Zhihuai Xiao, Jiang Guo, Hongtao Zeng, Pan Zhou and Shuqing Wang
The purpose of this paper is to develop a new hybridized controller based on fuzzy reasoning and neural network (NN) for hydropower generator unit (HGU).
Abstract
Purpose
The purpose of this paper is to develop a new hybridized controller based on fuzzy reasoning and neural network (NN) for hydropower generator unit (HGU).
Design/methodology/approach
The approach contains fuzzy neural networks controller (FNNC), RBF network identification (RBFNI) and HGU system. FNNC may give control value to control HGU via fuzzy NN reasoning and computing according to HGU rotate speed error and error varying rate. RBFNI is used to identify the character of HGU system and predict its output. FNNC may adjust parameters and member function according to the identifying and predictive outcome of RBFNI.
Findings
Sees that the hybridized control system is feasible and stable, and the controlling performance of the hybridized system is superior to conventional fuzzy controller.
Research limitations/implications
The theoretical proof of stability of the proposed scheme still remains to be studied. Accessibility and availability of membership functions and control rules is also a limitation applied.
Practical implications
The main advantage of the proposed method is that FNNC has reasoning, learning, and optimizing capability which can control effectively HGU. This will be useful for control engineers to control complex industrial plants.
Originality/value
The paper proposes new combined approach to optimal control of HGU using FNNC, and it is aimed at operational researches and engineers, especially those who dealt with HUG controller.
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Ye Li, Hongtao Ren and Junjuan Liu
This study aims to enhance the prediction accuracy of hydroelectricity consumption in China, with a focus on addressing the challenges posed by complex and nonlinear…
Abstract
Purpose
This study aims to enhance the prediction accuracy of hydroelectricity consumption in China, with a focus on addressing the challenges posed by complex and nonlinear characteristics of the data. A novel grey multivariate prediction model with structural optimization is proposed to overcome the limitations of existing grey forecasting methods.
Design/methodology/approach
This paper innovatively introduces fractional order and nonlinear parameter terms to develop a novel fractional multivariate grey prediction model based on the NSGM(1, N) model. The Particle Swarm Optimization algorithm is then utilized to compute the model’s hyperparameters. Subsequently, the proposed model is applied to forecast China’s hydroelectricity consumption and is compared with other models for analysis.
Findings
Theoretical derivation results demonstrate that the new model has good compatibility. Empirical results indicate that the FMGM(1, N, a) model outperforms other models in predicting the hydroelectricity consumption of China. This demonstrates the model’s effectiveness in handling complex and nonlinear data, emphasizing its practical applicability.
Practical implications
This paper introduces a scientific and efficient method for forecasting hydroelectricity consumption in China, particularly when confronted with complexity and nonlinearity. The predicted results can provide a solid support for China’s hydroelectricity resource development scheduling and planning.
Originality/value
The primary contribution of this paper is to propose a novel fractional multivariate grey prediction model that can handle nonlinear and complex series more effectively.
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Keywords
In recent years, fast urban expansion in China has stimulated rapid energy consumption growth and increased environmental pollution. Therefore, it is important to utilize clean…
Abstract
Purpose
In recent years, fast urban expansion in China has stimulated rapid energy consumption growth and increased environmental pollution. Therefore, it is important to utilize clean and renewable energy in district heating for the sustainable urban development. This study aimed to investigate the environmental and economic impacts of one hot dry rock (HDR) geothermal energy-based heating system in a life cycle framework.
Design/methodology/approach
By using the input–output-based life cycle analysis model, the energy consumption, CO2 emission and other pollutants of the HDR-based heating system were evaluated and then compared with those of other four heating systems based on burning coal or natural gas. The life cycle costs of the HDR-based heating system were also analyzed.
Findings
The results showed that using HDR geothermal energy for heating can significantly reduce fossil fuel consumption, CO2 emission as well as environmental pollution, and its life cycle costs are also competitive.
