Abstract
Painting is a two-dimensional visual language that expresses ideas and emotions while also creating aesthetic aspects. Flower and bird painting embodies an aesthetic ideal. For Chinese people, it serves as a harmonious coexistence with natural objects. Based on the contemporary context and the concept of environmental aesthetics, flower and bird painting should go beyond the sensual portrayal of plants and animals, individualistic lyricism, and the tendency of commercialization. It helps to examine the important value of plants and animals in the spiritual life of human beings from the perspective of the community of human destiny. It also raises the concern of contemporary people for the natural environment and the survival status of natural objects. Free from one’s sorrow and happiness, the painting focuses on the pressing ecological issues of universal concern to all mankind and becomes art with world significance expressed in Chinese aesthetic symbols and artistic forms. It is important to classify the teaching resources of Chinese flower and bird painting theory and time. The traditional Chinese flower and bird painting theory and practice course teaching resources classification method are inefficient; for this reason, the adaptive clustering algorithm of teaching resources of Chinese flower and bird painting theory and practice is proposed. Using mutual information technology to obtain incremental data, the digital Chinese flower and bird painting theory and practice course teaching resources features are extracted. It features a tree to be constructed according to the two-step clustering algorithm. The leaf nodes of the feature tree are grouped according to the hierarchical coalescence algorithm. The Euclidean square distance is used to obtain the Chinese flower and bird painting theory and practice course teaching resources square root measure continuous variables. The number of clusters with the maximum growth distance represents the final number of clusters. The results show that the method can realize the effective grouping and classification of Chinese flower and bird painting theory and practice course teaching resources.
1. Introduction
Painting is an art category that understands the natural world by reproducing the form, color, and charm of the perceptual appearance of specific objects such as animals and plants [1–3]. The physical properties, shapes, and structures of some plants have certain similarities and analogies with the Confucian expectations of the ideal of personality [4–6]. They have become the ethical symbols of the Confucian ideal moral personality [7, 8]. After the Song Dynasty, with the rise of literati painting, flower and bird painting have become a medium for painters to express their thoughts, feelings, and self-mood [9]. In the eyes of the ancient Chinese, this world is a harmonious world where all things coexist. People know themselves in the cognition of natural objects and construct a spiritual home of “harmony between man and nature” in art [10, 11].
The ideals of harmonious coexistence between man and nature in flower and bird paintings have encountered new challenges in contemporary times. After the baptism of biology and other related scientific knowledge, the understanding of animals and plants has surpassed all the ancients [12, 13]. The spiritual connotation of flower and bird painting is viewed from the perspective of environmental aesthetics, which is the product of anthropocentrism. Animal and plants are the only objects of the subject’s emotional expression and empathy, while objects without a subject have no inherent independence [14, 15]. Flower and bird painting has reached the peak of Chinese painting expressive art in the depth and breadth of expressing the spiritual dimension and emotion of the ancients [16].
Flower and bird painting is a figurative expression of the ancient Chinese people’s spirit of identifying natural objects, expressing subjective emotions, and constructing harmony between man and nature. The Song Dynasty was the peak of the development of flower and bird painting. Song Confucianism advocated “learning from objects” and applied it to understand all aspects of society, culture, and nature. They believe that there is the same principle between nature and human society as well as everyone, and painters can better understand themselves by studying nature carefully [17]. In painting, it is the realism of “taking the image as it is,” which pays attention to the grasp of the external “shape” and internal “principle” of natural objects. In the static, in-depth observation of the forms and living habits of animals and plants, the painter forms a meticulous and rigorous painting of flowers and birds in the academy, pays attention to the law, and pursues poetic aesthetics in the real depiction [18, 19]. Literati participated in painting evaluation and creation and expressed their emotions and thoughts in the paintings. Some plants were endowed with moral symbolic meanings because of their similarity and analogy with Confucian expectations of ideal personality. In the rise of literati culture and freehand flower and bird painting in the middle and late Ming Dynasty, the painters represented by Xu Wei [20, 21], Chen Chun, and later Zhu Zhang had many personal experiences and fates, which made flower and bird painting transcend the limitations of pictograms and names. The splashed ink and boldly cut composition express strong personal emotions and grief for the motherland. Every flower, one tree, one fish, and one bird become their sedatives for their wounded hearts and a spiritual portrayal of the fate of the people in the great era [21].
After modern scientific understanding “demythologized” old culture, classical art’s symbols and implications progressively faded from people’s daily lives and intellectual perspectives, becoming remote cultural representations. Contemporary flower and bird painting should not only focus on the breakthrough of formal language, but also on the content, which should transcend the limitations of the past, pay attention to the current problems, and try to build an artistic answer [10].
