Entropy Index Research Articles

Research on the Analysis Model of Regional Economic Growth Differences in China Based on Big Data and Intelligent Algorithms

China’s growing economy contributes significantly to worldwide consumption. Economic rebalancing promises opportunities for manufacturing exporters, and that can weaken commodity demand in the long term. China exerts increasing influence on emerging countries through trade, investment, and ideas. China faces several important economic issues that can hinder future development, including distortive economic policies that have evolved into an overreliance on fixed investment and exports for economic growth, government assistance for state-owned businesses, and a weak banking system. Building an information infrastructure and enhancing the technical level and application capability of big data (BD) remain under the purview of the Chinese Government. Artificial intelligence (AI)-based hybrid artificial neural network (HANN) might boost total factor productivity by a large margin, influencing many sectors in China in ways that official statistics would miss, including changes to the labor market, investment patterns, and overall productivity. Hence, BD-HANN has a coefficient of variation, quantity graph analysis, standard deviation, and entropy index, some of the most conventional quantitative research tools used to examine disparities in regional economic growth. According to the neoclassical growth model, regions with lower starting values of the capital-labor ratio anticipate higher per capita income growth rates. Thus, poor areas will grow faster than rich ones, assuming that the only difference between regional economies is the level of their initial stock of capital.

Urban Greenway Planning and Designing Based on MGWR and the Entropy Weight Method

Travelers’ attention to high-quality human habitats is increasing, and the role of urban greenways in improving the quality of travelling spaces has also been appreciated. This research aims at making the weight calculation of suitability more scientific and reasonable, clustering the shared bicycle travelling OD points according to suitability, and analyzing the distribution of OD points. Taking Xiamen as an example, multiscale geographically weighted regression and entropy weight methods were used to calculate the weights of variables using multi-source big data. The clustering of origin-destination (OD) points for shared bicycle travel are identified using the DBSCAN clustering algorithm, which can provide accurate support for greenway planning and shared bicycle placement. The results show that the density of tourist attractions, POI entropy index, road density, and intermediate are four important factors affecting the suitability of greenways. The clustering results of the shared bicycle OD points show that the high-aggregation areas of origin and destination points are located in the northeast and southwest directions as well as west and east directions. This study provides a theoretical and modelling analysis reference for greenway planning and design.

Zmiany entropii terenów zabudowanych w otoczeniu Krakowa w latach 2014-2020

Information on landscape structure is an important issue for sustainable development and for making correct spatial planning decisions. Therefore, studies providing information on the diversity and changes of land cover and land use in a selected area are currently an important research topic. In addition to quantitative-qualitative statistics, spatial entropy is increasingly used to assess the degree of diversity of land cover and land use. This paper aim was to determine the diversity of objects within the land cover classes in the years 2014, 2017 and 2020, with a focus on built-up areas, in three districts bordering the city of Kraków, i.e. the Wieliczka, Kraków and Proszowice districts, located in the Małopolskie Voivodeship in Poland. In order to perform the analysis with the appropriate spatial resolution, a hex grid was used to determine the diversity of objects in the built-up area class. For this reason, data on land cover from the BDOT10k national database of topographic objects were used. The analyses followed the division into classes and objects defined in the structure of the BDOT10k database. The degree of diversity was determined using the Entropy Index and Herfindahl-Hirschman Index. Changes in the diversity of built-up areas were observed especially in areas located in close proximity to the border of Kraków, as well as on its eastern and south-eastern sides. A significant relationship was also observed between the increase in diversity of objects in the built-up area class and the immediate proximity of roads.