Originality/value
This study not only evaluated the environmental and economic impacts of the HDR-based heating system in a life cycle framework but also provided a methodological life cycle assessment framework that can estimate both economic and environmental benefits, which can be used in policy making for China’s urban development.
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Md Jahidur Rahman, Hongtao Zhu and Sihe Chen
This study aims to investigate the relationship between corporate social responsibility (CSR) and financial distress and the moderating effect of firm characteristics, auditor…
Abstract
Purpose
This study aims to investigate the relationship between corporate social responsibility (CSR) and financial distress and the moderating effect of firm characteristics, auditor characteristics and the Coronavirus disease 2019 (Covid-19) in China.
Design/methodology/approach
The research question is empirically examined on the basis of a data set of 1,257 Chinese-listed firms from 2011 to 2021. The dependent variable is financial distress risk, which is measured mainly by Z-score. CSR score is used as a proxy for CSR. Propensity score matching, two-stage least square and generalized method of moments are adopted to mitigate the potential endogeneity issue.
Findings
This study reveals that CSR can reduce financial distress. Specifically, results show an inverse relationship between CSR and financial distress, more significantly in non-state-owned enterprises, firms with non-BigN auditor and during Covid-19. The results are consistent and robust to endogeneity tests and sensitivity analyses.
Originality/value
This study enriches the literature on CSR and financial distress, resulting in a more attractive corporate environment, improved financial stability and more crisis-resistant economies in China.
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This study aims to deem the new policy – talk for environmental protection – promoted in the second half of 2014 to be the exogenous event and adopts PSM and DID to verify whether…
Abstract
Purpose
This study aims to deem the new policy – talk for environmental protection – promoted in the second half of 2014 to be the exogenous event and adopts PSM and DID to verify whether and how the central government’s mechanism of supervision of environmental enforcement improves firm environmental performance and reveals the micro effect and working mechanism of the supervision of environmental enforcement.
Design/methodology/approach
The researchers first select reasonable control groups for target districts by means of PSM, then apply DID to compare corporations in the treatment group with those in the control group for the change of environmental performance before and after the talk for environmental protection, so as to evaluate the micro-level effect of such talks on corporate environmental performance; after that, the research examines the working mechanism of such talks on corporate environmental performance; then, it goes a step further to find out the environmental impact of such talks on corporations of different natures of property right.
Findings
It is found from the research that the talk for environmental protection will effectively improve the environmental performance of corporations in the target districts, and the improvement of environmental performance in state-owned corporations in the target districts will be more evident. However, such improvements, to a certain extent, are achieved by reducing the output value, and corporations do not increase environmental investments from a long-term perspective.
Research limitations/implications
First, the targets of the talk for environmental protection are mainly principals of municipal governments, but the research expands the scope to the whole province due to the small sample at the municipal level. Despite evidences showing that such a pressure of supervision impacts the whole province, the results obtained based on the data at the municipal level will be accurate. Second, the research selects a relatively short research period. Third, due to the limited data on corporate environmental performance in China, the research selects only listed companies from key monitored and controlled firms by state.
Practical implications
First, for the central government, environmental policy making is not the end of its job; it shall also supervise local governments’ work at environmental governance and properly handle its relationship with local governments. Second, for the local governments, in the course of implementing environmental policies, they should not only strengthen law enforcement but keep the continuity of law enforcement to avoid moving law enforcement. Third, in the long run, corporations must start from the source of production to enhance environmental governance and make cleaner production, so as to keep boosting corporate competitiveness and their ability of fighting risks.
Originality/value
First, the research innovatively provides empirical evidence about the effect of China’s supervision of environmental enforcement. Previous studies on this topic are mostly theoretical discussions only, while this research makes the talk for environmental protection the exogenous event about the supervision of law enforcement and achieves breakthroughs in empirical studies of administrative enforcement supervision. Second, the research pushes the studies on the implementation effect of environmental policies from a medium level to a micro level. Third, the research achieves some breakthroughs in the data for measuring corporate environmental performance.
