Fuzzy Synthetic Evaluation Method Research Articles

Data Driven and Fuzzy Synthetic Evaluation Based Submarine Cable Health State Assessment

—Health state assessment is of great importance to ensure the safe and stable operation of submarine cables. Submarine cables have composite structural characteristics and work in complex and influential environments, which hinders manual inspection, arouses difficulties in maintenance, and causes challenges on health state assessment. To this end, a data driven and fuzzy synthetic evaluation based submarine cable health state assessment method is proposed in this paper. Firstly, following the technical guidelines of submarine cable health state assessment, dynamic submarine cable online monitoring data and static data including periodic preventive test and operation inspection results are integrated to build a three-layer index system. In addition, long and short-term memory (LSTM) neural network based ultra-short-term prediction models are built to obtain the predictions of online monitoring indices. On this basis, together with the static data, a fuzzy synthetic evaluation method is used to establish a two-stage state evaluation process to obtain the multi-period health states of submarine cables. The effectiveness of the proposed method is verified with an actual submarine cable from an offshore platform in an oilfield of China National Offshore Oil Corporation (CNOOC).

Adaptation and application of the fuzzy synthetic evaluation (FSE) method for characterizing the trophic state of tropical semiarid reservoirs.

Eutrophication is a recurrent problem in water bodies, especially in tropical semiarid reservoirs. The trophic state index (TSI) is an important tool for the environmental management of aquatic systems. However, determining the TSI involves uncertainties that can affect decision-making. This study aimed to adapt and apply the fuzzy synthetic evaluation (FSE) to characterize the TSI considering the uncertainties of the reference eutrophication classification system. The Castanhão reservoir, the largest in the State of Ceará, Brazil, was taken as a case study. The results showed that (i) the uncertainty of the trophic classification system can be characterized by the triangular and trapezoidal membership functions; (ii) the result matrix associates the global trophic level with a degree of certainty, providing greater confidence to the decision maker; (iii) the eutrophication index (EI) is not an adequate tool for hierarchizing the trophic degree; and (iv) the membership level of the global trophic state generated by the FSE method is a suitable alternative to the EI. It is concluded that the proposed FSE model can be a useful tool for improving water resources management, especially in drylands.

Hydrogeochemical Characteristics and Groundwater Quality in Phreatic and Confined Aquifers of the Hebei Plain, China

This study aims to investigate hydrogeochemical characteristics and groundwater quality in the Hebei Plain and to discuss factors controlling the groundwater quality. A total of 54 groundwater samples were collected and analyzed for 31 hydrogeochemical parameters, and a fuzzy synthetic evaluation (FSE) method was used for assessing groundwater quality. Results show groundwater total hardness, total dissolved solids (TDS), and major ions excluding K+ in phreatic aquifers higher than that in confined aquifers. From the Piedmont plain to the littoral plain, phreatic aquifers towards the reducing environment, and the enhancement of water–rock interaction, ion exchange process, and evaporation probably resulted in the increase in groundwater TDS, major ions (excluding HCO3− and SO42−), B, and Mn concentrations. Moreover, phreatic groundwater chemistry was mainly controlled by rock weathering changing into evaporite dissolution and seawater intrusion from the Piedmont plain to the littoral plain, according to the Gibbs diagram. The proportion of drinkable groundwater in confined aquifers was 1.6 times that in phreatic aquifers. In phreatic aquifers, the proportion of drinkable groundwater in the Piedmont plain was as high as 68%, but none of the drinkable groundwater occurred in the central and littoral plains. Groundwater quality in phreatic aquifers was mainly controlled by five factors, including the water–rock interaction, the marine geogenic sources, the agricultural pollution, the acidification, and the reductive environment. By contrast, groundwater quality in confined aquifers was mainly controlled by three factors, including the water–rock interaction and redox processes, agricultural pollution, and the input of external water. Therefore, in the Hebei Plain, groundwater in confined aquifers is more suitable for drinking purposes than in phreatic aquifers. Additionally, phreatic groundwater in the Piedmont plain should be protected.

