Interval-valued q-rung orthopair fuzzy FMEA application to improve risk evaluation process of tool changing manipulator

2021 ◽  
Vol 104 ◽  
pp. 107192
Author(s):  
Chuanxi Jin ◽  
Yan Ran ◽  
Genbao Zhang
Keyword(s):  
Risk Evaluation ◽  
Evaluation Process ◽  
Fuzzy Fmea ◽  
Interval Valued

scholarly journals Approach to Multi-Attribute Decision-Making Methods for Performance Evaluation Process Using Interval-Valued T-Spherical Fuzzy Hamacher Aggregation Information

Axioms ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 145
Author(s):  
Yun Jin ◽  
Zareena Kousar ◽  
Kifayat Ullah ◽  
Tahir Mahmood ◽  
Nimet Yapici Pehlivan ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Evaluation Process ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Membership Degree ◽  
Operational Laws ◽  
Multi Attribute Decision Making ◽  
Interval Valued ◽  
Do So

Interval-valued T-spherical fuzzy set (IVTSFS) handles uncertain and vague information by discussing their membership degree (MD), abstinence degree (AD), non-membership degree (NMD), and refusal degree (RD). MD, AD, NMD, and RD are defined in terms of closed subintervals of that reduce information loss compared to the T-spherical fuzzy set (TSFS), which takes crisp values from intervals; hence, some information may be lost. The purpose of this manuscript is to develop some Hamacher aggregation operators (HAOs) in the environment of IVTSFSs. To do so, some Hamacher operational laws based on Hamacher t-norms (HTNs) and Hamacher t-conorms (HTCNs) are introduced. Using Hamacher operational laws, we develop some aggregation operators (AOs), including an interval-valued T-spherical fuzzy Hamacher (IVTSFH) weighted averaging (IVTSFHWA) operator, an IVTSFH-ordered weighted averaging (IVTSFHOWA) operator, an IVTSFH hybrid averaging (IVTSFHHA) operator, an IVTSFH-weighted geometric (IVTSFHWG) operator, an IVTSFH-ordered weighted geometric (IVTSFHOWG) operator, and an IVTSFH hybrid geometric (IVTSFHHG) operator. The validation of the newly developed HAOs is investigated, and their basic properties are examined. In view of some restrictions, the generalization and proposed HAOs are shown, and a multi-attribute decision-making (MADM) procedure is explored based on the HAOs, which are further exemplified. Finally, a comparative analysis of the proposed work is also discussed with previous literature to show the superiority of our work.

scholarly journals Semantic model for flood management

2012 ◽  
Vol 14 (4) ◽  
pp. 918-936 ◽  
Author(s):  
Julián Garrido ◽  
Ignacio Requena ◽  
Stefano Mambretti
Keyword(s):  
Risk Assessment ◽  
Conceptual Framework ◽  
Environmental Assessment ◽  
Risk Evaluation ◽  
Evaluation Process ◽  
Flood Management ◽  
Semantic Model ◽  
Effective Management ◽  
Flood Events ◽  
Qualified Personnel

Risk assessment involves the study of vulnerability and hazards. When focused on flood events, such an analysis should evidently include the theoretical and practical study of floods and their behavior. Nevertheless, risk assessment is not useful if the results are not subsequently used for more effective management and planning by local authorities and qualified personnel. The risk evaluation process is composed of a set of actions, each of which requires different inputs. In fact, the results of one action are used as the input for another. This paper describes a semantic model for the study and management of floods with a view to elaborating a conceptual framework and designing a knowledge base. The model is based on the environmental assessment ontology and demonstrates how a brief ontology can be generated.

An approach to decision making with interval-valued complex Pythagorean fuzzy model for evaluating personal risk of mental patients

2021 ◽  
pp. 1-26
Author(s):  
Lei Wang ◽  
Xindong Peng
Keyword(s):  
Decision Making ◽  
Fuzzy Model ◽  
Weighted Average ◽  
Evaluation Process ◽  
Pythagorean Fuzzy Set ◽  
Mental Patients ◽  
Personal Risk ◽  
Multiple Attribute ◽  
Uncertainty Information ◽  
Interval Valued

It is prominent important for managers to assess the personal risk of mental patients. The evaluation process refers to numerous indexes, and the evaluation values are general portrayed by uncertainty information. In order to conveniently model the complicated uncertainty information in realistic decision making, interval-valued complex Pythagorean fuzzy set is proposed. Firstly, with the aid of Einstein t-norm and t-conorm, four fundamental operations for interval-valued complex Pythagorean fuzzy number (IVCPFN) are constructed along with some operational properties. Subsequently, according to these proposed operations, the weighted average and weighted geometric forms of aggregation operators are initiated for fusing IVCPFNs, and their anticipated properties are also examined. In addition, a multiple attribute decision making issue is examined under the framework of IVCPFNs when employing the novel suggested operators. Ultimately, an example regarding the assessment on personal risk of mental patients is provided to reveal the practicability of the designed approach, and the attractiveness of our results is further found through comparing with other extant approaches.The main novelty of the coined approach is that it not only can preserve the original assessment information adequately by utilizing the IVCPFNs, but also can aggregate IVCPFNs effectively.

