Search Results (164)

Improving forest carbon sink efficiency (FCSE) is the key to mitigating climate change and achieving sustainable forest resource management in China. However, current research on FCSE remains predominantly focused on static perspectives and singular linear effects. Based on panel data from 30 provinces (autonomous regions and municipalities) in China from 2008 to 2022, this study integrated the super-efficiency Slack-Based Measure (SBM)-Malmquist–Luenberger (ML) model, spatial autocorrelation analysis, and dynamic fuzzy set qualitative comparative analysis (fsQCA) to reveal the spatiotemporal differentiation characteristics of FCSE and the multi-factor synergistic driving mechanism. The results showed that (1) the average value of the FCSE in China was 1.1. Technological progress (with an average technological change of 1.21) is the core growth driver, but the imbalance of technological efficiency change (EC) among regions restricts long-term sustainability. (2) The spatial distribution exhibited a U-shaped gradient pattern of “eastern—southwestern”, and the synergy effect between nature and economy is significant. (3) The dynamic fsQCA identified three sustainable improvement paths: the “precipitation–economy” collaborative type, the multi-factor co-creation type, and “precipitation–industry-driven” type; precipitation was the universal core condition. (4) Regional differences exist in path application; the eastern part depends on economic coordination, the central part is suitable for industry driving, and the western part requires multi-factor linkage. By introducing a dynamic configuration perspective, analyzing FCSE’s spatiotemporal drivers. We propose a sustainable ‘Nature–Society–Management’ interaction framework and region-specific policy strategies, offering both theoretical and practical tools for sustainable forestry policy design. Full article

The evaluation of tourism climate comfort is a systematic assessment of the climate conditions of tourist destinations. It is of great significance for improving the tourism experience, promoting the sustainable development of the tourism industry, and protecting the natural environment. In this study, the CiteSpace software was used to conduct a bibliometrics analysis of the study on tourism climate comfort in China, and the conceptual framework of this study was established based on the bibliometrics results. In the conceptual framework, this study firstly summarized eight indicators widely used in the current evaluation of tourism climate comfort. Secondly, four key technical means in the evaluation process were summarized, including geographic information system, analytic hierarchy process, fuzzy comprehensive evaluation, and cluster analysis. And three calculation methods of tourism climate comfort period were summarized, namely number of days with comfortable climate, five-day moving average method, and probability of climate-suitable days. Subsequently, the main application areas of tourism climate comfort evaluation were introduced: (1) exploration of the relationship between climate comfort and tourism activities (i.e., heat/cold-escape tourism, ice-snow tourism, outdoor rafting, coastal tourism, and other types of tourism activities); (2) exploration of the relationship between climate comfort and tourist flow; (3) the response of climate comfort to climate change; and (4) tourism climate regionalization. Finally, the main problems of current research and future development directions were proposed. Full article

Serving as critical sustainable transportation infrastructure, inland waterways provide dual socioeconomic and ecological value by (1) facilitating high-efficiency freight logistics through cost-effective bulk cargo transport while stimulating regional economic growth, and (2) delivering essential ecosystem services including flood regulation, water resource preservation, and biodiversity conservation. This study establishes a stakeholder-centered risk assessment framework to enhance decision-making of waterway engineering projects and promote the sustainable development of Inland Waterway Transport. We propose a three-layer approach: (1) identifying key stakeholders in the decision-making stage of waterway engineering projects through multi-dimensional criteria; (2) listing and classifying decision-making risks from the perspectives of managers, users, and other stakeholders; (3) applying the Decision-Making Trial and Evaluation Laboratory (DEMATEL) to prioritize key risks and proposing a risk assessment model based on fuzzy reasoning theory to evaluate decision-making risks under uncertain conditions. This framework was applied to the Yangtze River Trunk Line Wuhan–Anqing Waterway Regulation Project. The results show that the risk ranking is managers, users, and other stakeholders, among which the risk of engineering freight demand is particularly prominent. This suggests that we need to pay attention to optimizing material transportation and operational organization, promote the development of large-scale ships, and realize the diversification of ship types and transportation organizations. This study combines fuzzy reasoning with stakeholder theory, providing a replicable tool for the Waterway Management Authority to address the complex sustainability challenges in global waterway development projects. Full article

