Enhancing the performance of a ubiquitous location-aware service system using a fuzzy collaborative problem solving strategy

Chen, Toly

doi:10.1016/j.cie.2015.05.006

“…However, the method was either too theoretical or not adequately efficient for real-time applications. To solve this problem, a recent study proposed a heuristic that could be easily implemented for online applications [67] . However, the heuristic could not guarantee the global optimality of the recommendation.…”

Section: Article In Pressmentioning

confidence: 99%

Assessing factors critical to smart technology applications to mobile health care − the fgm-fahp approach

Chen

¹

2020

Health Policy and Technology

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a b s t r a c tSmart technologies present numerous opportunities for enhancing mobile health care. However, some concerns regarding the viability of smart technology applications must be addressed. This study investigated these concerns by reviewing the current practices of smart technology applications to mobile health care. As a result, five factors critical to the applicability of a smart technology to mobile health care are identified, and the fuzzy geometric mean-fuzzy analytic hierarchy process (FGM-FAHP) approach is proposed to assess the relative importance levels of the identified factors. The experimental results showed that the three most critical factors identified include: (a) the relaxation of the related medical laws; (b) unobtrusiveness; and (c) the precise need and situation of a user. Accordingly, approximately 44%, 26%, and 15% of the budget should be allocated to the realization of the three critical factors, respectively. In addition, the challenges involved and opportunities for enhancing the effectiveness of existing applications are discussed.

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“…However, a Petri net is based on numerous assumptions on probability distributions and parameter independence. To solve this problem, a recent study proposed a heuristic that could be easily implemented for online applications [67] . Then, he applied OWA to determine the clinic that was most suitable for the patient.…”

Section: Article In Pressmentioning

confidence: 99%

Evaluating the sustainability of a smart technology application to mobile health care: the FGM–ACO–FWA approach

Chen

¹

2019

Complex Intell. Syst.

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a b s t r a c tSmart technologies present numerous opportunities for enhancing mobile health care. However, some concerns regarding the viability of smart technology applications must be addressed. This study investigated these concerns by reviewing the current practices of smart technology applications to mobile health care. As a result, five factors critical to the applicability of a smart technology to mobile health care are identified, and the fuzzy geometric mean-fuzzy analytic hierarchy process (FGM-FAHP) approach is proposed to assess the relative importance levels of the identified factors. The experimental results showed that the three most critical factors identified include: (a) the relaxation of the related medical laws; (b) unobtrusiveness; and (c) the precise need and situation of a user. Accordingly, approximately 44%, 26%, and 15% of the budget should be allocated to the realization of the three critical factors, respectively. In addition, the challenges involved and opportunities for enhancing the effectiveness of existing applications are discussed.

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“…In addition, multiple experts’ opinions are consulted to avoid personal bias or omissions [ 23 ], resulting in the collaborative nature of the proposed methodology [ 24 , 25 ]. Further, fuzzy collaborative intelligence methods have been successfully applied to various topics, e.g., retrieving concepts from medical documents [ 26 ], enhancing the performance of a ubiquitous location-aware service system [ 27 ], distributing tasks among robots or three-dimensional (3D) printers [ 28 , 29 , 30 , 31 ], evaluating the suitability of a smart technology application for fall detection [ 32 ], etc.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Robustness of a Factory Amid the COVID-19 Pandemic: A Fuzzy Collaborative Intelligence Approach

Chen

¹

,

Wang

²

,

Chiu

³

2020

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The COVID-19 pandemic has affected the operations of factories worldwide. However, the impact of the COVID-19 pandemic on different factories is not the same. In other words, the robustness of factories to the COVID-19 pandemic varies. To explore this topic, this study proposes a fuzzy collaborative intelligence approach to assess the robustness of a factory to the COVID-19 pandemic. In the proposed methodology, first, a number of experts apply a fuzzy collaborative intelligence approach to jointly evaluate the relative priorities of factors that affect the robustness of a factory to the COVID-19 pandemic. Subsequently, based on the evaluated relative priorities, a fuzzy weighted average method is applied to assess the robustness of a factory to the COVID-19 pandemic. The assessment result can be compared with that of another factory using a fuzzy technique for order preference by similarity to ideal solution. The proposed methodology has been applied to assess the robustness of a wafer fabrication factory in Taiwan to the COVID-19 pandemic.

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Enhancing the performance of a ubiquitous location-aware service system using a fuzzy collaborative problem solving strategy

Cited by 12 publications

References 21 publications

Assessing factors critical to smart technology applications to mobile health care − the fgm-fahp approach

Assessing factors critical to smart technology applications to mobile health care − the fgm-fahp approach

Evaluating the sustainability of a smart technology application to mobile health care: the FGM–ACO–FWA approach

Assessing the Robustness of a Factory Amid the COVID-19 Pandemic: A Fuzzy Collaborative Intelligence Approach

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