. The controller combines decomposed fuzzy system (DFS) and Petri net to achieve good performance with less computation time. In the DFS structure, fuzzy variables are decomposed into several layers. DFS has been shown to have fast learning capability but with a complicated system structure. In this study, Petri net is employed to form a mechanism in constructing meaningful component fuzzy systems in the DFS so that the number of fuzzy components can be dramatically reduced without significantly degrading the modeling performance. Finally, the effectiveness of the proposed controller scheme is verified by simulation results.

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Reasoning dynamic fuzzy systems based on adaptive fuzzy higher order Petri nets

Cited by 28 publications

References 12 publications

Identifying targets for gene therapy of β-globin disorders using quantitative modeling approach

Identifying targets for gene therapy of β-globin disorders using quantitative modeling approach

A Bidirectional Diagnosis Algorithm of Fuzzy Petri Net Using Inner-Reasoning-Path

Direct adaptive control via decomposed fuzzy Petri net

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