Comparying two methods of disparity analysis of the anterior portion of m1 in the gray voles (Rodentia, Arvicolini) in a model sample: frequency analysis of morphotypes and geometric morphometrics

An analysis of disparity of the anterior portion of m1 shape in the gray voles in an artificial sample consisting of 5 groups with different frequency distributions of 5 morphotypes was carried out. Two main approaches were applied: (a) traditional analysis of frequency distribution of discrete morphotypes and (b) geometric morphometrics (GM) based on a strictly quantitative description of the shape of anterior portion of m1. The groups were compared quantitatively: Cavalli-Sforz–Edwards’ coefficient was applied in the first case, while the thin plate spline and Procrustes analyses in the second; their results were analyzed using a number of standard statistical methods (dispersion analysis, discriminant analysis, multidimensional scaling). Disparity within the groups was assessed using Shannon entropy index and averaged Procrustes distance. Traditional and GM approaches were shown to provide very similar results, with GM having a number of important advantages by being strictly quantitative. The second approach is recommended as the basic to replace the traditional one for explorations in disparity of tooth crown shape in the voles.

How to improve public environmental health by facilitating metro usage on weekend: exploring the non-linear and threshold impacts of the built environment.

The accelerated motorization has brought a series of environmental concerns and damaged public environmental health by causing severe air and noise pollution. The advocate of urban rail transit system such as metro is effective to reduce the private car dependence and alleviate associated environmental outcomes. Meanwhile, the increased metro usage can also benefit public and individual health by facilitating physical activities such as walking or cycling to the metro station. Therefore, promoting metro usage by discovering the nonlinear associations between the built environment and metro ridership is critical for the government to benefit public health, while most studies ignored the non-linear and threshold effects of built environment on weekend metro usage. Using multi-source datasets in Shanghai, this study applies Gradient Boosting Decision Trees (GBDT), a nonlinear machine learning approach to estimate the non-linear and threshold effects of the built environment on weekend metro ridership. Results show that land use mixture, distance to CBD, number of bus line, employment density and rooftop density are top five most important variables by both relative importance analysis and Shapley additive explanations (SHAP) values. Employment density and distance to city center are top five important variables by feature importance. According to the Partial Dependence Plots (PDPs), every built environment variable shows non-linear impacts on weekend metro ridership, while most of them have certain effective ranges to facilitate the metro usage. Maximum weekend ridership occurs when land use mixture entropy index is less than 0.7, number of bus lines reaches 35, rooftop density reaches 0.25, and number of bus stops reaches 10. Research findings can not only help government the non-linear and threshold effects of the built environment in planning practice, but also benefit public health by providing practical guidance for policymakers to increase weekend metro usage with station-level built environment optimization.

Income Inequality Analysis in Sumatra (Case Study of South Sumatera, North Sumatera, West Sumatera Province)

One indicator of an area of high economic growth is a low level of income inequality. This study aims to determine the development of income inequality that occurs in the provinces of South Sumatra, West Sumatra and North Sumatra, as well as classify and analyze the province based on economic growth and income inequality. The Data used in this study is time series and cross section data with a six-year observation period of 2018-2023 with 3 provinces in Sumatra yajni South Sumatra, West Sumatra and North Sumatra. The methods of analysis used in this study are Wiliamson index analysis, Theil Entropy index analysis, and Klassen typology analysis. With the results of the study, the average level of income inequality in 2018-2023 is in the range of 0.30 to 0.59. The highest income inequality is in the province of South Sumatra 0.59 and North Sumatra 0.45. Inequality in West Sumatra province is at 0.30 then it is categorized as moderate inequality. From Klassen's typological analysis, using the average Wiliamson index in 2018 to 2023, South Sumatra is in Quadrant II which is a fast-growing region, West Sumatra and North Sumatra are in Quadrant IV of the relatively underdeveloped region. From the results of Klassen typology analysis in 2018-2023 regencies or cities in West Sumatra province are in Quadrant II and Quadrant IV, regencies/cities in North Sumatra are in Quadrant I, quadrant II and quadrant IV. While the district / city in South Sumatra province located in Quadrant II and Quadrant IV.

