Neighborhood Relations Research Articles

Strengthening A ‘Nepal, India, and China Equitable (NICE) Relationship’ for Regional Development

This paper explores the prospects of fostering equitable trilateral economic cooperation among the contiguous nations of Nepal, India, and China (NIC). The underlying concept advocates for an integrated framework termed the 'Nepal, India, and China Equitable Relation' (NICE Relation). The study endeavours to elucidate Nepal's economic diplomacy from a geographical standpoint, emphasizing the significance of fostering warm neighbourhood relationships. Its overarching objective is to optimize the existing operational modalities of immediate neighbourhoods and socio-economic activities among NIC partners. The potential cooperations have unveiled insights derived from the realms of Development Cooperation, Economic Geography, and Centre-Periphery ideologies. A trilateral alliance of this nature has been revealed to catalyse enhanced cooperation within the immediate neighbourhood, fostering mutual benefits and contributing to the overarching goals of 'Protection (security), Peace, and Prosperity (PPP)' in the broader Himalayan region shared by these neighbouring nations.

'We see they are abandoned': Social support between people discharged from long-term psychiatric hospitalizations and their neighbors in Argentina.

Neighbors are an important component of personal social network (PSN) and despite their peripheral role and being considered as familiar strangers, they typically provide instrumental support. For people who is discharged after long-term psychiatric hospitalizations, neighbors would offer other types of social support and play a different role fostering the process of becoming full member of a given community. To analyze the effects of neighboring on both, those who have had long-term psychiatric hospitalizations and their neighbors. Data was collected between 2020 and 2021, including interviews with formal care staff of three housing support experiences in Argentina, and short testimonies from formerly discharged mental health service users living in the community and their neighbors. We analyzed the data using the Framework Method with a focus on the different aspects of social support and equity and reciprocity theories. Results suggest that emotional support was a frequent function displayed by neighbors toward people with a history of long-term psychiatric hospitalizations, which differs from typical neighboring relationships. Despite reciprocity was observed, users and neighbors displayed an unbalanced helping relationship.

Image encryption algorithm based on a new 3D chaotic system using cellular automata

Cryptography and steganography are usual methods for safe transfer of information, which encryption algorithms turn original images into unreadable noise-like images. This paper presents a novel symmetric cryptosystem designed for the transmission of RGB color images through open channels and our goal is to provide a secure cryptography algorithm against cropping and noise attacks. The encryption algorithm is based on a suitable 3D hybrid chaotic system, with high Lyapunov exponent value, leveraging the advantages of common chaos maps while addressing their inherent limitations. To further enhance security, a novel pixel shuffle operator is employed to eliminate any potential neighborhood relations between image pixels. The encryption process incorporates reversible second-order cellular automata, which are applied to the outputs of the chaotic system. Key generation is achieved through the utilization of irreversible cellular automata. The resulting key space is large enough to resist brute-force attacks and performs a high level of sensitivity. Experimental results, including analysis of histograms, entropies, and pixel correlations, confirm the effectiveness of the proposed image encryption scheme, and prove its resilient against statistical attacks and a remarkable resistance against data loss attacks.

Study on Green Gentrification Mechanisms and Residents’ Satisfaction in Chinese New Urban Areas: A Case Study of the Area Surrounding Julong Lake Park

As China’s urbanization rate continues to rise, new cities are constantly being built, and the popularity of sustainable concepts has led to the development of numerous green infrastructure projects. The increase in green resources has improved the overall urban environment, but this environmental improvement can lead to local stratification and give rise to a phenomenon known as “green gentrification”. Green gentrification can enhance neighborhood vitality but may also lead to negative consequences, such as the displacement of indigenous populations. This study primarily focuses on whether there is residential segregation and social differentiation between indigenous residents and newcomers due to green gentrification and whether they hold different views on green infrastructure. To address these issues and advance the cause of urban fairness and justice, break down neighborhood segregation, and promote community integration, we conducted satisfaction surveys and in-depth personal interviews with indigenous residents and newcomers regarding the Julong Lake facility, their individual circumstances, and the neighborhood relationships. The survey results revealed the following: (1) Both the indigenous residents and the newcomers expressed a relatively high satisfaction with the sports facilities at Julong Lake, but both groups reported a lower satisfaction with the neighborhood relationships. (2) The indigenous residents exhibited a lower satisfaction compared to the newcomers regarding the commercial facilities, social attributes, and green infrastructure surrounding Julong Lake. Additionally, the overall satisfaction with Julong Lake was lower for the indigenous residents compared to the newcomers. We synthesized the survey results and personal interviews with the indigenous residents and the newcomers and arrived at the following conclusions: (1) In the context of urbanization and uneven distribution of green resources in urban areas, the integration of suburban green resources with real estate development has given rise to the new phenomenon of an emerging green middle class, primarily driven by green resources. (2) The new residents exhibited higher satisfaction levels with Julong Lake park attributes and their personal circumstances compared to the long-term residents. This suggests a “green preference” among the new residents, leading to social stratification among the long-term residents driven by cultural aesthetics and value pursuits. The result of this is a stratification and adjacent residential segregation between the long-term residents and the newcomers. (3) The emerging green middle class areas have, on the one hand, promoted the migration of capital, middle-class populations, and green resources to the suburbs, to some extent favoring suburban green development. In conclusion, we hope that this research can help facilitate more equitable allocation of green resources in cities, formulate more optimal green policies, and promote harmonious coexistence and the sharing of the benefits of green development among residents of different income levels in urban areas.

