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The cumulative sum (Cusum) operator, also referred to as accumulating generation operator, is the fundamental of grey system models and proves to be successful in various real-world applications. This paper aims to uncover the advantages of the Cusum operator from a parameter estimation perspective, i.e. comparing integral matching with classical gradient matching.

Grey system models are represented as a state space form to investigate the effect of measurement errors on estimation performance; subsequently, gradient matching and integral matching are respectively formulated to estimate parameters from noisy observations and, then, their quantitative relationships are established by using matrix computation tricks.

Extensive simulations, which are conducted on both linear and non-linear models under different sample size and noise level combinations, show that integral matching is superior to gradient matching, and, also the former is less sensitive to measurement error.

This paper explains why the Cusum operator is widely utilized in grey system models, thereby further solidifying the mathematical fundamentals of grey system models.

This paper aims to reduce the confliction between different retail channels.

By investigating a game-theoretic model consisting of a dominant hotel, a promoter and an OTA, the authors analyze the optimal amount of reserved rooms on the hotel's official website and realize the coordination between the hotel and the promoter with an appropriate contact.

When the gap between promoter’s reservation profits under different promotion cost coefficients is reasonable, complete coordination can be achieved in the supply chain. In addition, numerical examples are conducted to show that the profit of hotel and supply chain can be maximized with a moderate amount of reserved rooms on OTA.

The authors only focus on one OTA scenarios, which overlooks the competition between OTAs.

Coordination strategy can fierce the increase on profit when the customer conversion rate increases.

The authors propose a contract menu to help the hotel avoid the profit loss under asymmetric promotion cost information.

The purpose of this paper is to examine the potential economic impacts of China’s insect-resistant GM maize and provide new evidence for decision making concerning its commercialization.

This study uses data drawn from the production trials of insect-resistant GM maize and expert interviews to determine the impacts of commercializing GM maize at farm level under three scenarios with varying severity of insect pest attacks in maize production. Economic impacts are simulated using a modified Global Trade Analysis Project model.

In farm terms, insect-resistant GM maize increases crop yield and reduces both pesticide and labor inputs. In national terms, China can increase its GDP by USD8.6 billion and maize self-sufficiency by about 2 percent given normal insect pest attacks if China commercializes GM maize. Additional beneficiaries include consumers and the livestock industry. Non-maize crops can also benefit from land saving through GM maize commercialization. Chemical is a sector with the decrease in its output because demand for pesticides will fall.

Although China has announced a roadmap for commercializing GM crops for use as feed and in processing after nearly two decades of producing GM cotton, no clear timetable for producing GM maize as feed has been established due to several concerns, including the potential for economic gains from GM maize. This study is the first to assess the economic impacts of commercializing China’s GM maize. The findings should have significant policy implications for the development and commercialization of GM crops in general and GM maize in particular.

Piston ring dynamic problem plays an important role in the lubricant characteristics of a reciprocating engine, which lead to engine wear and the increased consumption of lubricating oil. A cavitation analysis of the piston ring lubrication with two-dimensional Reynolds equation has rarely been reported owing to the complex working condition. The purpose of this study is to establish a precise model that can provide guidance for the design of the piston ring.

In this paper, a cavitation model and its effect on the piston ring lubrication was studied in a simulation program based on the mass-conserving theory which is solved by means of the Newton–Raphson method. In this study, some models such as mixed lubrication, asperity contact, blow-by/blow-back flow and cavitation have been coupled with the lubrication model.

The established model has been compared with the traditional model that deals with cavitation by using the Reynolds boundary condition algorithm. The cavitation zone, pressure distribution and density distribution between the piston ring and the cylinder have also been predicted. Studies of the changing trend for the pressure distribution and the cavitation zone at few typical crank angles have been listed to illustrate the cavitation changing rule. The analysis of the results indicates that the developed simulation model can adequately illustrate the lubrication problem of the piston ring system. All the analyses will provide guidance for the oil film rupture and the reformation process.

A two-dimensional cavitation model based on the mass-conserving theory has been built. The cavitation-forming and -developing process for the piston ring–liner lubrication has been studied. Non-cavitation occurs in the vicinity of top dead center and bottom dead center. The non-cavitation period will be longer in the vicinity of 360° of crank angle. The density distribution in the cavitation zone can be obtained.

It is a challenging task to analysis oxide wear particles when they are stuck together with other types of wear particles in complex ferrography images. Hence, this paper aims to propose a method of ferrography image segmentation to analysis oxide wear debris in complex ferrography images.

First, ferrography images are segmented with watershed transform. Then, two region merging rules are proposed to improve the initial segmentation results. Finally, the features of each particle are extracted to detect and assess the oxide wear particles.

The results show that the proposed method outperforms other methods of ferrography image segmentation, and the overlapping wear particles in complex ferrography images can be well separated. Moreover, the features of each separated wear particles can be easily extracted to analysis the oxide wear particles.

The proposed method provides a useful approach for the automatic detection and assessment of oxide wear particles in complex ferrography images.

The colours, edges and position information of wear debris are considered in the proposed method to improve the segmentation result. Moreover, the proposed method can not only detect oxide wear particles in ferrography images but also evaluate oxide wear severity in ferrography images.

