scholarly journals Evaluating the Suitability of a Smart Technology Application for Fall Detection Using a Fuzzy Collaborative Intelligence Approach

Mathematics ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 1097 ◽  
Author(s):  
Yu-Cheng Lin ◽  
Yu-Cheng Wang ◽  
Tin-Chih Toly Chen ◽  
Hai-Fen Lin
Keyword(s):  
Fall Detection ◽  
Decision Makers ◽  
Smart Technology ◽  
Technology Application ◽  
Technology Applications ◽  
Order Preference ◽  
Collaborative Intelligence ◽  
Fuzzy Weights ◽  
Intelligence Approach ◽  
The Ideal

Fall detection is a critical task in an aging society. To fulfill this task, smart technology applications have great potential. However, it is not easy to choose a suitable smart technology application for fall detection. To address this issue, a fuzzy collaborative intelligence approach is proposed in this study. In the fuzzy collaborative intelligence approach, alpha-cut operations are applied to derive the fuzzy weights of criteria for each decision maker. Then, fuzzy intersection is applied to aggregate the fuzzy weights derived by all decision makers. Subsequently, the fuzzy technique for order preference by similarity to the ideal solution is applied to assess the suitability of a smart technology application for fall detection. The fuzzy collaborative intelligence approach is a posterior-aggregation method that guarantees a consensus exists among decision makers. After applying the fuzzy collaborative intelligence approach to assess the suitabilities of four existing smart technology applications for fall detection, the most and least suitable smart technology applications were smart carpet and smart cane, respectively. In addition, the ranking result using the proposed methodology was somewhat different from those using three existing methods.

scholarly journals Assessing and Comparing COVID-19 Intervention Strategies Using a Varying Partial Consensus Fuzzy Collaborative Intelligence Approach

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1725
Author(s):  
Hsin-Chieh Wu ◽  
Yu-Cheng Wang ◽  
Tin-Chih Toly Chen
Keyword(s):  
Intervention Strategy ◽  
Critical Factor ◽  
Cost Effective ◽  
Intervention Strategies ◽  
Decision Makers ◽  
City Governments ◽  
Assessment Approach ◽  
Collaborative Intelligence ◽  
Partial Consensus ◽  
Intelligence Approach

The COVID-19 pandemic has severely impacted our daily lives. For tackling the COVID-19 pandemic, various intervention strategies have been adopted by country (or city) governments around the world. However, whether an intervention strategy will be successful, acceptable, and cost-effective or not is still questionable. To address this issue, a varying partial consensus fuzzy collaborative intelligence approach is proposed in this study to assess an intervention strategy. In the varying partial consensus fuzzy collaborative intelligence approach, multiple decision makers express their judgments on the relative priorities of factors critical to an intervention strategy. If decision makers lack an overall consensus, the layered partial consensus approach is applied to aggregate their judgments for each critical factor. The number of decision makers that reach a partial consensus varies from a critical factor to another. Subsequently, the generalized fuzzy weighted assessment approach is proposed to evaluate the overall performance of an intervention strategy for tackling the COVID-19 pandemic. The proposed methodology has been applied to compare 15 existing intervention strategies for tackling the COVID-19 pandemic.

scholarly journals A Multiple Criteria Decision Making Method Based on Relative Value Distances

2015 ◽  
Vol 40 (4) ◽  
pp. 299-315 ◽  
Author(s):  
Huan-jyh Shyur ◽  
Liang Yin ◽  
Hsu-shih Shih ◽  
Chi-bin Cheng
Keyword(s):  
Decision Making ◽  
Solution Method ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Relative Value ◽  
Seeking Behavior ◽  
Order Preference ◽  
Topsis Technique ◽  
The Ideal

Abstract This paper proposes a new multiple criteria decision-making method called ERVD (election based on relative value distances). The s-shape value function is adopted to replace the expected utility function to describe the risk-averse and risk-seeking behavior of decision makers. Comparisons and experiments contrasting with the TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) method are carried out to verify the feasibility of using the proposed method to represent the decision makers’ preference in the decision making process. Our experimental results show that the proposed approach is an appropriate and effective MCDM method.

scholarly journals Application of fuzzy technique for order preference by similarity to the ideal solution in the selection of candidates

2012 ◽  
Vol 9 (1) ◽  
pp. 35
Author(s):  
Mohd Ariff Ahmad Taharim ◽  
Liew Kee Kor
Keyword(s):  
Real Life ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Mathematical Form ◽  
Selection Processes ◽  
Proposed Model ◽  
Order Preference ◽  
The Right ◽  
Selection Of ◽  
The Ideal

Selecting the right candidate for the right cause is similar to identifying the most compromising solution of multi-criteria decision making (MCDM) problem. In real life the selection criteriamay involve vague and incomplete data which cannot be expressed in precise mathematical form or numerical values. Apparently fuzzy-based technique can be applied to describe and represent these data in fuzzy numbers. This paper presents a MCDM fuzzy TOPSIS based model designed to solve the selection problemfor allocation of government staff quarters. Result shows that the proposed model is suitable and appropriate. It was also found that the MCDM model which uses single decision maker rating process can also be applied to multiple decision makers. It is recommended that the application of fuzzy TOPSIS can be extended to other selection processes such as vendor selection, training evaluation or group marking of project works.