The neural moving horizon estimator (NMHE) is a relatively new and powerful state estimator that combines the strengths of neural networks (NNs) and model-based state estimation techniques. Various approaches exist for constructing NMHEs, each with its unique advantages and limitations. However, a comprehensive literature review that consolidates existing knowledge, outlines design guidelines, and highlights future research directions is currently lacking. To address this gap, this systematic review screened 1164 records and ultimately included 22 primary studies, following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol. This paper (1) explains the fundamental principles of NMHEs, (2) explores three major NMHE architectures, (3) analyzes the types of NNs used, such as multi-layer perceptrons (MLPs), long short-term memory networks (LSTMs), radial basis function networks (RBFs), and fuzzy neural networks, (4) reviews real-time implementability—including reported execution times ranging from 1.6 μs to 11.28 s on different computing hardware—and (5) identifies common limitations and future research directions. The findings show that NMHEs can be realized in three principal ways: model learning, cost function learning, and approximating the real-time optimization in moving horizon estimation. Cost function learning offers flexibility in capturing task-specific estimation goals, while model learning and optimization approximation approaches tend to improve estimation accuracy and computational speed, respectively. Full article

The characterization of soil attribute variability often requires dense sampling grids, which can be economically unfeasible. A possible solution is to perform targeted sampling based on previously collected data. The objective of this research was to develop a method for mapping soil attributes based on Management Zones (MZs) delineated from Sentinel-1 radar data. Sentinel-1 images were used to create time profiles of six indices based on VV (vertical–vertical) and VH (vertical–horizontal) backscatter in two agricultural fields. MZs were delineated by analyzing indices and VV/VH backscatter bands individually through two approaches: (1) fuzzy k-means clustering directly applied to the indices’ time series and (2) dimensionality reduction using deep-learning autoencoders followed by fuzzy k-means clustering. The best combination of index and MZ delineation approaches was compared with four soil attribute mapping methods: conventional (single composite sample), high-density uniform grid (one sample per hectare), rectangular cells (one composite sample per cell of 5 to 10 hectares), and random cells (one composite sample per cell of varying sizes). Leave-one-out cross-validation evaluated the performance of each sampling method. Results showed that combining the VV/VH index and autoencoders for MZ delineation provided more accurate soil attribute estimates, outperforming the conventional, random cells, and often the rectangular cell method. In conclusion, the proposed methodology presents scalability potential, as it does not require prior calibration and was validated on soil types commonly found across Brazil’s agricultural regions, making it suitable for integration into digital platforms for broader application in precision agriculture. Full article

It is essential to establish a normative framework that ensures the harmonious coexistence of humans and animals from legal and institutional perspectives. This study classifies and compares animal welfare policies in welfare states, identifying distinct policy types across different countries. Using fuzzy set ideal type analysis, this study examines seven OECD countries: Austria, Denmark, Germany, South Korea, Sweden, the United Kingdom (UK), and the United States (USA). These countries are consistent with Esping-Andersen’s three welfare state models and actively implement animal welfare policies. This study addresses the limitations of previous studies that focused primarily on animal-related discourses by examining the characteristics of different policy types that integrate two core components of animal welfare policy: animal welfare law and animal welfare systems. This analysis identified four types of animal welfare policies: (1) economic value type (South Korea and the USA); (2) social value type (the UK); (3) rights extension type (Denmark, Germany, and Sweden); and (4) ecological type (Austria). The results show that welfare state animal welfare policies are generally consistent with the ideological characteristics of the welfare system in question. However, Korea presents notable differences, providing valuable insights into its unique approach to animal welfare policy and informing future policy development. Full article