Defining neighborhood walkability for children in the ELFE cohort study

Abstract Background Although walkability is known to be associated with obesity in adults, there is a paucity of data evaluating the association of walkability and health outcomes in children. In particular, little is known regarding the possible association with children’s mental health. Methods We used data from the Etude Longitudinale Française depuis l’Enfance (ELFE) cohort study. Participating mothers gave birth in 2011 in a representative sample of 320 maternity hospitals in mainland France. This pilot study is limited to participants in Paris and children at 5.5 years old. Walkability is defined by three parameters: population density (defined by census data), street connectivity (defined by intersection density), and land-use mix (entropy index). To approximate walkable areas, 500-meter street-network buffer zones were created around each participants address using a geographic information system. Children’s mental health was assessed using parent-reported Strengths and Difficulties Questionnaire at age 5.5 years. Results There was a total of 280 children in this pilot study. On measures of land-use mix, we found a mean of 0.79 (SD: 0.12), representing high accessibility. Residential and intersection density were highly correlated (p < 0.01). The walkability index demonstrated high variability among participants (mean: 10.6; SD: 10.44; range: -1.67 - 30.59). Conclusions Developing a walkability index is a multifactorial measure to describe a children’s neighborhood environment. Future work includes determining the association with children’s mental health disorders, while accounting for individual and neighborhood variables. This ecological model can inform social epidemiology and contextual disparities in children’s health. Key messages • Little is known about neighborhood walkability and the association with children’s mental health. • Using objective measures to calculate neighborhood composition and help elucidate this relationship.

Integrating the frequency ratio and index of entropy with an extreme learning machine to map post-earthquake landslide susceptibility: a case study in Xingwen County, China

Integrating the frequency ratio and index of entropy with an extreme learning machine to map post-earthquake landslide susceptibility: a case study in Xingwen County, China

Access to bus services: an analysis of the influence of land use types

ABSTRACT During travel, commuters are naturally influenced by built environment factors, particularly land use types. However, the existing literature overlooks this impact and neglects the application of the adjusted Gaussian two-step floating catchment area method in studying accessibility to metro. To analyse the influence of land use types on accessibility to transit and the nature of such influence, we employed the adjusted Gaussian two-step floating catchment area method in measuring accessibility and the entropy index in gauging land use diversity. We also deduced the changes in accessibility scores to capture the effects of land use types. Additionally, we examined the differences in the bus and metro accessibility scores to clarify the influence of each mode. The accessibility scores in the study area were influenced by the land use types within it, and this influence was significant in the core administrative districts. These findings will support policymakers in land use and public transport planning.

Exploring the fundamental properties and MGF of a 3-component mixture of power distributions: a simulation study

This paper estimates the parameters of the 3-component mixture of power distributions. The expressions of fundamental properties of the said distribution are presented, and for judgment, the numerical results of mean, median, variance, mode and skewness are evaluated. The closed-form expressions of the reliability properties, the statistical properties and necessary inequality measures are discussed. The trend of reliability measures is shown with the help of numerical results and graphs by taking different values of parameters and proportion parameters. The mathematical expressions of certain related statistical functions are derived from the reliability functions, the moment generating function, the characteristics function, the probability generating function, and the factorial moment generating function. The expressions of essential entropies, Shannon’s entropy, the B-entropy and Renyi’s entropy, are derived. The mathematical expressions of inequality indexes, the Gini index, the Lorenz curve, the Bonferroni curve, the Zinga index, the Atkinson index and the generalized entropy index are also analysed. The RF, the HRF, the CHR, the RHR, the MRL, and the MWT functions are derived in reliability analysis. The numerical values and graphs for different parameters and proportion components are discussed to judge the behaviour of reliability properties.

Enhancement Method Based on Multi-Strategy Improved Pelican Optimization Algorithm and Application to Low-Illumination Forest Canopy Images