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

Healthcare ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 481
Author(s):  
Toly Chen ◽  
Yu-Cheng Wang ◽  
Min-Chi Chiu
Keyword(s):  
Average Method ◽  
Weighted Average ◽  
Ideal Solution ◽  
Weighted Average Method ◽  
Fuzzy Weighted Average ◽  
Order Preference ◽  
Collaborative Intelligence ◽  
The Impact ◽  
Intelligence Approach ◽  
Assessment Result

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.

Decision making based on intuitionistic fuzzy preference relations with additive approximate consistency

2020 ◽  
Vol 39 (3) ◽  
pp. 4041-4058
Author(s):  
Fang Liu ◽  
Xu Tan ◽  
Hui Yang ◽  
Hui Zhao
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Real Interval ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Proposed Model ◽  
Fuzzy Preference Relations ◽  
Novel Concept ◽  
Fuzzy Weights ◽  
Fuzzy Preference

Intuitionistic fuzzy preference relations (IFPRs) have the natural ability to reflect the positive, the negative and the non-determinative judgements of decision makers. A decision making model is proposed by considering the inherent property of IFPRs in this study, where the main novelty comes with the introduction of the concept of additive approximate consistency. First, the consistency definitions of IFPRs are reviewed and the underlying ideas are analyzed. Second, by considering the allocation of the non-determinacy degree of decision makers’ opinions, the novel concept of approximate consistency for IFPRs is proposed. Then the additive approximate consistency of IFPRs is defined and the properties are studied. Third, the priorities of alternatives are derived from IFPRs with additive approximate consistency by considering the effects of the permutations of alternatives and the allocation of the non-determinacy degree. The rankings of alternatives based on real, interval and intuitionistic fuzzy weights are investigated, respectively. Finally, some comparisons are reported by carrying out numerical examples to show the novelty and advantage of the proposed model. It is found that the proposed model can offer various decision schemes due to the allocation of the non-determinacy degree of IFPRs.

scholarly journals Comparative Analysis of Hybrid Fuzzy MCGDM Methodologies for Optimal Robot Selection Process

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 839
Author(s):  
Tabasam Rashid ◽  
Asif Ali ◽  
Juan Guirao ◽  
Adrián Valverde
Keyword(s):  
Selection Process ◽  
Industrial Robot ◽  
Vital Role ◽  
Decision Makers ◽  
Fuzzy Information ◽  
Criteria Weights ◽  
Topsis Technique ◽  
Fuzzy Weights ◽  
Robot Selection ◽  
Interval Valued

The generalized interval-valued trapezoidal fuzzy best-worst method (GITrF-BWM) provides more reliable and more consistent criteria weights for multiple criteria group decision making (MCGDM) problems. In this study, GITrF-BWM is integrated with the extended TOPSIS (technique for order preference by similarity to the ideal solution) and extended VIKOR (visekriterijumska optimizacija i kompromisno resenje) methods for the selection of the optimal industrial robot using fuzzy information. For a criteria-based selection process, assigning weights play a vital role and significantly affect the decision. Assigning weights based on direct opinions of decision makers can be biased, so weight deriving models, such as GITrF-BWM, overcome this discrepancy. In previous studies, generalized interval-valued trapezoidal fuzzy weights were not derived by using any MCGDM method for the robot selection process. For this study, both subjective and objective criteria are considered. The preferences of decision makers are provided with the help of linguistic terms that are then converted into fuzzy information. The stability and reliability of the methods were tested by performing sensitivity analysis, which showed that the ranking results of both the methodologies are not symmetrical, and the integration of GITrF-BWM with the extended TOPSIS method provides stable and reliable results as compared to the integration of GITrF-BWM with the extended VIKOR method. Hence, the proposed methodology provides robust optimal industrial robot selection.