Terrain Hazard Risk Analysis for Flood Disaster Management in Chaohu Basin, China, Based on Two-Dimensional Cloud

2020 ◽  
Vol 24 (4) ◽  
pp. 532-542
Author(s):  
Jun Lyu ◽  
Xianfu Cheng ◽  
Peter Shaw ◽  
◽  
Keyword(s):  
Risk Evaluation ◽  
Qualitative Data ◽  
Multivariable Analysis ◽  
Evaluation Process ◽  
Flood Disaster ◽  
Preliminary Evaluation ◽  
Terrain Analysis ◽  
Two Dimensional ◽  
Cloud Models ◽  
Model Algorithm

Terrain analysis is essential to flood disaster risk evaluation. It is a complicated evaluation process, involving both quantitative and qualitative data analysis. However, quantitative and qualitative data cannot be put into operation directly. Based on stochastic and fuzzy mathematics, cloud models allow interchange between qualitative and quantitative data, dealing with randomness and ambiguity. Two- or multi-dimensional cloud models can solve the problem of multivariable analysis. This study used absolute elevation and neighborhood elevation standard deviation as main factors. Using the model, it demonstrated the construction of qualitative conditions and risk evaluation clouds and established a set of two-dimensional cloud reasoning rules to calculate the joint certainties with all the grids in reasoning rules. By selecting the highest certainty of cloud reasoning, preliminary evaluation results were obtained. For more accurate results, the model algorithm was improved, and further iterations were performed. The results of two-dimensional cloud reasoning showed better dispersion and precision than traditional methods did. The terrain risk distribution of Chaohu Basin, China, agreed with reality with great detail. A new method regarding the risk assessment of flood disaster was also proposed.

scholarly journals On K-Means Clustering with IVIF Datasets for Post-COVID-19 Recovery Efforts

Mathematics ◽  
2021 ◽  
Vol 9 (20) ◽  
pp. 2639
Author(s):  
Lanndon Ocampo ◽  
Joerabell Lourdes Aro ◽  
Samantha Shane Evangelista ◽  
Fatima Maturan ◽  
Egberto Selerio ◽  
...  
Keyword(s):  
Case Studies ◽  
Evaluation Process ◽  
Sensitivity Analyses ◽  
High Exposure ◽  
Attribute Weights ◽  
Hospitality Sector ◽  
Low Exposure ◽  
Tourism And Hospitality ◽  
Clustering Problems ◽  
Interval Valued

The recovery efforts of the tourism and hospitality sector are compromised by the emergence of COVID-19 variants that can escape vaccines. Thus, maintaining non-pharmaceutical measures amidst massive vaccine rollouts is still relevant. The previous works which categorize tourist sites and restaurants according to the perceived degree of tourists' and customers’ exposure to COVID-19 are deemed relevant for sectoral recovery. Due to the subjectivity of predetermining categories, along with the failure of capturing vagueness and uncertainty in the evaluation process, this work explores the use k-means clustering with dataset values expressed as interval-valued intuitionistic fuzzy sets. In addition, the proposed method allows for the incorporation of criteria (or attribute) weights into the dataset, often not considered in traditional k-means clustering but relevant in clustering problems with attributes having varying priorities. Two previously reported case studies were analyzed to demonstrate the proposed approach, and comparative and sensitivity analyses were performed. Results show that the priorities of the criteria in evaluating tourist sites remain the same. However, in evaluating restaurants, customers put emphasis on the physical characteristics of the restaurants. The proposed approach assigns 12, 15, and eight sites to the “low exposure”, “moderate exposure”, and “high exposure” cluster, respectively, each with distinct characteristics. On the other hand, 16 restaurants are assigned “low exposure”, 16 to “moderate exposure”, and eight to “high exposure” clusters, also with distinct characteristics. The characteristics described in the clusters offer meaningful insights for sectoral recovery efforts. Findings also show that the proposed approach is robust to small parameter changes. Although idiosyncrasies exist in the results of both case studies, considering the characteristics of the resulting clusters, tourists or customers could evaluate any tourist site or restaurant according to their perceived exposure to COVID-19.

