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1 – 10 of over 27000Yuhang Zhang, Yan Huang, Tingting Xu, Chang Liu and Liangyan Tao
The classification of aircraft failures has been a significant part of functional hazard analysis (FHA). Aiming at the shortcomings of the traditional FHA method in the evaluation…
Abstract
Purpose
The classification of aircraft failures has been a significant part of functional hazard analysis (FHA). Aiming at the shortcomings of the traditional FHA method in the evaluation of aircraft risk, the purpose of this paper is to put forward a new approach by combining the gray comprehensive relation calculation method in the gray system theory with the traditional FHA in order to deal with the problem of “little data, poor information.”
Design/methodology/approach
This paper combines FHA, 1–9-scale method and gray relation analysis. At first, aircraft failure scenarios are chosen and data from experts are collected; then gray system theory is applied to find the relevance of such scenarios. Finally, the classification according to relevance is determined.
Findings
In the past, “little data, poor information” made it difficult for researchers to implement FHA. In this paper, the authors manage to deal with the problem of “poor information” and provide an approach to find the seriousness of aircraft failure.
Research limitations/implications
Due to the use of expert-evaluating methods, the classification of failures is still a little subjective and can be improved in this area. In the future, the method can be improved from the perspective of combining FMEA to analyze more complex indicators or using multisource heterogeneous solutions to solve fuzzy numbers, probabilities, gray numbers and indicators that cannot be assigned.
Practical implications
The paper uses FHA to divide the failure state and establishes a gray evaluation model of the aircraft failure state classification to verify the relevant method. Some aircraft safety design requirements are used to check the safety hazards of the aircraft during the design process, and to provide rational recommendations for the functional design of the aircraft.
Social implications
Improving the safety of aircraft is undoubtedly of great practical significance and has become a top priority in the development of the civil aviation industry. In this paper, the FHA method and the failure state of the aircraft are studied. The original FHA method is innovated by using the gray system theory applicable to the poor information state. Therefore, to some extent, this study has significance for improving the safety of civil aircraft flight, ensuring people’s travel safety and enhancing the society’s trust in civil aviation.
Originality/value
The main innovation of this paper is integrating the FHA method and the gray system theory. This study calculates the comprehensive relation degree of each failure under different flight stages, and uses FHA to divide the failure state, and finally establishes a gray evaluation model of the aircraft failure state classification to analyze the different conditions of the landing gear brake system, so that it improves the present situation, and the problem with the character of “little data, poor information” can be addressed better.
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Caiyun Sun and Li Shi
The purpose of this paper is to evaluate doctoral candidates’ innovative ability tendency.
Abstract
Purpose
The purpose of this paper is to evaluate doctoral candidates’ innovative ability tendency.
Design/methodology/approach
This study uses the theory of gray target contribution to analyze the influence degree of doctoral candidates’ individual personality factor toward their innovative ability and calculate gray impact quantitative values.
Findings
Based on the theory of contribution degree of gray target, a nine-factor model of innovative personality of doctoral candidates is built. IP=f (B, H, G, Q1, Q2, A, I, F, O), (therein: B – intelligence, H – social boldness, G – perseverance, Q1 – experimental, Q2 – independence, A – gregariousness, I – sensibility, F – excitability, O – anxiety).
Practical implications
This study based on gray target contribution theory builds nine-factor doctoral candidates’ innovative personality model to test the innovative ability tendency of doctoral candidates, which makes cultivating units, mentors and doctoral candidates to know their innovative ability tendency well, perfecting their own knowledge structure in time, effectively improving their innovative ability. The system can also be applied to the work of doctoral candidates as a reference tool to evaluate the innovative ability of applicants.
Originality/value
This study quantitatively evaluates the influence of doctoral candidates’ personality index on the tendency of doctoral candidates’ innovative ability.
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This study aims to use gray models to predict abnormal stock returns.
Abstract
Purpose
This study aims to use gray models to predict abnormal stock returns.
Design/methodology/approach
Data are collected from listed companies in the Tehran Stock Exchange during 2005-2015. The analyses portray three models, namely, the gray model, the nonlinear gray Bernoulli model and the Nash nonlinear gray Bernoulli model.
Findings
Results show that the Nash nonlinear gray Bernoulli model can predict abnormal stock returns that are defined by conditions other than gray models which predict increases, and then after checking regression models, the Bernoulli regression model is defined, which gives higher accuracy and fewer errors than the other two models.
Originality/value
The stock market is one of the most important markets, which is influenced by several factors. Thus, accurate and reliable techniques are necessary to help investors and consumers find detailed and exact ways to predict the stock market.
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The purpose of this paper is to develop a system to analyse the characteristics of infrared objects.
Abstract
Purpose
The purpose of this paper is to develop a system to analyse the characteristics of infrared objects.
Design/methodology/approach
According to the gray scale of image pixel by the image entropy, gray scale estimating is carries on to construct the neural networks. And then the grey relational analysis and grey clustering methods are applied to filter the possible object. The target is predicted through image segmentation pretreatment based on the forecasting value by grey system and assigned corresponding mark. The forecasting precision is greatly elevated by GM (1, 1) model.