Assessment of corporate social responsibility performance for Vietnamese construction organizations

Purpose Corporate social responsibility (CSR) performance is critical to address construction activities’ environmental and social impacts. This study aims to evaluate the level of CSR implementation across various categories within the context of the Vietnamese construction industry. Design/methodology/approach The literature review and semi-structured interviews were conducted to determine Vietnamese construction organizations’ most commonly implemented CSR activities. A total of 252 valid responses were then obtained through a questionnaire survey. In addition, the fuzzy synthetic evaluation (FSE) method was used to evaluate the extent to which CSR categories have been implemented in construction companies. Findings The findings revealed 31 commonly implemented CSR activities of the Vietnamese construction firms, which were grouped into four categories. Of the four categories, the FSE analysis showed that stakeholder CSR was the most critical category, followed by ethical CSR, philanthropic CSR and environmental CSR. Originality/value This research provides valuable CSR activities to construction companies that intend to develop sustainably. Moreover, the proposed prioritization methodology offers practitioners a reliable and easy-to-use evaluation tool that clearly understands CSR performance within their organizations.

Fuzzy quantitative risk allocation model (FQRAM) to guide decision-making on risk allocation in Ghanaian public-private partnership (PPP) power projects

PurposePublic-private partnership (PPP) power projects are associated with varying risk factors. This paper aims to develop a fuzzy quantitative risk allocation model (QRAM) to guide decision-making on risk allocation in PPP power projects in Ghana.Design/methodology/approachA total of 67 risk factors and 9 risk allocation criteria were established from literature and ranked in a two-round Delphi survey using questionnaires. The fuzzy synthetic evaluation method was used in developing the risk allocation model.FindingsThe model’s output variable is the risk allocation proportions between the public body and private body based on their capability to manage the risk factors. Out of the 37 critical risk factors, the public sector was allocated 12 risk factors with proportions = 50%, while the private sector was allocated 25 risk factors with proportions = 50%.Originality/valueTo the best of the authors’ knowledge, this research presents the first attempt in Ghana at endeavouring to develop a QRAM for PPP power projects. There is confidence in the model to efficiently allocate risks emanating from PPP power projects.

Depth-profiling analysis of ZnO layers with three morphologies by direct-current glow discharge mass spectrometry

In the fabrication of high-quality materials, information regarding the element concentration and distribution in the depth direction is particularly important. In this study, the potential applicability of direct-current glow discharge mass spectrometry (dc-GD-MS) was explored for depth-profiling analysis of zinc oxide (ZnO) layers on steel substrates. The ZnO layers on steel substrates presented three morphologies of thin films, network textures and nanorods fabricated by magnetron sputtering (ZnO-1/steel), sol–gel method (ZnO-2/steel) and hydrothermal synthesis (ZnO-3/steel), respectively. The discharge conditions were optimized based on dc-GD-MS to obtain the ideal depth resolutions. The results revealed that compared with ZnO layers of ZnO-2/steel and ZnO-3/steel, the dc-GD-MS depth-profiling analysis of ZnO-1/steel presented superior performance with depth resolution of 0.22 μm and a clear interface between ZnO layer and steel substrate. dc-GD-MS depth-profiling analysis suggested that the ZnO layer morphology, thickness and sputtering rate could affect the depth resolution. Furthermore, the fuzzy synthetic evaluation method (FSEM) suggested that the layer morphology had a greater impact on the depth resolutions than thickness and sputtering rate under the optimized discharge conditions. The study presented an efficient and sensitive approach for determining the elemental concentrations and distributions of semi-conducting materials, offering novel insights into material fabrication.

Evaluation of the Critical risk factors in PPP - procured Mass Housing Projects in Abuja Nigeria - A fuzzy synthetic evaluation (FSE) approach