scholarly journals Failure Mode and Effect Analysis (FMEA) with Extended MULTIMOORA Method Based on Interval-Valued Intuitionistic Fuzzy Set: Application in Operational Risk Evaluation for Infrastructure

Information ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 313 ◽  
Author(s):  
Lelin Lv ◽  
Huimin Li ◽  
Lunyan Wang ◽  
Qing Xia ◽  
Li Ji
Keyword(s):  
Failure Mode ◽  
Risk Evaluation ◽  
Failure Modes ◽  
Water Diversion ◽  
Weighted Averaging ◽  
Effect Analysis ◽  
Intuitionistic Fuzzy ◽  
Interval Valued ◽  
Multimoora Method ◽  
Evaluation Information

Failure Mode and Effect Analysis (FMEA) is a useful risk assessment tool used to identify, evaluate, and eliminate potential failure modes in numerous fields to improve security and reliability. Risk evaluation is a crucial step in FMEA and the Risk Priority Number (RPN) is a classical method for risk evaluation. However, the traditional RPN method has deficiencies in evaluation information, risk factor weights, robustness of results, etc. To overcome these shortcomings, this paper aims to develop a new risk evaluation in FMEA method. First, this paper converts linguistic evaluation information into corresponding interval-valued intuitionistic fuzzy numbers (IVIFNs) to effectively address the uncertainty and vagueness of the information. Next, different priorities are assigned to experts using the interval-valued intuitionistic fuzzy priority weight average (IVIFPWA) operator to solve the problem of expert weight. Then, the weights of risk factors are subjectively and objectively determined using the expert evaluation method and the deviation maximization model method. Finally, the paper innovatively introduces the interval-valued intuitionistic fuzzy weighted averaging (IVIFWA) operator, Tchebycheff Metric distance, and the interval-valued intuitionistic fuzzy weighted geometric (IVIFWG) operator into the ratio system, the reference point method, and the full multiplication form of MULTIMOORA sub-methods to optimize the information aggregation process of FMEA. The extended IVIF-MULTIMOORA method is proposed to obtain the risk ranking order of failure modes, which will help in obtaining more reasonable and practical results and in improving the robustness of results. The case of the Middle Route of the South-to-North Water Diversion Project’s operation risk is used to demonstrate the application and effectiveness of the proposed FMEA framework.

Transformation of agriculture risk management

2019 ◽  
Vol 79 (1) ◽  
pp. 136-155
Author(s):  
Ahmad Raza Bilal ◽  
Mirza Muhammad Ali Baig
Keyword(s):  
Risk Management ◽  
Risk Evaluation ◽  
Agricultural Sector ◽  
Risk Mitigation ◽  
Evaluation Process ◽  
Regulatory Compliance ◽  
Content Type ◽  
Farm Credit ◽  
Agriculture Risk

Purpose The purpose of this paper is to investigate the balanced role of internal and external compliance in risk evaluation process of specialized agriculture financing. The authors examine the adaptive behavior of risk managers to determine the role of proposed transformation for risk monitoring (RM) and control process in risk mitigation and avoidance of agriculture credit failure. Design/methodology/approach A self-administered survey was conducted to collect data from 353 risk-related officers and managers in Zarai Taraqiati Bank Limited (ZTBL) Pakistan. The authors used a previously tested scale for the main constructs. The descriptive analyses were used to gauge the model capacity for determining the strength of proposed risk patterns in agriculture risk management. Findings The results reveal that risk evaluation process in ZTBL is reasonably efficient in mitigating risks. Given the sensitive nature of farm credit, there is a need of fundamental reforms in risk policy manuals in line with central bank’s agriculture prudential regulations and Basel-III standards. The results fully support H1 and H2, while H3 is partially validated. The result patterns indicate serious issues in risk evaluation process in agriculture finance that is causing higher delinquency in farm credit. Research limitations/implications Based on highlighted issues, the authors recommend valuable guidelines in the RM review system for agriculture financing products at ZTBL. Practical implications The authors propose remodeling of agriculture risk management and offer valuable insights to the agriculture financial regulators and government in taking policy initiatives in the pre-and-post agriculture risk evaluation process. The proposed model enables RM process to improve farm credit delinquency, particularly in ZTBL and other agriculture banking networks in commercial banks. Originality/value This is the first study to empirically investigate RM evaluation process in agriculture risk management of ZTBL in Pakistan, thus, offers new horizon of farm credit regulatory compliance in agricultural sector of Pakistan.

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