A fuzzy expert system architecture for data and event stream processing

Poli, Jean-Philippe; Boudet, Laurence

doi:10.1016/j.fss.2017.10.005

Cited by 11 publications

(6 citation statements)

References 29 publications

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“…The role of fuzzy logic in architecture is well-desired. Rather than the use of multiple heterogeneous space attitudes either qualitative or quantitative, fuzzy logic has an accurate result (Moaven and Habibi, 2020; Poli and Boudet, 2018). Moreover, it is a flexible model that used multiple input variables to determine the output.…”

Section: Fuzzy Inference System and Fuzzy Logicmentioning

confidence: 99%

A quality learning environment: an assessment of spaciousness of architectural design studios of Iraqi Kurdistan region universities using fuzzy logic

Hussein

Mustafa

2023

OHI

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PurposeSpaciousness is defined as “the feeling of openness or room to wander” that has been affected by various physical factors. The purpose of this paper is to assess the spaciousness of space to determine how spacious the space is. Furthermore, the study intends to propose a fuzzy-based model to assess the degree of spaciousness in terms of physical parameters such as area, proportion, the ratio of window area to floor area and color value.Design/methodology/approachFuzzy logic is the most appropriate mathematical model to assess uncertainty using nonhomogeneous variables. In contrast to conventional methods, fuzzy logic depends on partial truth theory. MATLAB Fuzzy Logic Toolbox was used as a computational model including a fuzzy inference system (FIS) using linguistic variables called membership functions to define parameters. As a result, fuzzy logic was used in this study to assess the spaciousness degree of design studios in universities in the Iraqi Kurdistan region.FindingsThe findings of the presented fuzzy model show the degree to which the input variables affect a space perceived as larger and more spacious. The relationship between parameters has been represented in three-dimensional surface diagrams. The positive relationship of spaciousness with the area, window-to-floor area ratio and color value has been determined. In contrast, the negative relationship between spaciousness and space proportion is described. Moreover, the three-dimensional surface diagram illustrates how the changes in the input values affect the spaciousness degree. Besides, the improvement in the spaciousness degree of the design studio increases the quality learning environment.Originality/valueThis study attempted to assess the degree of spaciousness in design studios. There has been no attempt carried out to combine educational space learning environments and computational methods. This study focused on the assessment of spaciousness using the MATLAB Fuzzy Logic toolbox that has not been integrated so far.

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Section: Fuzzy Inference System and Fuzzy Logicmentioning

confidence: 99%

A quality learning environment: an assessment of spaciousness of architectural design studios of Iraqi Kurdistan region universities using fuzzy logic

Hussein

Mustafa

2023

OHI

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“…The knowledge of the rules is closely linked to that of the facts but is the result, so to speak, of the accumulation of this knowledge, which is used to elaborate the rules that define the behavior of the system. Finally, the knowledge of control allows the choice of the best strategy for the functioning of the system [24].…”

Section: Artificial Intelligence Concepts and Toolsmentioning

confidence: 99%

“…According to [24] the Internet of Things (IoT) is an organization of correlated preparing devices, mechanical and propelled machines, things, animals, or people that are given unique identifiers and the ability to move data over a framework without anticipating that human-to-human or human-to-PC. The IoT architecture is designed to provide all objects with identification, detection, networking, and processing capabilities, so that they can exchange and share information with each other and develop advanced services over the Internet.…”

Section: Internet Of Thingsmentioning

confidence: 99%

Intelligent Support System for Healthcare Logistics 4.0 Optimization in the Covid Pandemic Context

Dossou¹,

Foreste²,

Misumi³

2021

JSEA

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“…The Internet of Things (IoT) paradigm has emerged from the proliferation of objects and mobile devices (i.e., “things”) connected, which results in the acquisition of periodic event flows from different devices and sensors that need to be processed [ 1 ]. IoT proposes to expand the current structure of the Internet into a network of interconnected objects that not only collect information from the environment but also interact with the physical world to provide services such as information transfer and analysis, applications, and communications [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

Dempster–Shafer Theory for Modeling and Treating Uncertainty in IoT Applications Based on Complex Event Processing

Bezerra

Teles

Coutinho

et al. 2021

Sensors

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The Internet of Things (IoT) has emerged from the proliferation of mobile devices and objects connected, resulting in the acquisition of periodic event flows from different devices and sensors. However, such sensors and devices can be faulty or affected by failures, have poor calibration, and produce inaccurate data and uncertain event flows in IoT applications. A prominent technique for analyzing event flows is Complex Event Processing (CEP). Uncertainty in CEP is usually observed in primitive events (i.e., sensor readings) and rules that derive complex events (i.e., high-level situations). In this paper, we investigate the identification and treatment of uncertainty in CEP-based IoT applications. We propose the DST-CEP, an approach that uses the Dempster–Shafer Theory to treat uncertainties. By using this theory, our solution can combine unreliable sensor data in conflicting situations and detect correct results. DST-CEP has an architectural model for treating uncertainty in events and its propagation to processing rules. We describe a case study using the proposed approach in a multi-sensor fire outbreak detection system. We submit our solution to experiments with a real sensor dataset, and evaluate it using well-known performance metrics. The solution achieves promising results regarding Accuracy, Precision, Recall, F-measure, and ROC Curve, even when combining conflicting sensor readings. DST-CEP demonstrated to be suitable and flexible to deal with uncertainty.

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A fuzzy expert system architecture for data and event stream processing

Cited by 11 publications

References 29 publications

A quality learning environment: an assessment of spaciousness of architectural design studios of Iraqi Kurdistan region universities using fuzzy logic

A quality learning environment: an assessment of spaciousness of architectural design studios of Iraqi Kurdistan region universities using fuzzy logic

Intelligent Support System for Healthcare Logistics 4.0 Optimization in the Covid Pandemic Context

Dempster–Shafer Theory for Modeling and Treating Uncertainty in IoT Applications Based on Complex Event Processing

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