The study accessed the critical risk factors in public-private partnership procured mass housing project (PPP-MHP) delivery in Nigeria. The research design adopts a quantitative approach, using well-structured questionnaires distributed to stakeholders involved in PPP-MHPs i.e. the consultants, in-house professionals, contractors, and the organized private sector (OPS) registered with PPP departments of the Federal Capital Territory Development Authority (FCDA) Abuja, Nigeria. The instrument relates to the background information of respondents and the risk peculiar to PPP-MHP. Sixty-three (63) risk factors were submitted for the respondents to rank on a Likert scale of 7 using Mean Item score (MIS) for risk occurrence and its severity, while the risk significance index (RI) was used to determine the risk impact. Fuzzy Synthetic Evaluation (FSE) method was subsequently applied to determine the risk criticality groups and the overall risk level in the sector. The findings show that thirty-one (31) risk factors were critical in the sector while the financial and micro-economic risk group is contributing most significantly to the overall risk level in PPP-MHPs in Nigeria. The implication for practice is that having known the risk group contributing most significantly to the overall risk level in PPP-MHPs, adequate financial and budgetary allocation should be made available before embarking on a such venture to sustain the scheme in the country. The study is one of the recent research conducted on housing since the procurement option is novel in the sector. The study is of immense value to PPP actors by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP MHPs.

Modeling the principal success factors for attaining systemic circularity in the building construction industry: An international survey of circular economy experts

To achieve zero waste and cumber the acute environmental effect of the building construction industry (BCI), circular economy (CE) implementation is pertinent. Such implementation requires the incorporation of certain actionable factors that are critical to its success. However, investigating these factors considering the individualistic variations of developed and developing economies is rarely conducted in the literature. Therefore, this study evaluated the critical success factors (CSFs) for attaining systemic circularity in the BCI of both developed and developing economies. The methodological framework adopted comprises a literature review and a questionnaire survey of 140 CE experts across 39 developed and developing economies. The data collected was analyzed using exploratory factor analysis (EFA), rank agreement analysis (RAA), and fuzzy synthetic evaluation (FSE) techniques. The EFA analysis revealed four principal success factors (PSFs): data-driven digital tools and circularity plan, capacity building and pre-demolition auditing, systemic circularity guidelines and commitment, and circular metric and secondary market development. The RAA results showed that consensus and non-consensus exist between the two groups (developed and developing economies) on the PSFs. The FSE method revealed that all the PSFs are paramount in achieving a successful CE implementation in the two economies. However, the top two in developed economies are systemic circularity guidelines and commitment, and circular metric and secondary market development, while data-driven digital tools and circularity plans, and capacity building and demolition monitoring are the top two in developing economies. The RAA findings underscore the need to be context conscious while adopting the CSFs for CE implementation in the BCI. The FSE findings and the PSF models developed would guide the government and management teams in resource allocation during CE implementation. This study contributes to existing knowledge by providing essential insights into the CSFs that would promote systemic circularity attainment in the BCI of developed and developing economies.

A clustering-based energy consumption evaluation method for process industries with multiple energy consumption patterns

ABSTRACT The production systems in process industries are confirmed to be tremendously energy-consuming, and the trust in promoting their energy efficiency has become a concern, with its precondition being to evaluate the real-time energy consumption. A widespread evaluation method is to develop a global model that employs energy audit techniques, whereas they are always carried out with few appreciations of multiple energy consumption patterns, and the utilization of energy consumption auxiliary information. To address the challenge, a two-stage clustering-based-energy consumption evaluation method is proposed for process industries in this study. Specifically, a novel structure of the fuzzy clustering method is designed with a mixture of unsupervised and semi-supervised learning stages that leverages the weighted information to independently address energy consumption patterns. Then energy consumption predictions are estimated for potential energy-optimized control. The key performance indicators of energy consumption are calculated for each pattern, and the final evaluation grade will be achieved through the fuzzy synthetic evaluation method. According to the experiment results, the proposed method delivers better evaluation results against baselines with more accurate clustering; it may provide a new thought for energy consumption evaluation and is confirmed to enable practitioners to acquire the potential benefits in engineering.

Evaluating a driving index of nonresidential green building implementation for sustainable development in developing countries from a Vietnamese perspective

AbstractThe purpose of this study is to evaluate a quantitative driving index for implementing green building in Vietnam as a case study in developing countries. Using literature review and expert interviews, 19 driving forces affecting green building implementation were identified in the Vietnamese context. Via obtained data from a questionnaire survey, four principle factors were grouped from defined drivers. The fuzzy synthetic evaluation method was utilized to develop a driving index (DI) for developing the green building in Vietnam. DI model indicated that environmental impact is the most crucial group for green building implementation in Vietnam. Apart from this, the result of the comparative analysis also indicated that most driving forces for adopting green building in developing countries related to environmental and social problems. These results provide the decision‐makers with a comprehensive tool to assess the expectations for green building implementation in both Vietnam and other developing countries.