The purpose of this study is to make a prediction of China's energy consumption structure from the perspective of compositional data and construct a novel grey model for forecasting compositional data.

Due to the existing grey prediction model based on compositional data cannot effectively excavate the evolution law of correlation dimension sequence of compositional data. Thus, the adaptive discrete grey prediction model with innovation term based on compositional data is proposed to forecast the integral structure of China's energy consumption. The prediction results from the new model are then compared with three existing approaches and the comparison results indicate that the proposed model generally outperforms existing methods. A further prediction of China's energy consumption structure is conducted into a future horizon from 2021 to 2035 by using the model.

China's energy structure will change significantly in the medium and long term and China's energy consumption structure can reach the long-term goal. Besides, the proposed model can better mine and predict the development trend of single time series after the transformation of compositional data.

The paper considers the dynamic change of grey action quantity, the characteristics of compositional data and the impact of new information about the system itself on the current system development trend and proposes a novel adaptive discrete grey prediction model with innovation term based on compositional data, which fills the gap in previous studies.

Using computer technology to realize ferrographic intelligent fault diagnosis technology is fundamental research to inspect the operation of mechanical equipment. This study aims to effectively improve the technology of deep learning technology in the field of ferrographic image recognition.

This paper proposes a binocular image classification model to solve ferrographic image classification problems.

This paper creatively proposes a binocular model (BesNet model). The model presents a more extreme situation. On the one hand, the model is almost unable to identify cutting wear particles. On the other hand, the model can achieve 100% accuracy in identifying Chunky and Nonferrous wear particles. The BesNet model is a bionic model of the human eye, and the used training image is a specially processed parallax image. After combining the MCECNN model, it is changed to BMECNN model, and its classification accuracy has reached the highest level in the industry.

The work presented in this thesis is original, except as acknowledged in the text. The material has not been submitted, either in whole or in part, for a degree at this or any other university. The BesNet model developed in this article is a brand new system for ferrographic image recognition. The BesNet model adopts a method of imitating the eyes to view ferrography images, and its image processing method is also unique. After combining the MCECNN model, it is changed to BMECNN model, and its classification accuracy has reached the highest level in the industry.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0150/

Gross domestic product (GDP) is an important indicator to measure a country's economic development. If the future development trend of a country's GDP can be accurately predicted, it will have a positive effect on the formulation and implementation of the country's future economic development policies. In order to explore the future development trend of China's GDP, the purpose of this paper is to establish a new grey forecasting model with time power term to forecast GDP.

Firstly, the shortcomings of the traditional grey prediction model with time power term are found out through analysis, and then the generalized grey prediction model with time power term is established (abbreviated as PTGM (1,1, α) model). Secondly, the PTGM (1,1, α) model is improved by linear interpolation method, and the optimized PTGM (1,1, α) model is established (abbreviated as OPTGM (1,1, α) model), and the parameters of the OPTGM (1,1, α) model are solved by the quantum genetic algorithm. Thirdly, the advantage of the OPTGM (1,1, α) model over the traditional grey models is illustrated by two real cases. Finally the OPTGM (1,1, α) model is used to predict China's GDP from 2020 to 2029.

The OPTGM (1,1, α) model is more suitable for predicting China's GDP than other grey prediction models.

A new grey prediction model with time power term is proposed.

As a common form of failure in industry, corrosion causes huge economic losses. At present, with the development of computational techniques, artificial intelligence (AI) is playing a more and more important role in the field of scientific research. This paper aims to review the application of AI in corrosion protection research.

In this paper, the role of AI in corrosion protection is systematically described in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction.

With efficient and in-depth data processing methods, AI can rapidly advance the research process in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction and save on costs.

This paper summarizes the application of AI in corrosion protection research and provides the basis for corrosion engineers to quickly and comprehensively understand the role of AI and improve production processes.

This paper aims to consolidate prior research from policy and management domains to identify stages in China's technological learning within the imitation paradigm during 1949‐2001, focusing on changes in the government's strategic priorities and policies and the nature, mode and sources of technological learning, then to contrast the firm and institutional features that have emerged under the imitation paradigm with those defining the emerging creation paradigm. The analysis leads to clear implications for both policy and management for the Chinese firms to make this transition and compete in higher value‐added global industries.

An overview and conceptual paper based on observations and literature review.

This paper derives a parsimonious set of four dimensions to demarcate five stages in the evolution of China's technological learning: the government's strategic priority, nature of technology, the mode and the source of learning. It identifies six factors acting as significant impediments to Chinese firms' transition from imitation to creation.

In the first place, this paper provides managerial implications which are of great interest to Chinese practicing managers to manage their firms' transition from imitation to creation; second, the policy imperatives highlighted by this paper will help Chinese policymakers to design appropriate incentive mechanisms to enable Chinese firms to build up their competitiveness within the creation paradigm and thereby become global competitors. Meanwhile, this paper provides a systematic analysis on the evolution of China's technology development. This five stage‐based framework will help practicing managers in China understand whether, which and when Chinese firms can make the transition necessary to compete based on the creation of proprietary resources and capabilities.