PUBLIC BATH USE AT A JAPANESE SENIOR APARTMENT ASSOCIATED WITH NEIGHBORHOOD RELATIONSHIPS AND SOCIAL SUPPORT

Abstract The number of older adults who choose to move into senior apartments is increasing in Japan. The development of quality relationships within the senior apartment is important for the healthy aging of the residents. A “public bath” is a unique facility in Japanese senior apartment where residents can interact with each other. Historically, Japan has had a culture of bathing with family and friends in public baths, and the use of this facility is expected to lead to socialization. This study aimed to examine the association between the frequency of public bath use, and neighborhood relationship and social support within a senior apartment. A cross-sectional survey was conducted in a senior apartment in February 2022 (Saitama Prefecture, Japan) towards the entire residents (n=185). Frequency of public bath use (once a week or more vs. less than once a week) was used as the independent variable. Neighborhood relationship (can support or talk to each other vs. only light greetings or no relationship) and social support (have vs. do not have social support) within the senior apartment were used as dependent variable. A binary regression analysis (n=117, female=60.7%) revealed that a higher frequency of public bath use associated with deep neighborhood relationship (OR: 7.14, 95% CI: 1.39-36.63) and social support (OR: 3.44, 95% CI: 1.19-9.99). These results suggest the importance of having a public bath in Japanese senior apartment setting. Furthermore, integrating facilities that possess cultural significance at senior apartments could be important for fostering social relationships.

STRATEGIC PLANNING “TAKING THE ENEMY TO COPE WITH THE ENEMY” OF LY HONG CHUONG TO NORTH KOREA AND VIETNAM (1879-1885)

When Western empires infiltrated Asian countries which had traditional relations with China such as Vietnam and North Korea, Minister of Qing Dynasty - Ly Hong Chuong, gave strategic planning “taking the enemy to cope with the enemy” in order to maintain this relationship. However, that strategic planning of Ly Hong Chuong could not compete with the power of the West, making the Qing dynasty not only unable to protect the traditional Neighbour Relationship but also being torn by the Western empires, becoming a colony.

Shared neighbors rough set model and neighborhood classifiers

Neighborhood relations are established by employing a distance metric and parameters, where the distance metric is utilized to measure the dissimilarities between objects. The information about adjacent objects tends to vary, even though these objects belong to a neighborhood. Taking into account neighborhood information, this paper introduces a similarity measure of shared neighbors, which is determined by the overlapping neighbors in a neighborhood relation. The similarity measure, induced by a neighborhood relation, is superior to the distance metric in quantifying differences, and it is crucial to note that the neighborhood relation can be any binary relation. A neighborhood of shared neighbors is proposed based on the proposed similarity measure, which consists of the most similar neighbors. Subsequently, we propose the shared neighbors rough set model, which is regarded as a framework of fusing neighborhood information. Moreover, an attribute reduction algorithm and a neighborhood classifier of shared neighbors are designed. The experimental results demonstrate the effectiveness of the neighborhood classifier and the shared neighbors rough set model.