Enhancement is a crucial step in the field of image processing, as it significantly improves image analysis and understanding. One of the most commonly used methods for image contrast enhancement is the incomplete beta function (IBF). However, the key challenge lies in determining the optimal parameters for the IBF. This paper introduces a multi-strategy improved pelican optimization algorithm (MIPOA) to address the low-illumination color image enhancement problem. The MIPOA algorithm utilizes a nonlinear decreasing coefficient to boost the exploration ability and convergence speed, whereas the Hardy–Weinberg principle compensates for the unsound exploitation mechanism. Additionally, the diversity variation operation improves the ability of the algorithm to escape local optimal solutions. The performance of the proposed MIPOA algorithm was evaluated using a benchmark function and was found to outperform five variant algorithms in extensive comparisons. To further harness the potential of the MIPOA algorithm, the authors propose a low-light forest canopy image enhancement method based on the MIPOA algorithm. The MIPOA algorithm searches for the optimal parameters of the IBF, leading to fast contrast enhancement of the image. The segmented gamma correction function is designed to enhance the brightness of the low-light forest canopy images. In determining the optimal parameters of IBF, the MIPOA algorithm demonstrates superior performance compared to other intelligent algorithms in the feature similarity index (FSIM), entropy, and contrast improvement index (CII) of 75%, 58.33%, and 75%, respectively. The proposed MIPOA-based enhancement method achieves a moderate pixel mean and surpasses the conventional enhancement method with an average gradient of 91.67%. The experimental results indicate that the MIPOA effectively addresses the limitations of low optimization accuracy in IBF parameters, and the enhancement method based on the MIPOA provides a more efficacious approach for enhancing low-light forest canopy images.

Application of the Decision Tree Method for Differentiating Human Groups

One of the tasks of modern biological anthropology is to develop a system that could objectively classify humanity on the basis of measurements. Here, the decision tree algorithm was chosen to create a classification of groups. The method helps to evaluate the differentiating power of specific dimensions for separating samples and to assess the composition of clusters at each step of the analysis. Standard cranial measurements were used, and the entropy index was chosen as a heterogeneity measure. Classification units were 39 ethno-territorial groups from 13 major regions of the Old World. At the first step, differentiation is made between broad-faced and narrow-faced groups, demonstrating the classificatory value of this trait. The first cluster includes only Mongoloids, admixed Southern Siberian populations, and Ainu. The second cluster is heterogeneous, but its further subdivision is more in line with the traditional classification. Traits underlying the branching of the tree may be the same in different branches, evidencing their taxonomic importance. Capabilities of the decision tree method proved sufficient to construct a system largely similar to the traditional one. Certain traits separate large groups of populations, while others are efficient at the regional level. The method, therefore, can be recommended as a supplementary tool at the intraspecific level.

Residential Segregation of Foreign Immigrants in South Korea by Country‐of‐Birth Income

ABSTRACTThis study examines changes in spatial distribution and residential segregation patterns of immigrant groups in South Korea from 2008 to 2021. Since the mid‐1990s, the immigrant community has increased rapidly; however, geographical stratification has intensified among heterogeneous immigrant groups. Foreign immigrants from 195 countries are divided into four groups based on the average income in the country of birth. Dissimilarity and multigroup entropy indices were adopted to explore the aspatial aspects of immigrant segregation. Exploratory spatial data analysis was used to examine the spatial separation of foreign clusters. The implications of these results are threefold. First, immigrant residential segregation is as serious as in developed countries and has deepened. Second, immigrants from advanced economies are concentrated in Seoul, while immigrants from upper‐middle economies are clustered in the southwestern part of the capital region. In contrast, immigrants born in lower‐middle class and underdeveloped countries are distributed among rural and manufacturing areas in the non‐capital region. Finally, the differences in the course of economic migration according to socioeconomic background are considered to be the decisive cause of the spatial segregation of immigrants. This study challenges policymakers engaged in integrating immigrant communities in South Korea.

Developmental noise, entropy, and biological system condition.

Developmental noise is considered as a permissible level of entropy, as a compromise between the cost and needed precision of the realization of genetic information. In terms of entropy, noise is a measure of acceptable level of disorder to ensure a reliable system operation. Developmental noise plays a role in the observed phenotypic diversity and is associated with other indicators of the biological system condition. The thermodynamic characteristic of entropy by the energy metabolism also turns out to be related to the developmental noise. Phenotypic variability is largely determined by developmental homeostasis, including both canalization (an ability to form a similar phenotype under different conditions) and developmental stability (a capability for perfect development measured by noise level). It is shown that the change in the noise level, as an expression of the certain entropy level, unlike other forms of phenotypic variability, is a reflection of a change in the system condition. Although the entropy indices of ontogeny and community under certain conditions can change simultaneously, the entropy index at the level of developmental noise proves to be a more unambiguous and universal measure of the disorder of a biological system, compared to biodiversity indices at the community level.