Hydrogeochemical Characteristics and Groundwater Quality in a Coastal Urbanized Area, South China: Impact of Land Use

Land use transformation accompanied with various human activities affects groundwater chemistry and quality globally, especially in coastal urbanized areas because of complex human activities. This study investigated the impact of land use on groundwater chemistry and quality in a coastal alluvial aquifer (CAA) of the Pearl River Delta where urbanization continues. A fuzzy synthetic evaluation method was used to evaluate the groundwater quality. Besides, factors controlling groundwater chemistry and quality in the CAA were discussed by using a principal components analysis (PCA). Nearly 150 groundwater samples were collected. All samples were filtered on-site and stored at 4 °C until the laboratory procedures could be performed. Nineteen chemical parameters including pH, dissolved oxygen, redox potential, total dissolved solids, K+, Na+, Ca2+, Mg2+, NH4+, HCO3−, NO3−, SO42−, Cl−, I−, NO2−, Pb, Mn, Fe, and As were analyzed. Results show that groundwater chemistry in the CAA was dominated by Ca-HCO3 and Ca·Na-HCO3 facies. In addition, groundwater with NO3 facies was also present because of more intensive human activities. In the CAA, 61.8% of groundwaters were fit for drinking, and 10.7% of groundwaters were undrinkable but fit for irrigation, whereas 27.5% of groundwaters were unfit for any purpose. Poor-quality groundwaters in urban and agricultural areas were 1.1–1.2 times those in peri-urban areas, but absent in the remaining area. Groundwater chemistry and quality in the CAA was mainly controlled by five factors according to the PCA. Factor 1 is the release of salt and NH4+ from marine sediments, and the infiltration of domestic and septic sewage. Factor 2 is agricultural activities related to the irrigation of river water, and the use of chemical fertilizers. Factor 3 is the industrial pollution related to heavy metals and acid deposition. Factor 4 is the input of anthropogenic reducing sewage inducing the reductive dissolution of As-loaded Fe minerals and denitrification. Factor 5 is the I− contamination from both of geogenic and anthropogenic sources. Therefore, in order to protect groundwater quality in coastal urbanized areas, repairing old sewer systems in urban areas, building sewer systems in peri-urban areas, limiting sewage irrigation and the amount of chemical fertilizers application in agricultural areas, as well as strengthening the supervision of the industrial exhaust gas discharge in urban and peri-urban areas are recommended.

Assessment of symmetries and asymmetries on barriers to circular economy adoption in the construction industry towards zero waste: A survey of international experts

This study evaluates simultaneously the symmetries and asymmetries on the classification of barriers to circular economy (CE) adoption in the building construction industry (BCI) of developing and developed economies. This is crucial because the vagueness of the impacts of CE barriers in extant studies affects encyclopaedic and specific CE policy formulation. Consequently, feedbacks from 140 CE experts across 39 developing and developed economies were analysed. Fuzzy synthetic evaluation (FSE) method was deployed to objectively determine the significant impacts of the barriers, whereas the Mann-Whitney U test was applied to identify significant differences in experts' opinions between the two economies. The FSE results indicated that organizational, information technology, and infrastructure and logistics barriers are the most critical to global CE adoption. The Mann-Whitney U test reveals a significant difference in the experts’ perspectives between developing and developed economies on regulatory, information technology, and economic and market barriers. Therefore, they are perceived as specific barriers as they impact CE adoption in BCI differently across the two economies. However, infrastructure and logistics, and organizational barriers are classified as general barriers. The findings of this study underscored the contextuality of barriers to CE adoption in BCI and demonstrated the need for generic and specific policy development. Also, the significance indices of the classification of the barriers using FSE method serve as an allocative function that will help policymakers and stakeholders allocate requisite resources to the most profound barriers towards achieving global systemic circularity and zero construction waste.