Characterization of trajectories of physical activity and cigarette smoking from early adolescence to adulthood

BackgroundCigarette smoking and physical inactivity are two critical risk factors for noncommunicable diseases and all-cause mortality. However, few studies have compared the long-term trajectories of both behaviors, as well as multilevel factors associated with trajectory patterns. Using the National Longitudinal Study of Adolescent to Adult Health (Add Health) Wave I through V survey data, this study characterized distinct subgroups of the population sharing similar behavioral patterns from adolescence to adulthood, as well as predictors of subgroup membership for physical activity (PA) and cigarette smoking behavior respectively.MethodsUsing the Add Health Wave I through V survey data, we identified the optimal number of latent classes and class-specific trajectories of PA and cigarette smoking from early adolescence to adulthood, fitting latent growth mixture models with standardized PA score and past 30-day cigarette smoking intensity as outcome measures and age as a continuous time variable. Associations of baseline sociodemographic factors, neighborhood characteristics, and sociopsychological factors with trajectory class membership were assessed using multinomial logistic regression.ResultsWe identified three distinct subgroups of non-linear PA trajectories in the study population: moderately active group (N = 1067, 5%), persistently inactive group (N = 14,257, 69%) and worsening activity group (N = 5410, 26%). Foror cigarette smoking, we identified three distinct non-linear trajectory subgroups: persistent non-smoker (N = 14,939, 72%), gradual quitter (N = 2357, 11%), and progressing smoker (N = 3393, 16%). Sex, race/ethnicity, neighborhood environment and perceived peer support during adolescence were significant predictors of both physical activity and cigarette smoking trajectory subgroup membership from early adolescence to adulthood.ConclusionsThere are three distinct subgroups of individuals sharing similar PA and cigarette smoking behavioral profile respectively from adolescence to adulthood in the Add Health study population. Behavioral interventions that focus on neighborhood environment (e.g. establish community-based activity center) and relationship to peers during adolescence (e.g. peer counseling) could be key to long-term PA promotion and cigarette smoking cessation.

The role of Azerbaijan as the EU’s energy supplier: a secondary alternative partner in natural gas

ABSTRACT This article focuses on what kind of shortcomings Azerbaijan has in becoming the main energy supplier of the EU. The objective of this study is to analyse disadvantages of Azerbaijan via a mixed methodology which is based on discourses, data of Eurostat and description of political and geographical shortcomings of the country. Azerbaijan has both some advantages and disadvantages. The policy of neighbourhood relations is implemented between Azerbaijan and the EU. Azerbaijan is a country with which the EU has friendly relations in the Caucasus region. By analysing Azerbaijan's capacity, its importance and position for the EU can be emphasised. Data published by Eurostat are used in this study. According to these data, it can be stated that Russia is no longer a major supplier to the EU. The asymmetric interdependence between the EU and Russia in energy field has weakened as a result of the recent steps taken by European politicians. The USA, Qatar, Norway and the United Kingdom are among the new supplier countries. What role can Azerbaijan play in satisfying the EU's energy needs? In this article, I argue that Azerbaijan can be an important supplier to the EU, but it cannot become the main energy supplier.

국방부 예비역을 위한 실버타운 선호도에 관한 연구

This study derives desirable implications that can be applied through an empirical analysis of the silver town preferences of reservists in order to improve housing supply, housing welfare, residential environment, and quality of life for reservists of the Ministry of National Defense in an aging society and reflects them in the military housing policy of the Ministry of National Defense. It is done.
 As a result of the study, it was found that internal characteristics were the most preferred, followed by program characteristics, relationship, and economic characteristics, while physical characteristics were the least preferred.
 First, men and women strongly preferred safety facilities, living convenience facilities, emergency medical care, regular checkups, and emergency support, and preferred health activities, silver activities, neighbor relations, and staff response. On the other hand, women preferred deadlines, residential independence, household activities, business management, and pastimes. Second, in terms of service years, those with 10 or 20 years or more prefer health activities and silver activities, while those with 10 or more years prefer emergency medical services, regular checkups, and medical support, and those with 20 or more years prefer safety facilities, living convenience facilities, neighbor relations, and medical support. I preferred staff response. In particular, for over 20 years, emergency medical care, regular checkups, and emergency support were highly preferred. Third, the Military Housing Policy Division under the Military Facilities Planning Directorate of the Ministry of Defense Resource Management establishes a military housing policy, and the Ministry of National Defense Facilities Headquarters reflects it in the guidelines for preparing basic design requirements for national defense and military facility standards, as well as working guidelines, standard plans, and standard detailed drawings, and the Military Mutual Aid Association It is reflected in the business plan of the real estate investment headquarters of the construction investment division, and it is believed that the morale of reservists will increase if unused military facilities are discovered and used as a silver town site.

