Data fusion as source for the generation of useful knowledge in context-aware systems

Muñoz, Julio; Molero–Castillo, Guillermo; Benítez–Guerrero, Edgard; Bárcenas, Everardo

doi:10.3233/jifs-169500

Cited by 12 publications

(8 citation statements)

References 40 publications

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“…( 8) and Eq. (9). We obtain the following calculation formula:       0.5 0.5 0.5 0.5 0.5 , , ,…”

Section: Data Fusion and Results Analysismentioning

confidence: 99%

“…After hundreds of years of research, fractional differentials does not have a unified definition, many scholars have proposed their own definition methods and theoretical systems based on their own understanding and application fields. At present, the commonly used definitions are those of Grunwald-Letnikov (G-L), Caputo, and Riemann-Liouville (R-L) [9,10].…”

Section: Fractional Differential Definitionmentioning

confidence: 99%

“…The essence of software method is information data fusion algorithm. up to now, there have been many research results Common mathematical algorithms are fuzzy set theory [9], fuzzy neural networks [10], probability model [11] and particle swarm optimization algorithm [12], et al and obtained a regrettable research review. For example, Li Huo et al [13] proposed an integral infinite log-ratio algorithm (IILRA) and an integral infinity log-ratio algorithm based on the signal-to-noise ratio (BSNR-IILRA) to Improve the detection accuracy of laser communication detection position in the atmosphere.…”

Section: 1 Introductionmentioning

confidence: 99%

See 2 more Smart Citations

High Accuracy Detection Technique for Information Data Under the Influence of Multiple Factors based on Fractional Partial Differential Equations

Zuo¹,

Chen²

2023

Preprint

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In engineering practice, various types of information data are affected by many factors during the collection process. For example, information data measurement errors are caused by equipment performance and the working environment. During the transmission of detection information, the signal distortion caused by energy loss and signal interference causes unpredictable detection errors in the collected information data. Through the study of fractional calculus theory, it was found that it is suitable for studying nonlinear, non-causal, and non-stationary signals, and has the dual functions of improving detection information and enhancing signal strength. Therefore, under the influence of many factors, we applied the fractional difference algorithm to the field of information data processing. Multi-sensor detection data fusion algorithm based on the fractional partial differential equation was adopted to establish its online detection data. A multi-sensor detection data fusion algorithm based on a fractional partial differential equation is established, which effectively fuses the information data detection errors caused by various influencing factors and greatly improves the detection accuracy of information data. The effectiveness of this method is proved through its application in an experiment.

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“…( 8) and Eq. (9). We obtain the following calculation formula:       0.5 0.5 0.5 0.5 0.5 , , ,…”

Section: Data Fusion and Results Analysismentioning

confidence: 99%

Section: Fractional Differential Definitionmentioning

confidence: 99%

Section: 1 Introductionmentioning

confidence: 99%

See 1 more Smart Citation

High Accuracy Detection Technique for Information Data Under the Influence of Multiple Factors based on Fractional Partial Differential Equations

Zuo¹,

Chen²

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The essence of the software method is the information data-fusion algorithm. up to now, there have been many research results Common mathematical algorithms are fuzzy set theory [22], fuzzy neural networks [23], probability model [24] and particle swarm optimization algorithm [25], et al and obtained a regrettable research review. For example, Huo et al [26] proposed an integral infinite log-ratio algorithm (IILRA) and an integral infinity log-ratio algorithm based on signal-to-noise ratio (BSNR-IILRA) to improve the detection accuracy of the laser communication detection position in the atmosphere.…”

Section: High-precision Information Data Acquisition Technologymentioning

confidence: 99%

Research on Manufacturing Equipment Operation State Evaluation Technology Based on Fractional Calculus

Chen¹,

Zuo²,

Geng³

et al. 2023

Preprint

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The operation status of manufacturing equipment is directly related to the reliability of the operation of manufacturing equipment and the continuity of operation of the production system. Based on the analysis of the operation status of manufacturing equipment and its characteristics, it is proposed that the concept of assessing the operation status of manufacturing equipment can be realized by applying real-time acquisition of accurate inspection data of important parts of weak motion units and comparing them with their motion status evaluation criteria. Through the study of the application characteristics of fractional-order calculus theory, a differential data fusion model based on the fractional-order differential operator is established. The advantages of Internet of Things (IoT）technology and fractional order differential fusion algorithm are integrated to obtain real-time high-precision data of the operating parameters of manufacturing equipment, and the research objective of operating condition assessment of manufacturing equipment is realized. The feasibility and effectiveness of the method are verified by the application of the method in machining center operation status assessment.

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“…Bayesian networks and D-S evidence theory are commonly used to deal with the uncertainty in multi-sensor data, which frequently results in anomalous data. However, the Bayesian estimation fusion method requires access to prior data to generate new probability estimates, which is not always possible [ 6 ]. Dempster–Shafer (D-S) evidence theory is a theory of fuzzy reasoning proposed by Dempster in 1967 [ 7 ] and subsequently refined by Shafer [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Sensor Data-Fusion Method Based on Cloud Model and Improved Evidence Theory

Xiang

Huang

et al. 2022

Sensors

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The essential factors of information-aware systems are heterogeneous multi-sensory devices. Because of the ambiguity and contradicting nature of multi-sensor data, a data-fusion method based on the cloud model and improved evidence theory is proposed. To complete the conversion from quantitative to qualitative data, the cloud model is employed to construct the basic probability assignment (BPA) function of the evidence corresponding to each data source. To address the issue that traditional evidence theory produces results that do not correspond to the facts when fusing conflicting evidence, the three measures of the Jousselme distance, cosine similarity, and the Jaccard coefficient are combined to measure the similarity of the evidence. The Hellinger distance of the interval is used to calculate the credibility of the evidence. The similarity and credibility are combined to improve the evidence, and the fusion is performed according to Dempster’s rule to finally obtain the results. The numerical example results show that the proposed improved evidence theory method has better convergence and focus, and the confidence in the correct proposition is up to 100%. Applying the proposed multi-sensor data-fusion method to early indoor fire detection, the method improves the accuracy by 0.9–6.4% and reduces the false alarm rate by 0.7–10.2% compared with traditional and other improved evidence theories, proving its validity and feasibility, which provides a certain reference value for multi-sensor information fusion.

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Data fusion as source for the generation of useful knowledge in context-aware systems

Cited by 12 publications

References 40 publications

High Accuracy Detection Technique for Information Data Under the Influence of Multiple Factors based on Fractional Partial Differential Equations

High Accuracy Detection Technique for Information Data Under the Influence of Multiple Factors based on Fractional Partial Differential Equations

Research on Manufacturing Equipment Operation State Evaluation Technology Based on Fractional Calculus

A Multi-Sensor Data-Fusion Method Based on Cloud Model and Improved Evidence Theory

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