Fuzzy multicriteria decision-making-based optimal Zn–Al alloy selection in corrosive environment

2020 ◽  
Vol 111 (11) ◽  
pp. 953-963
Author(s):  
Ankur V. Bansod ◽  
Awanikumar P. Patil ◽  
Kanak Kalita ◽  
B. D. Deshmukh ◽  
Nilay Khobragade
Keyword(s):  
Decision Making ◽  
Weight Loss ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
Al Alloy ◽  
Ideal Solution ◽  
Corrosive Environment ◽  
Multicriteria Decision ◽  
Al Content ◽  
The Ideal

Abstract Suitable material selection with emphasis on a specific property or application is an indispensable part of engineering sciences. It is a complex process that involves multiple criteria and often multiple decision makers. The tendency of decision makers to specify their preference in terms of imprecise qualitative statements like ‘good’, ‘bad’ etc. poses a further challenge. Thus, in this research, a comprehensive multicriteria decision-making study was conducted to select the optimal Zn-Al alloy based on performance in a corrosive environment. Four variants of technique for order of preference by similarity to the ideal solution were used to perform the multicriteria decision-making analysis. Group decision and imprecise decision making is handled by incorporating the fuzzy theory concept in a technique for order of preference by similarity to the ideal solution. The effect of addition of aluminium to zinc was studied by examination of microstructure, hardness, and corrosion behaviour. The result indicates that an increase in Al content increases the formation of dendrites. The dendrites were rich in the α phase, which results in an increase in hardness. An increase in Al content in Zn (Zn-22Al and Zn-55Al) results in the uniform distribution of the a phase in the microstructure and reduction of non-equilibrium phases. The potentiodynamic polarisation test revealed that an increase in Al in the alloy decreases the corrosion current density. The weight loss test carried out to validate the potentiodynamic test findings exhibited higher weight loss in pure Zn and lowest in Zn-55Al. Similar results were observed in the salt spray test. The multicriteria decision-making analysis revealed that Zn-55Al is the most suitable alloy in a corrosive environment among the tested alloys.

GIS Based Multi-Criteria decision support system and machine learning for Hospital Site Selection case study Oran - Algeria

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Site Selection ◽  
Decision Makers ◽  
Analysis Method ◽  
Automatic Learning ◽  
Hospital Site ◽  
Set Up ◽  
High Level ◽  
Selection Of ◽  
The Ideal

The selection of hospital sites is one of the most important choice a decision maker has to take so as to resist the pandemic. The decision may considerably affect the outbreak transmission in terms of efficiency , budget, etc. The main targeted objective of this study is to find the ideal location where to set up a hospital in the willaya of Oran Alg. For this reason, we have used a geographic information system coupled to the multi-criteria analysis method AHP in order to evaluate diverse criteria of physiological positioning , environmental and economical. Another objective of this study is to evaluate the advanced techniques of the automatic learning . the method of the random forest (RF) for the patterning of the hospital site selection in the willaya of Oran. The result of our study may be useful to decision makers to know the suitability of the sites as it provides a high level of confidence and consequently accelerate the power to control the COVID19 pandemic.

scholarly journals Health Is Wealth: Study on Consumer Preferences and the Willingness to Pay for Ecological Agricultural Product Traceability Technology: Evidence from Jiangxi Province China

2021 ◽  
Vol 18 (22) ◽  
pp. 11761
Author(s):  
Ximing Chen ◽  
Jie Shang ◽  
Muhammad Zada ◽  
Shagufta Zada ◽  
Xueqiang Ji ◽  
...  
Keyword(s):  
Willingness To Pay ◽  
Consumer Preferences ◽  
Jiangxi Province ◽  
Agricultural Product ◽  
Technology Application ◽  
Additional Payments ◽  
Organic Rice ◽  
Blockchain Technology ◽  
Experiment Method ◽  
Technology Applications

The application of traceability technology is an important way to solve food safety problems. Different traceability technologies bring different effects to consumers. Existing studies have not explored consumers’ preferences in regards to product traceability technology applications, and they have not analyzed their willingness to pay. Therefore, this study focused on organic rice, an ecological agricultural product. The study was based on a survey from Jiangxi Province, China. It used a selective experiment method in order to analyze consumer preferences and the willingness to pay for ecological agricultural product traceability technology. The results show that consumer preferences are as follows: blockchain technology application attributes, traditional traceability-technology-application attributes, high credit-supervision attributes, and international-certification attributes. In terms of willingness to pay, consumers have the highest willingness to pay for the application of blockchain technology, which they are willing to pay CNY 21.902 more per kg for this attribute. At the same time, consumers are also willing to make additional payments for traditional traceability-technology-application attributes, high credit-supervision attributes, and international-certification attributes. Their willingness to pay is CNY 20.426, CNY 17.115 yuan, and CNY 11.049, respectively.

Sign in / Sign up

Export Citation Format

Share Document