Feature selection based on self-information combining double-quantitative class weights and three-order approximation accuracies in neighborhood rough sets

Feature selection is related to information processing, and its measurement and algorithm use various intelligent methodologies, such as neighborhood rough sets (NRSs). At present by NRSs, the relative neighborhood self-information (Relative-NSI) introduces an information function for algebraic characterization, and its feature selection algorithm (NSI-FS) has been successfully applied. However, Relative-NSI and NSI-FS ignore the underlying recognition information of decision classes; thus, they have the advancement space. In this study, absolute rates and correlative coefficients of decision classes are double-quantitatively introduced, and three-order approximation accuracies are systematically established to induce a robust self-information measure; thus, corresponding feature selection optimally improves NSI-FS to have generalization abilities. Firstly, three-order approximation accuracies are constructed by using two-time class weights of absolute rates and Spearman's correlation coefficients, and the new measure called ClaWNSI promotes Relative-NSI in terms of class recognition. Then, the three-order approximation accuracies and subsequent ClaWNSI are evolved in matrix forms, and relevant class weights of Spearman's correlation coefficients are realized by two vectors from approximation matrices. Furthermore, ClaWNSI and its feature significance motivate a heuristic selection algorithm (called ClaWNSI-FS). Finally, data experiments on 14 datasets validate ClaWNSI and ClaWNSI-FS; ClaWNSI-FS outperforms NSI-FS and five other contrast algorithms to acquire better classification performance.

Psychological pushing propagation in crowds—Does the observation of pushing behavior promote further intentional pushing?

When large numbers of people come together (e.g., at concerts or religious gatherings), critical situations can arise easily. While physical factors such as crowd density play a role, people's behavior can also affect crowd dynamics. For example, pushing and shoving, which are closely related to density, can quickly contribute to potentially dangerous dynamics. There is little extant research, however, on why people start pushing in the first place. Aside from individual reasons (e.g., motivation), social reasons might also play a role: an initial instance of pushing might be imitated or spark a competition if the pusher seems to reach the goal faster or the behavior of individuals defines a group norm whether pushing is allowed or not. Practically speaking, these social factors should lead people to push because they perceive other pushers, or, in other words, a psychological pushing propagation occurs. To address this question, the behavior (pushing or non-pushing) of people in 14 different experimental runs of crowds walking through a bottleneck (N = 776) was assessed by two independent raters with the help of a rating system of forward motion. This assessment was then linked to the spatiotemporal positions of the participants to combine it with the neighborhood relations. Based on that, it was analyzed whether individuals who started to push were more likely to be in the direct neighborhood of individuals who were already pushing. Results showed a small but significant effect suggesting that there is an influence, but that pushing is not overly “contagious.”

Locality Preserving Projections with Autoencoder

Locality Preserving Projections (LPP) is a popular dimensionality reduction method in the manifold learning field. However, LPP and all its variants only consider the one-way mapping from the high-dimensional space to the low-dimensional space and have no reverse verification, resulting in inaccurate low-dimensional embeddings. In this paper, we propose a new LPP method, called LPPAE (Locality Preserving Projections with Autoencoder), based on the linear Autoencoder. It constructs a two-way mapping: at the encoding stage, the conventional projection of LPP is viewed as a mapping from the high-dimensional space to the low-dimensional space. At the decoding stage, the low-dimensional embeddings are mapped back to the original high-dimensional space. The main contributions of the new method are: (1) This design not only preserves the neighborhood relationship of the data but more importantly, ensures that the low-dimensional embeddings can more accurately ”represent” the original data, thus significantly improving the performance of LPP. Experimental results on Handwritten Alphadigits, COIL-20, Yale, AR datasets show that the recognition rates of LPPAE are 26.06, 10.09, 5.40, and 8.86% higher than those of the original LPP respectively. On the MNIST dataset, compared to some of the latest improvements of LPP, including LPPMDC, LAPP, LPP+TR, and DNLPP, the recognition rate of LPPAE has been improved by 12.50, 38.10, 9.10, and 2.61%, respectively. (2) LPPAE regards the conventional LPP as an encoder, which is a new perspective. The idea of LPPAE can be used as a general framework and then extended to other manifold learning methods, and then a series of new methods can be developed.