Making full use of digital teaching resources to enhance the intuitiveness of the curriculum during lectures has the advantage of broadening horizons and enhancing students’ thinking skills. The vividness of Chinese flower and bird painting theory and practice course classroom teaching is extremely important. The implementation of digital processing of Chinese flower and bird painting theory and practice course teaching resources can help improve the quality of Chinese flower and bird painting theory and practice course teaching. Clustering algorithm is an important algorithm that classifies things based on the similarity of different categories. The clustering algorithm, also known as point cluster analysis, is an important method of multivariate statistics that accurately classify things based on the characteristics that exist between things to be classified. There are many different types of features that can be found in things. Based on the features that exist between entities, classification results can be obtained without a priori knowledge. Many sectors, including sociology, education, psychology, and economics, have adopted clustering approaches [22–24].
Li et al. propose a classification prediction method for Docker container resource control and perform the classification of Docker container resource quality of service by group technology. Docker is a container resource service classifier. Using spectral clustering algorithm to predict the use of container resources can realize the effective utilization of container resources. The above two methods are studied for digital resources as well as container resources classification problems, respectively, and obtain a high classification effect. However, they are applied to Chinese flower and bird painting theory and practice course teaching resources with poor classification effects [25, 26].
To this end, an adaptive clustering algorithm for teaching resources of Chinese flower and bird painting theory and practice courses is proposed. The features are extracted, and the two-step clustering algorithm is used to implement the subsumption classification of resources based on the extracted features. The feature extraction can reduce the digital Chinese flower and bird painting theory and practice course teaching resources with higher dimensionality to lower dimensionality and reduce the dimensionality of the original teaching resources according to the fixed transformation rules. It will also provide data technology for the subsequent accurate grouping and classification. It is verified that this method is highly effective in classifying digital teaching resources and can be applied to the practical application of digital teaching resources.
The rest of the research paper is structured as follows; the coming section will explain the algorithms of adaptive clustering. It will be followed by analysis. Finally, the paper is concluded in section four.
2. Adaptive Clustering Algorithm for Teaching Resources of Chinese Flower and Bird Painting Practice and Theory Course
This section will explain the contemporary flower and bird painting practice and theory, digital Chinese flower and bird painting theory and practice course feature extraction, and two-step clustering algorithm for subsumption classification.
2.1. Contemporary Flower and Bird Painting Practice and Theory
Since the twentieth century, the most urgent problem facing mankind is the rapid deterioration of planet Earth’s environment due to rapid industrialization. The accompanying crisis of survival of mankind and all living things also play a negative role. Environmental philosophies that emphasize the need to maintain the balance of the diversity of life on Earth have emerged. They believe that this planet is not exclusive to human beings, who can take resources at will without limit, but it is a world where all species coexist and are ecologically balanced.
Bird and flower painting, which embodies the concept of harmony between man and nature, is still confused by the rudeness and superficiality of natural objects. It needs to be rationalized and scientific at the intellectual level. In terms of content, it should transcend the parochialism of one’s own emotions in the past and face the broader reality of human destiny. An abstract can no longer exist after detaching from the present life. We should return to reality, face the urgent ecological problems facing mankind today, and build a modern and artistic solution rooted in the Chinese tradition.
In response to the problem of superficial understanding of natural objects in bird and flower painting, Canadian environmental aesthetician Alan Carlson’s “scientific cognitivism” provides a reference for us to solve this problem. He believes that the aesthetic appreciation of natural objects should not only be at the perceptual level but also should be based on relevant knowledge. This scientific knowledge about a specific natural object can help us grasp the aesthetic characteristics of the given object more accurately. For example, biology tells us the secrets about the many individuals, species, and phenomena of life on earth, so that our natural aesthetic appreciation not only appreciates the external forms of various species of life, shapes, colors, sounds, etc., but also understands their habits and inner life characteristics in a more concrete and in-depth way. Scientific knowledge can not only ensure the principle of objectivity of aesthetic appreciation but also enhance and deepen the level of appreciation of the aesthetics of natural objects, making it possible for the aesthetic appreciation to have a higher level of appropriate, serious, natural aesthetics. Alan Carlson’s theory of “scientific cognitivism” highlights the important role of scientific knowledge in enhancing and deepening aesthetic experience, which, despite its shortcomings, can effectively address the overly subjective and sensual general position of the ancients in the appreciation of birds and flowers. It makes up for the phenomenon that the aesthetic experience of plants and animals only stays at the superficial level of “appreciation”, so that “natural things return to natural things” themselves. Only by deepening and elevating our appreciation of the external beauty of forms into rational recognition, and giving bird and flower painting a more solid scientific foundation, can we appreciate the aesthetic characteristics of natural objects, deepen and elevate our appreciation of the external beauty of forms into rational recognition, and give bird and flower painting a more solid scientific foundation.