Against the intensifying mismatch between urban and rural land resources, activating farmers’ intentions to revitalize their idle homesteads is a key issue in optimizing land resource allocation and promoting urban–rural integrated development. However, existing studies mostly focus on the marginal effect of a single factor and ignore the synergistic effect of multiple factors, making it difficult to reveal the complex causal logic of farmers’ decision-making. This study aims to explain the causal asymmetry and equivalent path problem in farmers’ revitalized decision-making by capturing the multidimensional interaction mechanism of “external stimulus–mental cognition”. This study integrates the social stratification theory, the theory of planned behavior, and the Stimulus–Organism–Response framework to systematically explore how the interactive configuration of farmer differentiation and cognition from a multidimensional perspective drives the formation of farmers’ willingness to engage in high inventory activities, based on the 881 farmer research data in Shaanxi Province, using fuzzy-set qualitative comparative analysis (fsQCA) methodology. This study found that (1) a single condition cannot independently explain the intentions of farmers to revitalize, and its formation needs to rely on the synergistic linkage of multiple conditions; (2) the configuration of farmers’ high intentions to revitalize includes “wealth capital differentiation–dual cognitive-driven type”, “single cognitive-driven type”, “reputation capital differentiation–single cognitive-driven type”, “wealth capital differentiation–single cognitive-driven type”, which wealth capital differentiation is the common core condition triggering high intention; and (3) the formation of farmers’ low revitalization intentions stems from the insufficient differentiation of farmers and the lack of cognitive elements. Therefore, policymakers should take a holistic perspective in enhancing farmers’ revitalization intentions, focusing on the rational allocation between farmer differentiation and farmers’ cognition. Full article

This paper innovatively proposes the concepts of length, width, and depth for modern agricultural industrial systems. The development level of the modern agricultural industrial system is systematically measured by the length of the agricultural industry chain, the width of agriculture in terms of its overlap with and integration of non-agriculture industries, and the depth of agricultural productive services. Using the fuzzy set qualitative comparative analysis method, 88 main production areas of special and excellent agricultural products in Shanxi, China, are selected as sample objects. The configuration paths of the length, width, and depth of the modern agricultural industrial system impacting farmers’ wage income, operating income, property income, and transfer income are explored. The study found the following: (1) The income level of farmers is jointly influenced by the length, width, and depth of the modern agricultural industrial system, emphasizing that a single factor does not constitute a necessary condition for farmers’ income growth and prosperity. (2) There exist four types of paths through which the modern agricultural industrial system can promote increases in farmer incomes, namely “non-industry length * industry width”, “industry length * non-industry width * non-industry depth”, “non-industry length * industry depth” and “industry length * non-industry depth”, a various types of paths have a differential impact on the structure of farmers’ incomes. (3) The length, width, and depth of the modern agricultural industrial system individually have crowding-out effects on each of a farmer’s four types of income. Full article

Competing in a complex and interconnected environment, firms are increasingly employing open innovation to search for and collaborate with different partners for better performance. While universities are considered an important source of knowledge for industry, there has been limited literature that investigates patterns of their collaboration in an open innovation context. Moreover, the influence of contextual characteristics such as size and industry classes on these patterns has also received little attention. Aiming to address these research gaps, a research framework was developed from the extant literature. Taking into account the main antecedents integrated into this framework, a fuzzy c-means clustering approach was employed to find a typology of open innovative firms in their collaboration with universities. Using the typical value of the fuzzifier factor of this algorithm equal to 2, three distinct clusters were identified with respect to these antecedents as low, insecure, and responsive open innovators. Then, an econometric model using a multinomial logistic regression was constructed to explore the influence of firms’ size and industry type on the identified patterns of such collaboration. Based on the marginal effects analysis, mixed evidence was found regarding the influence of the firm’s size on the identified clusters, while the impact of industry intensity was in line with other prior studies in the extant literature. The results of our study lead to some meaningful implications from both an empirical and managerial point of view that are discussed alongside with future research recommendations. Full article