WRND: A weighted oversampling framework with relative neighborhood density for imbalanced noisy classification

Imbalanced data and label noise are ubiquitous challenges in data mining and machine learning that severely impair classification performance. The synthetic minority oversampling technique (SMOTE) and its variants have been proposed, but they are easily constrained by hyperparameter optimization such as k-nearest neighbors, their performance deteriorates owing to noise, they rarely consider data distribution information, and they cause high complexity. Furthermore, SMOTE-based methods perform random linear interpolation between each minority class sample and its randomly selected k-nearest neighbors, regardless of sample differences and distribution information. To address the above problems, an adaptive, robust, and general weighted oversampling framework based on relative neighborhood density (WRND) is proposed. It can combine with most SMOTE-based sampling algorithms easily and improve performance. First, it adaptively distinguishes and filters noisy and outlier samples by introducing the natural neighbor, which inherently avoids the extra noise and overlapping samples introduced by the synthesis of noisy samples. The relative neighborhood density of each sample can then be obtained, which reflects the intra-class and inter-class distribution information within the natural neighborhood. To alleviate the blindness of SMOTE-based methods, the number and locations of synthetic samples are informedly assigned based on distribution information and reasonable generalization of natural neighborhoods of original samples. Extensive experiments on 23 benchmark datasets and six classic classifiers with eight pairs of representative sampling algorithms and two state-of-the-art frameworks, significantly demonstrate the effectiveness of the WRND framework. Code and framework are available at https://github.com/dream-lm/WRND_framework.

Some Logics in the Vicinity of Interpretability Logics

In this paper we shall define semantically some families of propositional modal logics related to the interpretability logic \(\mathbf{IL}\). We will introduce the logics \(\mathbf{BIL}\) and \(\mathbf{BIL}^{+}\) in the propositional language with a modal operator \(\square\) and a binary operator \(\Rightarrow\) such that \(\mathbf{BIL}\subseteq\mathbf{BIL}^{+}\subseteq\mathbf{IL}\). The logic \(\mathbf{BIL}\) is generated by the relational structures \(\left<X,R,N\right>\), called basic frames, where \(\left<X,R\right>\) is a Kripke frame and \(\left<X,N\right>\) is a neighborhood frame. We will prove that the logic \(\mathbf{BIL}^{+}\) is generated by the basic frames where the binary relation \(R\) is definable by the neighborhood relation \(N\) and, therefore, the neighborhood semantics is suitable to study the logic \(\mathbf{BIL}^{+}\) and its extensions. We shall also study some axiomatic extensions of \(\mathsf{\mathbf{BIL}}\) and we will prove that these extensions are sound and complete with respect to a certain classes of basic frames. Finally, we prove that the logic BIL+ and some of its extensions are complete respect with the class of neighborhood frames.

Reconstructing and Deconstructing Neighborhoods: Horizontality, Materialities, and Struggles in the Case of Pinheirinho do Palmares district, Brazil

Based on an ethnography developed with social movements derived from the eviction process of an old popular district in the city of São José dos Campos, São Paulo, Brazil, we analyze how an idea of neighborship is applied to the processes of struggle and their outcomes. In 2004, a land of over 1,000,000 m2, owned by a bankrupt industry, was occupied by an entire district of over 5,000 people. This “illegal” occupation had been going on for almost 8 years when a court decision ordered the land to be vacated. The case of the Pinheirinho dos Palmares neighborhood, as it was known, became an emblematic example of Brazilian housing policies, with its violent eviction drawing the entire country’s attention. This article deals with the struggles that the evicted residents started and that resulted, at the end of almost 5 years, in the construction of a new district by the state, based on a new housing program. We are going to analyze how concerns about organizing the new neighborship from the old neighborhood relations were fundamental in the geographical and architectural production of the new district. The article seeks to intertwine the notions of resistance and neighborship, responsible for the new configuration of the district.

An efficient mixed-variable generation operator for integrated energy system configuration optimization

Energy consumption has skyrocketed as society has progressed, resulting in energy crises and environmental issues. New energy technologies are being developed to address these challenges, and technologies such as the cogeneration of electricity, heating, and cooling are being used to improve energy utilization. The configuration of an energy system has a critical impact on the economics of the system, its ability to supply energy, etc. This study establishes a multiobjective mixed-variable configuration optimization model for a comprehensive combined cooling, heating, and power energy system. The model considers equipment types (categorical variables), equipment quantities (integer variables), and critical parameters (real variables) as optimization variables, where economic performance, the proportion of renewable energy, supply shortage, and dependence on the external power grid are considered unoptimized objectives. This is a multiobjective and mixed-variable problem, and the combination of the two properties poses an excellent challenge for evolutionary algorithms in optimizing the model. Therefore, we propose an efficient generating operator based on a fully connected weighted neural network, called the FCWN operator. This operator overcomes the challenge of the discrete variable space and broken neighborhood relationships in mixed-variable problems. During the algorithm search process, search history information is used to update the fully connected weight network for distribution estimation of the variable space. Offspring are generated based on the fully connected network to improve the algorithm’s search efficiency. In the experimental section, we construct a model with 20 variables and conduct simulation-based configuration optimization for scenarios with 3, 5, and 8 available equipment types. The final obtained Pareto frontier solution set is evaluated using the hypervolume metric, a widely used multiobjective evaluation metric. The Wilcoxon rank sum test on the experimental results shows that the proposed algorithm has better results than other state-of-the-art algorithms at a 95% confidence level.