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Xiaoxu Dang, Mengying Wang, Xiaopeng Deng, Hongtao Mao and Pengju He
Corporate social responsibility (CSR) practices frequently result in increased costs for Chinese international contractors (CICs), where profitability is the primary objective;…
Abstract
Purpose
Corporate social responsibility (CSR) practices frequently result in increased costs for Chinese international contractors (CICs), where profitability is the primary objective; therefore, internal corporate drivers and external pressures play a crucial role in encouraging them to engage in sustainable CSR practices. This study systematically examines the dynamic impact of internal and external stakeholders on the CSR practices of CICs.
Design/methodology/approach
This study adopted a structural equation model (SEM) to identify and validate a correlation between stakeholders and CSR practices. Standardized causal coefficients estimated in SEM were used to construct a fuzzy cognitive map (FCM) model to illustrate the effect of stakeholders on CSR practices with linkage direction and weights. Predictive, diagnostic, and hybrid analyses were performed to dynamically model the variation in stakeholders on the evolution of CSR practices.
Findings
The empirical results demonstrate that (1) employee participation in CSR has the greatest impact on CSR practices, followed by CSR strategies, partner and customer expectations, and finally government regulations. (2) In the early stage of CSR fulfillment, CSR strategies have the greatest influence on CSR practices; in the later stage of CSR fulfillment, employee participation in CSR has the greatest influence on CSR practices. (3) In the long run, the most effective and economical integrated interventions are those that address employee participation in CSR, partner expectations and customer expectations, and intervention in CSR strategies is needed if the level of CSR practice needs to be improved in the short term.
Originality/value
This study contributes to the research on the influence mechanisms of CSR practices of CICs and systematically analyzes their dynamic influence on CSR practices of CICs from the perspective of stakeholders.
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Xiaohua Shi, Chen Hao, Ding Yue and Hongtao Lu
Traditional library book recommendation methods are mainly based on association rules and user profiles. They may help to learn about students' interest in different types of…
Abstract
Purpose
Traditional library book recommendation methods are mainly based on association rules and user profiles. They may help to learn about students' interest in different types of books, e.g., students majoring in science and engineering tend to pay more attention to computer books. Nevertheless, most of them still need to identify users' interests accurately. To solve the problem, the authors propose a novel embedding-driven model called InFo, which refers to users' intrinsic interests and academic preferences to provide personalized library book recommendations.
Design/methodology/approach
The authors analyze the characteristics and challenges in real library book recommendations and then propose a method considering feature interactions. Specifically, the authors leverage the attention unit to extract students' preferences for different categories of books from their borrowing history, after which we feed the unit into the Factorization Machine with other context-aware features to learn students' hybrid interests. The authors employ a convolution neural network to extract high-order correlations among feature maps which are obtained by the outer product between feature embeddings.
Findings
The authors evaluate the model by conducting experiments on a real-world dataset in one university. The results show that the model outperforms other state-of-the-art methods in terms of two metrics called Recall and NDCG.
Research limitations/implications
It requires a specific data size to prevent overfitting during model training, and the proposed method may face the user/item cold-start challenge.
Practical implications
The embedding-driven book recommendation model could be applied in real libraries to provide valuable recommendations based on readers' preferences.
Originality/value
The proposed method is a practical embedding-driven model that accurately captures diverse user preferences.
Details
Keywords
Qunfeng Zeng, Hao Jiang, Qi Liu, Gaokai Li and Zekun Ning
This paper aims to introduce a high-temperature grease design method assisted by back propagation neural network (BPNN) and verify its application value.
Abstract
Purpose
This paper aims to introduce a high-temperature grease design method assisted by back propagation neural network (BPNN) and verify its application value.