An indicator framework for assessing the readiness of hospital in the smart healthcare transformation

The technical and management issues that existed in traditional healthcare institutions, such as relatively lagging technologies, untimely information, have received increasing attention. In recent decades, the reconstruction or transformation of smart healthcare system has emerged as a new research trend. Especially with the outbreak of the COVID-19 epidemic, the smart healthcare system realizes the timely allocation of medical resources and sharing of information. Therefore, this paper aims to develop an indicator framework for assessing the hospital’s readiness in transforming towards smart healthcare. First, based on the literature review, an indicator framework of readiness of smart healthcare transformation is developed for smart healthcare transformation, which includes three hierarchies of “ smart facility management (smart FM)”, “medical system (MS)” and “organizational management (OM)”. Secondly, an online questionnaire survey is conducted to test the validity of the indicator framework. Based on factor analysis, the indicator framework is proved to be effective as a whole, and all the 26 indicators are significant. Finally, the readiness of case hospital “A” in the smart healthcare transformation is examined by fuzzy synthetic evaluation method. The findings of this paper provide an assessment tool for medical institutions to self-evaluate their status in the information construction process.

Supply chain risk factor assessment of Indian pharmaceutical industry for performance improvement

PurposeThe purpose of the present work is to improve the industry performance by identifying and quantifying the risks faced by the Indian pharmaceutical industry (IPI). The risk values for the prominent risks and overall industry are determined based on the four risk parameters, which would help determine the most contributive risks for mitigation.Design/methodology/approachAn extensive literature survey was done to identify the risks, which were also validated by industry experts. The finalized risks were then evaluated using the fuzzy synthetic evaluation (FSE) method, which is the most suitable approach for the risk assessment with parameters having a set of different risk levels.FindingsThe three most contributive sub-risks are counterfeit drugs, demand fluctuations and loss of customers due to partners' poor service performance, while the main risks obtained are demand, financial and logistics. Also, the overall risk value indicates that the industry faces medium to high risk.Practical implicationsThe study identifies the critical risks which need to be mitigated for an efficient industry. The industry is most vulnerable to the demand risk category. Therefore, the managers should minimize this risk by mitigating its sub-risks, like demand fluctuations, bullwhip effect, etc. Another critical sub-risk, the counterfeit risk, should be managed by adopting advanced technologies like blockchain, artificial intelligence, etc.Originality/valueThere is insufficient literature focusing on risk quantification. Therefore, this work addresses this gap and obtains the industry's most critical risks. It also discusses suitable mitigation strategies for better industry performance.

Resilient reverse logistics with blockchain technology in sustainable food supply chain management during COVID‐19

AbstractCOVID‐19, which is a global problem, affects the all supply chains throughout the world. One of the supply chains most affected by COVID‐19 is food supply chains. Since the sustainable food supply chain processes are complex and vulnerable in terms of product variety, it has been negatively affected by the operational effects of COVID‐19. While the problems experienced in the supply chain processes and raw material constraints caused stops in production, the importance of new business models and production approaches came to the fore. One of the issues of increasing importance is the adoption of reverse logistics activities in sustainable food supply chains and increasing the resilience of food supply chains by integrating blockchain technology into processes. However, adapting blockchain technology to increase the resilience of reverse logistics activities in the food supply chain has advantages as well as risks that need to be considered. Therefore, it is aimed to determine these risks by using fuzzy synthetic evaluation method for eliminating the risks of blockchain adaptation for flexible reverse logistics in food supply chains to increase resiliency. The novelty of this study is that besides discussing about the benefits of BC‐T, it is to identify the risks it can create, to eliminate these risks and to guide the establishment of resilience in reverse logistics activities of SFSCs. According to results, the risks with the highest value among the subrisks are determined as data security risks. Data management risks are calculated as the risk with the highest value.

Property managers’ awareness of the potential benefits of vertical greenery systems on buildings

Many human activities are carried out in buildings, suggesting that the contribution of buildings to global warming is significant. This study examines the awareness of property managers (estate surveyors and valuers) about the potential benefits of vertical greenery systems (VGSs) on buildings. The questionnaire for the study was administered online to property managers working with registered estate surveying and valuation firms operating in Lagos. On firm basis, a total of 282 property managers working for the firms were considered. Of this total, 127 responded to the questionnaire, but 121 (representing 42.9%) were of use in the analysis of data. The data were analyzed using the fuzzy synthetic evaluation method. The result showed that property managers were generally less aware, with an overall awareness level of 2.60. Further analysis showed that the property managers were less aware of the benefits of VGSs on buildings. The levels of awareness of the property managers about VGSs' environmental benefits, social benefits, and economic benefits are 2.65, 2.58, and 2.53 respectively. We conclude that an improvement in the level of awareness of the property managers would assist in the formulation of policies by the government towards the achievement of SDGs.