A fast detection method for building wood measurement based on interval type-2 fuzzy model

Automatic measurement detection in the process of wood processing can effectively improve production efficiency and yield to promote upgrading the wood processing industry. Therefore, this article researches visual detection technology for wood surface measurements and proposes a construction wood measurement detection method based on interval type-2 fuzzy theory. This method overcomes the problem of increasing heterogeneity and similarity of homogeneous areas on the wood surface, which increases the difficulty of measurement detection. Firstly, the Gaussian model is improved by establishing a wood measurement image feature model that considers rate neighborhood relationships as the basic model. Then, the basic model is fuzzified to construct an interval type-2 fuzzy model (IT2FM) to characterize the uncertainty features of the modeling and achieve measurement detection of building wood. We conducted experiments using a wood measurement detection dataset to study the influence of the construction form of IT2FM on wood measurement detection and evaluated the results using kappa values. The detection accuracy of this method is improved by about 10% compared to traditional machine learning and deep learning methods, and it only takes about 3–5 s to run the program. The experimental results show that the proposed method can effectively suppress the noise generated by wood measurement detection and prevent missed detection. It can achieve high-quality measurement detection of wood dead knots, loose knots, and cracked parts.

RCPM_CFI: A regional core pattern mining method based on core feature influence

Regional co-location pattern mining is a branch of spatial co-location pattern mining, which is used to discover co-location patterns that prevalently co-occur in local regions. The regional co-location patterns can reveal the association relationships among spatial features in the local regions. However, in practice, the association relationship between certain features is asymmetrical, and some features play a key (core) role in the relationship, as central position. To explore the regional co-location patterns with core feature (called regional core patterns (RCPs)) as well as their prevalent regions, this paper presents a regional partition method based on the influence of core feature. Additionally, a regional core pattern mining (RCPM) algorithm is proposed to mine the RCPs and unveil their spatial distribution resulting from the arrangement of core feature. In the regional partition stage, we propose a partition criterion that takes into account the influence of core feature. This criterion aims to comprehensively address the spatial distribution relationship between core instances and their neighboring non-core instances, ensuring the partition process is rational and complete. In the RCPM stage, we propose a core-based nearest affiliation measure method to assess the neighbor relationship between core and non-core instances, which can consider the fact that there is competition between spatial instances of the same spatial feature. And, to effectively calculate pattern prevalence and quickly identify RCPs, we present a data structure called Core_Hash to store the influence relationship between core and non-core instances. Extensive experimental evaluations and analyses are conducted on synthetic and real-world datasets. Compared to the existing algorithms, our proposed algorithms yield more reasonable and comprehensive RCPs and demonstrate good efficiency and scalability.

Research Method for Ship Engine Fault Diagnosis Based on Multi-Head Graph Attention Feature Fusion

At present, there are problems such as low fault data, insufficient labeling information, and poor fault diagnosis in the field of ship engine diagnosis. To address the above problems, this paper proposes a fault diagnosis method based on probabilistic similarity and rank-order similarity of multi-head graph attention neural networks (MPGANN) models. Firstly, the ship engine dataset is used to explore the similarity between the data using the probabilistic similarity of T_SNE and the rank order similarity of Spearman’s correlation coefficient to define the neighbor relationship between the samples, and then the appropriate weights are selected for the early fusion of the two graph structures to fuse the feature information of the two scales. Finally, the graph attention neural networks (GANN) incorporating the multi-head attention mechanism are utilized to complete the fault diagnosis. In this paper, comparative experiments such as graph construction and algorithm performance are carried out based on the simulated ship engine dataset, and the experimental results show that the MPGANN outperforms the comparative methods in terms of accuracy, F1 score, and total elapsed time, with an accuracy rate of 97.58%. The experimental results show that the model proposed in this paper can still fulfill the ship engine fault diagnosis task well under unfavorable conditions such as small samples and insufficient label information, which is of practical significance in the field of intelligent ship cabins and fault diagnosis.