Findings
The paper illustrates that, based on the analysis and its experimental results, this system has a good recognition rate for infrared target.
Research limitations/implications
This paper provides a way to grasp the minutial feature of the image. The filtering operation based on pixel level provided auto‐adapted filtering with a new stage.
Practical implications
Applications of grey theory deepened the content of detecting infrared targets and enriched technology of image processing.
Originality/value
This system introduces an effective method for detecting infrared targets.
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Manouchehr Omidvari, Seyyed Morteza Abootorabi and Hossein Mehrno
The statistical report published by the Iranian Social Security Organization in 2012 showed that, of all industries, the construction industry is associated with the highest…
Abstract
Purpose
The statistical report published by the Iranian Social Security Organization in 2012 showed that, of all industries, the construction industry is associated with the highest number of work-related accidents. Furthermore, as this sector contains a large human workforce, identification of the factors contributing to the occurrence of such accidents is vital. The paper aims to discuss these issues.
Design/methodology/approach
Furthermore, as this sector contains a large human workforce, identification of the factors contributing to the occurrence of such accidents is vital. In the present study, such factors were initially identified, after which the most important of these, managerial factors, were selected. Subsequently, the identification of the causes of the managerial factors was carried out with the use of the fault tree analysis (FTA) method and application of OR and AND entries.
Findings
Since it is difficult to determine the probability of occurrence of events in this industry with certainty, and because gray numbers (numbers of which the exact value is unknown, and which represent uncertain information) have a strong relationship with human expressions, the probability of occurrence of the main undesired events was also evaluated using the gray numbers as input entries, in addition to ranking the probability of occurrence of intermediate events.
Originality/value
The findings revealed that FTA using gray numbers is a useful and effective tool in risk assessment.
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Samira Nadafi, Seyed Hamed Moosavirad and Shahram Ariafar
The purpose of this paper is to determine the project completion time and cost under non-deterministic conditions using interval gray numbers (IGNs).
Abstract
Purpose
The purpose of this paper is to determine the project completion time and cost under non-deterministic conditions using interval gray numbers (IGNs).
Design/methodology/approach
The earned value management (EVM) method based on the IGN has been developed.
Findings
The EVM method based on the IGN has been verified by a numerical example that can be applied to construction projects.
Practical implications
The EVM method, based on the gray numbers, reduces the budget and time shortage risk. Also, using this method, the managers would not be restricted to provide very exact values in their progress reports in the non-deterministic conditions.
Originality/value
One notable and significant point in all projects during the execution process is to estimate the project completion time and cost. However, non-deterministic conditions for both planned and actual physical completion percentage of projects have not been considered for predicting the project completion time and cost in the literature. Therefore, the novelty of this paper is the prediction of project completion time and cost under non-deterministic conditions using IGN.
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Camelia Delcea, Saad Ahmed Javed, Margareta-Stela Florescu, Corina Ioanas and Liviu-Adrian Cotfas
The Grey System Theory (GST) is an emerging area of research within artificial intelligence. Since its founding in 1982, it has seen a lot of multidisciplinary applications. In…
Abstract
Purpose
The Grey System Theory (GST) is an emerging area of research within artificial intelligence. Since its founding in 1982, it has seen a lot of multidisciplinary applications. In just a short period, it has garnered some considerable strengths. Based on the 1987–2021 data collected from the Web of Science (WoS), the current study reports the advancement of the GST.
Design/methodology/approach
Research papers utilizing the GST in the fields of economics and education were retrieved from the Web of Science (WoS) platform using a set of predetermined keywords. In the final stage of the process, the papers that underwent analysis were manually chosen, with selection criteria based on the information presented in the titles and abstracts.
Findings
The study identifies prominent authors, institutions, publications and journals closely associated with the subject. In terms of authors, two major clusters are identified around Liu SF and Wang ZX, while the institution with the highest number of publications is Nanjing University of Aeronautics and Astronautics. Moreover, significant keywords, trends and research directions have been extracted and analyzed. Additionally, the study highlights the regions where the theory holds substantial influence.
Research limitations/implications
The study is subject to certain limitations stemming from factors such as the language employed in the chosen literature, the papers included within the Web of Science (WoS) database, the designation of works categorized as “articles” in the database, the specific selection of keywords and keyword combinations, and the meticulous manual process employed for paper selection. While the manual selection process itself is not inherently limiting, it demands a greater investment of time and meticulous attention, contributing to the overall limitations of the study.
Practical implications
The significance of the study extends not only to scholars and practitioners but also to readers who observe the development of emerging scientific disciplines.
Originality/value
The analysis of trends revealed a growing emphasis on the application of GST in diverse domains, including supply chain management, manufacturing and economic development. Notably, the emergence of COVID-19 as a new research focal point among GST scholars is evident. The heightened interest in COVID-19 can be attributed to its global impact across various academic disciplines. However, it is improbable that this interest will persist in the long term, as the pandemic is gradually brought under control.