Increased bird sound diversity in vineyards enhances visitors' tour experience

Abstract Biodiversity is rapidly declining, reducing the quantity and quality of human interactions with nature and constraining its contribution to human health and well‐being. Natural sounds are a key component of our experience of nature, but biodiversity losses are reflected in soundscapes, which are becoming less diverse and quieter. We characterised the soundscapes across 21 English vineyards using acoustic indices and related them to bird species richness and abundance. We found that higher bird species richness, but not abundance, led to more diverse and louder soundscapes, as reflected in higher values of Acoustic Complexity Index (ACI), Bioacoustic Index (BIO) and Normalised Difference Soundscape Index (NDSI), and lower values of Acoustic Entropy Index (H). Secondly, at three of the study vineyards that run vineyard tours, we measured visitors' experience of the tour in terms of sound enjoyment, soundscape connectedness and tour satisfaction and related these to ambient and experimentally enhanced soundscapes, where we used playback recordings of five additional birdsongs to increase the soundscapes' complexity and volume. Under ambient conditions, respondents' (n = 107) experience was significantly higher at sites with soundscapes that had higher ACI and BIO values, and lower H, Acoustic Diversity Index (ADI) and NDSI values, indicating a positive effect of more diverse and louder soundscapes. Natural sounds formed an important part of the tour experience at these sites, making visitors feel more present and connected to nature. Under experimental soundscape enhancement, respondents (n = 79) reported hearing significantly more bird species during the tour, and they reported significantly higher scores for sound enjoyment, soundscape connectedness and tour satisfaction than under ambient conditions. This effect was stronger in visitors who engaged more in pro‐environmental behaviours, such as purchasing organic foods. Our study demonstrates (i) the direct contribution of aural modes to our experience of nature and (ii) that the delivery of biodiversity conservation measures aimed at supporting bird diversity could simultaneously enhance the experience and well‐being benefits of spending time in nature. Natural soundscapes should therefore be recognised and valued as natural capital, and their protection should be incorporated into conservation planning and policy. Read the free Plain Language Summary for this article on the Journal blog.

Population genetic analysis of the Lviv region based on surname data

Aim. The study aimed to determine indicators characterizing the population structure of the Lviv region. Methods. The study employed the method of describing the genetic structure of the population using surnames, as proposed by I. Barrai. Results. Indicators of population structure in district populations of the Lviv region exhibited a wide range of values. The basic index, the isonymy index (I), varied between 2.3 and 26.5 (×10-4). The inbreeding coefficient (FST) ranged from 11.2 to 66.1 (×10-5), the migration index (v) from 70.8 to 212.9 (10-4), the diversity index (a) from 3.8 to 22.9 (×102), the entropy index (H) from 10.0 to 13.0, and the redundancy of surnames (R) from 26.1 to 36.2. In some settlements, there is an accumulation of bearers of the same surname, which can be explained by the founder effect. Conclusions. The rates of isonymy, inbreeding, and migration in district populations were several times higher than those observed in the regional population. The level of isonymy was lowest in areas with high tourist and transit activity.

The Sombor Indices of Banana Tree Graph and Fractal Tree Type Dendrimer

Topological descriptors are graph-theoretical metrics that allow one to describe a molecular structure’s underlying connectedness. Degree-based topological descriptors have been investigated widely and are associated with several chemical characteristics. The examination of graph entropy indices as a gauge for the intricacy of the underlying connection and as a means of characterizing structural attributes has also gained significance.The present study utilizes the graph-theory-based edge partition method to examine Sombor variants for the Banana Tree Graph, Fractal, and Cayley Tree Type Dendrimers. We have employed Shannon’s entropy model to determine the graph-based entropy of these graphs and produced Sombor indices.