Background: Since periodontitis prevalence has increased globally and there is a bidirectional relationship between periodontitis and diabetes mellitus (DM), new methods of preventing and screening involving DM biomarkers could impact periodontitis management. We aimed to develop a fuzzy system to estimate the risk of periodontitis in patients with DM. Methods: Body mass index (BMI), glycemia (G), total cholesterol (C), and triglyceride (T) measurements were collected from 87 patients diagnosed with DM. Oral examinations were performed, and the number of the periodontal pockets (nrPPs) was determined. A fuzzy system was developed: BMI and G as inputs resulted in Periodontitis Risk 1 (PRisk1) output; C and T as inputs resulted in Periodontitis Risk 2 (PRisk2) output. From PRisk1 and PRisk2, the cumulative periodontitis risk (PCRisk) was assessed. Linguistic terms and linguistic grades (very small, small, medium, big, and very big) were assigned to the numerical variables by using 25 different membership functions. PCRisk and nrPP values were statistically processed. Results: In our developed fuzzy system, BMI, G, C, and T as input data resulted in periodontitis risk estimation. PCRisk was correlated with nrPP: when PCRisk increased by 1.881 units, nrPP increased by 1 unit. The fuzzy logic-based system effectively estimated periodontitis risk in type 2 diabetes patients, showing a significant correlation with the number of periodontal pockets. These findings highlight its potential for early diagnosis and improved interdisciplinary care. Full article

Ecotourism comfort is an important way to promote the harmonious coexistence between humans and nature, and it is the concrete implementation of the concept of harmonious coexistence and the theory of “Two Mountains”. Based on the urban comfort theory, the ecotourism comfort level of Chengdu city from 2010 to 2020 was measured. The MCR model and the gravity model were used to extract the potential corridor of ecotourism comfort to identify the core area of ecotourism comfort, and its configuration path was analyzed through a qualitative comparison of fsQCA fuzzy sets. The findings are as follows: (1) The overall level of ecotourism comfort in Chengdu has been improved, and the spatial distribution has a “core-edge” structure, which has obvious characteristics of “polarization leading and common development”. Among them, Wuhou District, Qingyang District, and Longquanyi District are the core areas, and the driving effect on marginal areas is particularly significant. (2) The potential ecological corridors in Chengdu are more densely distributed in the east than in the west, with significant north–south variations within both regions. (3) The core corridors of ecotourism comfort originate from Xinjin District and Longquanyi District, characterized by a banded distribution and primarily concentrated along the southwest–northeast axis. (4) The high level of ecotourism comfort in Chengdu is primarily manifested in five distinct types: “comprehensive drive, resource–transportation synergy, technology–transportation integration, government–led investment, and tourism market–technology linkage”. The research results offer a theoretical basis and scientific reference for enhancing the comfort level of urban ecotourism and comprehensively promoting the sustainable development of ecotourism. Full article

An enhanced whale optimization algorithm (WOA) through the implementation of a generalized type-2 fuzzy logic system (GT2FLS) is outlined. The initial idea is to improve the efficacy of the original WOA using a GT2FLS to find the optimal values of the ${\overrightarrow{\mathit{r}}}_{\mathbf{1}}$ and ${\overrightarrow{\mathit{r}}}_{\mathbf{2}}$ parameters of the WOA, for the case of optimizing mathematical functions. In the WOA algorithm, ${\overrightarrow{\mathit{r}}}_{\mathbf{1}}$ is a variable that affects the new position of the whale in the search space, in this case, affecting the exploration, and ${\overrightarrow{\mathit{r}}}_{\mathbf{2}}$ is a variable that has an effect on finding the local optima, which is an important factor for the exploration. The efficiency of a fuzzy WOA with a GT2FLS (FWOA-GT2FLS) is highlighted by presenting the excellent results of the case study of the benchmark function optimization. A relevant analysis and comparison with a bio-inspired algorithm based on artificial bees is also presented. Statistical tests and comparisons with other bio-inspired algorithms and the initial WOA, with type-1 FLS (FWOA-T1FLS) and interval type-2 FLS (FWOA-IT2FLS), are presented. For each of the methodologies, the metric for evaluation is the average of the minimum squared errors. Full article