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The paper aims to propose a clustering model for panel data. More specifically, the paper aims to construct a gray incidence model for panel data to solve the classification with…
Abstract
Purpose
The paper aims to propose a clustering model for panel data. More specifically, the paper aims to construct a gray incidence model for panel data to solve the classification with multi-factors and multi-attributes.
Design/methodology/approach
The paper opted for a clustering theory study using gray incidence theory based on dynamic weighted function. The paper presents an example to verify the rationality of the new model, which suggests that the new model can reflect the incidence degree of panel data.
Findings
The paper provides a new gray incidence model based on a dynamic weighted function that can amplify the characteristics of the sample to some extent. The properties of the new incidence model, such as normalization, symmetry and nearness, are all satisfied. The paper also shows that the new incidence model performs very well on cluster discrimination.
Originality/value
The new model in this paper has supplemented and improved the gray incidence analysis theory for panel data.
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Changhai Lin, Zhengyu Song, Sifeng Liu, Yingjie Yang and Jeffrey Forrest
The purpose of this paper is to analyze the mechanism and filter efficacy of accumulation generation operator (AGO)/inverse accumulation generation operator (IAGO) in the…
Abstract
Purpose
The purpose of this paper is to analyze the mechanism and filter efficacy of accumulation generation operator (AGO)/inverse accumulation generation operator (IAGO) in the frequency domain.
Design/methodology/approach
The AGO/IAGO in time domain will be transferred to the frequency domain by the Fourier transform. Based on the consistency of the mathematical expressions of the AGO/IAGO in the gray system and the digital filter in digital signal processing, the equivalent filter model of the AGO/IAGO is established. The unique methods in digital signal processing systems “spectrum analysis” of AGO/IAGO are carried out in the frequency domain.
Findings
Through the theoretical study and practical example, benefit of spectrum analysis is explained, and the mechanism and filter efficacy of AGO/IAGO are quantitatively analyzed. The study indicated that the AGO is particularly suitable to act on the system's behavior time series in which the long period parts is the main factor. The acted sequence has good effect of noise immunity.
Practical implications
The AGO/IAGO has a wonderful effect on the processing of some statistical data, e.g. most of the statistical data related to economic growth, crop production, climate and atmospheric changes are mainly affected by long period factors (i.e. low-frequency data), and most of the disturbances are short-period factors (high-frequency data). After processing by the 1-AGO, its high frequency content is suppressed, and its low frequency content is amplified. In terms of information theory, this two-way effect improves the signal-to-noise ratio greatly and reduces the proportion of noise/interference in the new sequence. Based on 1-AGO acting, the information mining and extrapolation prediction will have a good effect.
Originality/value
The authors find that 1-AGO has a wonderful effect on the processing of data sequence. When the 1-AGO acts on a data sequence X, its low-pass filtering effect will benefit the information fluctuations removing and high-frequency noise/interference reduction, so the data shows a clear exponential change trends. However, it is not suitable for excessive use because its equivalent filter has poles at the non-periodic content. But, because of pol effect at zero frequency, the 1-AGO will greatly amplify the low-frequency information parts and suppress the high-frequency parts in the information at the same time.
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R.M. Ammar Zahid, Muhammad Kaleem Khan and Volkan Demir
Current research aims to investigate the relationships between Chinese national cultural values (uncertainty avoidance (UA), power distance, masculinity (MAS), individualism (IDV…
Abstract
Purpose
Current research aims to investigate the relationships between Chinese national cultural values (uncertainty avoidance (UA), power distance, masculinity (MAS), individualism (IDV) and Confucian dynamism) and accounting practices (professionalism, uniformity, conservatism and secrecy).
Design/methodology/approach
A sample of 842 users/preparers of financial statements participated in this cross-sectional, questionnaire-based survey from China. Covariance-based structural equation modeling (CB-SEM) was used to test the proposed relationship.
Findings
Results show that cultural values strongly impact financial reporting practices in China. Chinese society is characterized by low UA, high power distance, collectivism, future orientation (Confucianism) and masculine traits. These values show an overall preference for uniformity, conservatism and secrecy in financial reporting with weak professionalism. The findings show that Chinese society emphasizes law abidance, strict codes of conduct, written rules and regulations and respect for consistent orthodox measures.
Practical implications
This study provides valuable input for policymakers in developing regulations and accounting standards in the Chinese market. Understanding the relationship between cultural dimensions and accounting values helps to address societal challenges and align policies with cultural values to acquire desired financial reporting values. Global firm managers must consider cultural dimensions in accounting when entering Chinese markets or negotiating with partners from different cultures. Findings also suggest local managers gain self-awareness of their cultural biases and accounting values, enabling them to navigate businesses and society's financial reporting needs.
Originality/value
This study enriches the existing literature on cultural and accounting practice studies by validating the role of stakeholder and social contract theories in Gray–Hofstede’s framework and highlighting the influence of dominant cultural values on accounting values. The study provides a unique empirical analysis of the Chinese market by using a questionnaire survey and structural equation modeling (SEM). Further, it also opens avenues for future research on the relationship between cultural dimensions, accounting practices and their global impact. These findings emphasize the importance of cultural sensitivity and adaptability, especially in multicultural environments.
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