The spillover and comovement of downside and upside tail risks among crude oil futures markets

Combining efficient transfer entropy and DY spillover indices, this study first explores the contagion effects of downside and upside tail risks among INE, Brent, and WTI. Then we utilize wavelet coherence to capture the comovement characteristics of tail risks at multi-time scales. Furthermore, by mapping wavelet coherence information into comovement networks, the diversity and regularity of mode conversions of tail interdependency are investigated in depth. The results show that INE is reactively susceptible to the tail risk spillovers from Brent and WTI, and in terms of the magnitude of spillover to INE, Brent surpasses WTI prominently. The coherence between the tail risks of INE and Brent or WTI is much weaker than that of the Brent-WTI pair, especially in the short term or in the upside tail case. The evolution of downside tail risk comovement is more difficult to stabilize. A few comovement modes show a significantly higher probability of occurrence than others, and they also tend to link each other. Of special note are some comovement modes with low probability of occurrence yet behave as the key “bridges” in the mode transformation process.

Adaptive stepsize forward–backward pursuit and acoustic emission-based health state assessment of high-speed train bearings

Compressed sensing (CS) is a promising tool for data compression reconstruction. However, fault diagnosis methods for high-speed train bearings based on CS and acoustic emission (AE) technologies have not been reported yet. Notably, the accuracy and speed of CS two-stage reconstruction methods are affected and restricted by prior initial conditions. Therefore, this article proposes adaptive dynamic thresholds applicable to adaptive stepsize forward–backward pursuit (ASFBP), and bearing health state assessment method. First, the adaptive dynamic thresholds for atom selection and deletion are constructed based on the residual feedback mechanism and the atom quality distribution law, which enables ASFBP to realize high-precision rapid reconstruction of signal without any atom priori initial conditions. Second, the initial dictionary length is improved based on the AE hit characteristics. Furthermore, a damage state comprehensive evaluation index (DSCEI) is established using principal component analysis based on AE time-domain hit parameters and compression-domain energy parameter. Compared with the kurtosis index and permutation entropy index, the DSCEI demonstrates better monotonicity and stability in the quantitative evaluation of high-speed train bearing condition. Finally, the validity and stability of the method are verified by testing under complex test conditions resembling actual high-speed train lines, providing valuable insights for the CS-based data-driven bearing fault diagnosis.

Diverse pathways to permanent childlessness in Singapore: A latent class analysis.

The proportions of adults reaching midlife without having children have been rising rapidly across the globe, particularly in Asia. However, little is known about the pathways to permanent childlessness within the region's childless population. This study utilized latent class analysis (LCA) to typologize pathways to childlessness based on dynamic characteristics of multiple life domains (i.e., partnership, education, and occupation) among 489 childless Singaporeans aged 50 and above from a 2022 nationwide survey. Additionally, we utilized multinomial logistic regressions to examine the sociodemographic correlates of pathway profiles and Shannon's entropy index to assess the heterogeneity in pathways to childlessness among successive cohorts. Results revealed five distinct profiles of pathways to childlessness: the Never-Married Semi-Professionals, the Low-Flex Blue-Collars, the Highly Educated Professionals, the Ever-Married Semi-Professionals, and the Flexible Blue-Collars. These pathway profiles were significantly associated with sociodemographic characteristics such as gender and family background. Women's pathways to childlessness were more standardized and heavily influenced by partnership characteristics, compared to those of men. The childless from privileged family background were less likely to follow pathways characterized by disadvantageous education and occupational status. There were also rising trends of voluntary childlessness among married childless individuals and increasing heterogeneity in pathways to childlessness across successive birth cohorts. In sum, our findings are consistent with some of the predictions of the Second Demographic Transition theory, suggesting that Singapore may be experiencing a demographic transition characterized by rising childlessness, decoupling of marriage and childbearing, and de-standardization of the life course.