A fuzzy cascaded PI−PD (FCPIPD) controller is proposed in this paper to optimize load frequency control (LFC) in the linked electrical network. The FCPIPD controller is composed of fuzzy logic, proportional integral, and proportional derivative with filtered derivative mode controllers. Utilizing renewable energy sources (RESs), a dual-area hybrid AC/DC electrical network is used, and the FCPIPD controller gains are designed via secretary bird optimization algorithm (SBOA) with aid of a novel objective function. Unlike the conventional objective functions, the proposed objective function is able to specify the desired LFCs response. Under different load disturbance situations, a comparison study is conducted to compare the performance of the SBOA-based FCPIPD controller with the one-to-one (OOBO)-based FCPIPD controller and the earlier LFC controllers published in the literature. The simulation’s outcomes demonstrate that the SBOA-FCPIPD controller outperforms the existing LFC controllers. For instance, in the case of variable load change and variable RESs profile, the SBOA-FCPIPD controller has the best integral time absolute error (ITAE) value. The SBOA-FCPIPD controller’s ITAE value is 0.5101, while sine cosine adopted an improved equilibrium optimization algorithm-based adaptive type 2 fuzzy PID controller and obtained 4.3142. Furthermore, the work is expanded to include electric vehicle (EV), high voltage direct current (HVDC), generation rate constraint (GRC), governor dead band (GDB), and communication time delay (CTD). The result showed that the SBOA-FCPIPD controller performs well when these components are equipped to the system with/without reset its gains. Also, the work is expanded to include a four-area microgrid system (MGS), and the SBOA-FCPIPD controller excelled the SBOA-CPIPD and SBOAPID controllers. Finally, the SBOA-FCPIPD controller showed its superiority against various controllers for the two-area conventionally linked electrical network. Full article

This paper investigated the tracking problem of mixed ${\mathcal{H}}_{\infty }$ and $L_2-L_{\infty }$ adaptive fault-tolerant control (FTC) for continuous-time interval type-2 fuzzy systems (IT2FSs). For the membership function mismatch and uncertainty between the modules of the nonlinear system, the IT2 fuzzy model is applied to linearly approximate it. The observer can sensitively estimate the system state, and the adaptive fault estimation functions can estimate adaptively the fault signals, which enables the designed adaptive FTC scheme to ensure the asymptotic stability of the closed-loop control system and achieve the desired mixed ${\mathcal{H}}_{\infty }$ and $L_2-L_{\infty }$ tracking performance. The designed adaptive control law can achieve the purpose of dynamic compensation for faults and disturbances, and the introduced lemmas further reduce the design conservatism by adjusting the slack parameters and matrices. Finally, a mass-spring-damping system is used to illustrate the effectiveness of the designed method. Full article

In the context of increasingly fierce global competition, utilizing digital technology to realize disruptive innovation is an effective way for enterprises to gain access to the mainstream market and form long-term competitive advantages. From the perspective of affordance, this study classifies digital technology affordance into cumulative affordance and variant affordance and explores the influence mechanism of digital technology affordance on enterprise disruptive innovation according to three core innovation phases: “fuzzy front-end–development–commercialization”. Based on 241 data points from different industries and types of enterprises, this empirical study found that (1) cumulative affordance and variant affordance have a significant positive impact on disruptive innovation and its “fuzzy front-end—development—commercialization” phases; (2) dynamic capabilities play a mediating role between digital technology affordance and disruptive innovation; and (3) the three aspects of dynamic capabilities—sensing, seizing, and reconfiguring—are greatly enhanced by cumulative affordance and variable affordance. These findings contribute to the research on the relationship between digital technology affordance and disruptive innovation and provide a micro-level perspective on how firms realize disruptive innovation through digital technology affordance. Full article