Design/methodology/approach
First, the grease data sets were built by sorting out the base data of greases in a large number of literatures and textbooks. Second, the BPNN model was built, trained and tested. Then, the optimized BPNN model was used to search the unknown data space and find the composition of greases with excellent high-temperature performance. Finally, a grease was prepared according to the selected composition predicted by the model and the high-temperature physicochemical performance, high-temperature stability and tribological properties under different friction conditions were investigated.
Findings
Through high temperature tribology experiments, thermal gravimetric analysis and differential scanning calorimetry experiments, it is proved that the high temperature grease prepared based on BPNN has good high-temperature performance.
Originality/value
To the best of the authors’ knowledge, a new method of designing and exploring high-temperature greases is successfully proposed, which is useful and important for the industrial applications.
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Jue Li, Hongbo Xu, Jussi Hokka, Toni T. Mattila, Hongtao Chen and Mervi Paulasto‐Kröckel
The purpose of this paper is to study the reliability of SnAgCu solder interconnections under different thermal shock (TS) loading conditions.
Abstract
Purpose
The purpose of this paper is to study the reliability of SnAgCu solder interconnections under different thermal shock (TS) loading conditions.
Design/methodology/approach
The finite element method was employed to study the thermomechanical responses of solder interconnections in TS tests. The stress‐strain analysis was carried out to study the differences between different loading conditions. Crack growth correlations and lifetime predictions were performed.
Findings
New crack growth data and correlation constants for the lifetime prediction model are given. The predicted lifetimes are consistent with the experimental results. The simulation and experimental results indicate that among all the loading conditions studied the TS test with a 14‐min cycle time leads to the earliest failure of the ball‐grid array (BGA) components.
Originality/value
The paper presents new crack growth correlation data and the constants of the lifetime prediction models for SnAgCu solder interconnections, as well as for the BGA components. The paper adds insight into the thermomechanical reliability evaluation of SnAgCu solder interconnections.
Details
Keywords
Debiao Meng, Shiyuan Yang, Chao He, Hongtao Wang, Zhiyuan Lv, Yipeng Guo and Peng Nie
As an advanced calculation methodology, reliability-based multidisciplinary design optimization (RBMDO) has been widely acknowledged for the design problems of modern complex…
Abstract
Purpose
As an advanced calculation methodology, reliability-based multidisciplinary design optimization (RBMDO) has been widely acknowledged for the design problems of modern complex engineering systems, not only because of the accurate evaluation of the impact of uncertain factors but also the relatively good balance between economy and safety of performance. However, with the increasing complexity of engineering technology, the proposed RBMDO method gradually cannot effectively solve the higher nonlinear coupled multidisciplinary uncertainty design optimization problems, which limits the engineering application of RBMDO. Many valuable works have been done in the RBMDO field in recent decades to tackle the above challenges. This study is to review these studies systematically, highlight the research opportunities and challenges, and attempt to guide future research efforts.
Design/methodology/approach
This study presents a comprehensive review of the RBMDO theory, mainly including the reliability analysis methods of different uncertainties and the decoupling strategies of RBMDO.
Findings
First, the multidisciplinary design optimization (MDO) preliminaries are given. The basic MDO concepts and the corresponding mathematical formulas are illustrated. Then, the procedures of three RBMDO methods with different reliability analysis strategies are introduced in detail. These RBMDO methods were proposed for the design optimization problems under different uncertainty types. Furtherly, an optimization problem for a certain operating condition of a turbine runner blade is introduced to illustrate the engineering application of the above method. Finally, three aspects of future challenges for RBMDO, namely, time-varying uncertainty analysis; high-precision surrogate models, and verification, validation and accreditation (VVA) for the model, are discussed followed by the conclusion.
Originality/value
The scope of this study is to introduce the RBMDO theory systematically. Three commonly used RBMDO-SORA methods are reviewed comprehensively, including the methods' general procedures and mathematical models.