Abnormal-Aware Multiperson Evaluation System with Improved Fuzzy Weighting

There exists a phenomenon that subjectivity highly lies in the daily evaluation process. Our research primarily concentrates on a multiperson evaluation system with anomaly detection to minimize the possible inaccuracy that subjective assessment brings. We choose the two-stage screening method, which consists of rough screening and score-weighted Kendall-τ distance to winnow out abnormal data, coupled with hypothesis testing to narrow global discrepancy. Then we use fuzzy synthetic evaluation method (FSE) to determine the significance of scores given by reviewers as well as their reliability, culminating in a more impartial weight for each reviewer in the final conclusion. The results demonstrate a clear and comprehensive ranking instead of unilateral scores, and we get to have an efficiency in filtering out abnormal data as well as a reasonably objective weight determination mechanism. We can sense that through our study, people will have a chance of modifying a multiperson evaluation system to attain both equity and a relatively superior competitive atmosphere. A preprint has previously been published (Ni, 2022).

Research on Psychology Evaluation Method of Nuclear Power Plant Operators

Nuclear power plant operators play a more and more important part to plant safe operation. The paper analyzes and discusses the qualitative and quantitative evaluation methods for the operators. The comparison-analysis of the scope and result of application has been done between the method of outline figure fitted and the method of fuzzy synthetic evaluation. The research can be referenced in the evaluation of operators.

A comprehensive risk assessment model based on a fuzzy synthetic evaluation approach for green building projects: the case of Vietnam

PurposeRisks in implementing green building (GB) projects have emerged as a significant obstacle for GB development, especially in developing countries. In recent years, both academics and construction practitioners have paid considerable attention to the risks associated with GB. In this study, the authors aimed to create a comprehensive risk assessment model that considers three crucial risk features: impact level, probability of occurrence and risk manageability.Design/methodology/approachIn the research, authors adopted the mean scoring and fuzzy synthetic evaluation method to assess GB risks. Based on expert assessments, this model can determine the significance of risk factors, risk groups and overall risk. Notably, this research applied the proposed model to assess GB risks in Vietnam by surveying 58 GB experienced professionals.FindingsThe findings revealed that GB risks are relatively high in Vietnam, implying that risk management is essential for GB projects to succeed. The results also showed that “lack of experience of GB designers” is the most critical factor, and “human resources risk in the design phase” is the top crucial risk group.Originality/valueThis study contributes a novel and practical model to help practitioners assess risks in GB projects. In addition, this research offers detailed GB risk evaluations in Vietnam and thus could be a valuable reference for construction practitioners and future studies.

Risk Identification and Assessment of PPP Forestry Projects in China Using a Fuzzy Synthetic Evaluation Approach

At present, the Chinese government is vigorously promoting the use of PPP mode to attract social capital and financial capital into the field of forestry, including ecological construction, protection and utilization, which is of great significance for promoting the construction of ecological civilization and the development of both the economy and the society. Because the financing, organization, implementation and environmental factors of PPP forestry projects are relatively complicated, there are certain risks for both the government and social capital. In order to evaluate the risks of China's forestry projects for the government and social capital, 43 risk factors were identified and divided into 4 groups based on Delphi method and questionnaire survey. 23 key risk factors were selected according to the standardized values. Then, the probability of occurrence (PO), impact size (IS) and overall risk level (ORL) of each key factor were determined by fuzzy synthetic evaluation(FSE) method, and each KRF, KRG and overall risk level (ORL) were calculated. Based on the results, "Government Decision Risk" in KRF was the most critical risk factor, and KRG "Financial Risk" was the most critical risk factor group. Overall, fuzzy comprehensive results showed that the ORL of China's forestry PPP project is relatively high. According to the analysis results, countermeasures were put forward. The research results could provide reference for all participants in PPP forestry projects to make decisions, and formulate a comprehensive risk management plan to use limited resources. In addition, this study could expand professional knowledge and enrich relevant results.