Natural objects are not isolated from the human world. Their scientific understanding is necessary for a deeper and more objective understanding of the inner structure and aesthetic characteristics of the natural objects themselves. The second important element is to evoke a deeper understanding of natural objects on the basis of reflections on the current human behavior towards the destruction of natural ecology. The environmental crisis has become a common problem for all living organisms on earth, and the survival of natural objects is even more worrying. Born in an ancient farming society where productivity was not developed, flower and bird paintings reproduce the natural landscape where plants and animals grow and flourish and gradually become the spiritual totem of the nation and a cultural complex that can only be remembered on paper. The emotions and ideas contained in flower and bird paintings have also lost their objective conditions of the times. Contemporary painters pay attention to the living conditions of natural objects with the help of which they draw the public’s attention to the natural ecological crisis. This is an issue of the times faced by the community of human destiny and thus a “big self” that transcends individual and national limitations and self-expression. This big self is the position of the current human community. It reflects on the destruction of the ecological environment and the possibility of rebuilding the dynamic balance.
The ancient Chinese respected nature. They emphasized the vitality of natural objects and do not deny the importance of natural objects in human life. This concept is clearly reflected in literature and art works, such as poetry and painting, and should become one of the spiritual resources for the creation of flower and bird paintings nowadays. When appreciating natural objects, the ancients had a sympathetic heart; they put themselves in the place of the natural objects for a sympathetic experience and shared the fate of the natural objects, which is a deeper aesthetic appreciation of natural objects and the environment.
2.2. Digital Chinese Flower and Bird Painting Theory and Practice Course Feature Extraction
In the process of applying digital Chinese flower and bird painting theory and practice course teaching resources, with the increase of teaching course hours, the resource data is in incremental development trend. For this, new as well as historical data should be considered at the same time to achieve feature extraction based on the global perspective and avoid ignoring the hidden information contained in the resources. The adaptive sliding window mutual information method is used to process the historical data and incremental data of digital Chinese flower and bird painting theory and practice course teaching resources to realize the feature extraction of digital Chinese flower and bird painting theory and practice course teaching resources.
The matrix represents the original window data, and the matrix represents the incremental window data. All the data contained in the digital Chinese flower and bird painting theory and practice course teaching resources are represented by . and represent the mutual information matrix of the digital Chinese flower and bird painting theory and practice course teaching resources and the mutual information matrix of the original window data and the new window data. denotes the mutual information matrix of all samples of digital Chinese flower and bird painting theory and practice course teaching resources.
According to the definition of the mutual information, the expression of mutual information matrix is as follows:
The diagonalization process uses the unit array to represent the characteristic decomposition formula of as follows:
Using the projection of received in the space tensed by , the following equation is obtained:
The sum of Equation (1) and Equation (2) is obtained as follows:
The characteristic decomposition formula is as follows:
Substituting Equation (5) into Equation (4), the expression is obtained as follows:
Through the above process, the decomposition results of all digital Chinese flower and bird painting theory and practice course teaching resources features can be obtained.
Through Equation (2) it is known that:
In Equation (7), and denote the matrix composed of the first eigenvalues and the original digital Chinese flower and bird painting theory and practice course teaching resources principal component decision matrix, respectively.
Through the above process, the eigenvalues and the eigenvectors of the new window data mutual information matrix are obtained, and .
The formula for obtaining the eigenvalues of all digital Chinese flower and bird painting theory and practice course teaching resources samples based on the eigenvectors and eigenvalues is as follows:
In Equation (8), represents the sample data of historical digital Chinese flower and bird painting theory and practice course teaching resources; represents the sample data. The vector formula can be obtained as follows:
The obtained feature vectors are used to establish the principal component decision matrix. The digital Chinese flower and bird painting theory and practice course teaching resources are mapped to the established principal component decision matrix to achieve data dimensionality reduction. The above process is repeated in the subsequent windows to achieve feature extraction of all digital Chinese flower and bird painting theory and practice course teaching resources samples.
2.3. Two-Step Clustering Algorithm for Subsumption Classification
The two-step clustering algorithm mainly consists of two parts: constructing the feature tree and grouping by hierarchical coalescent algorithm.
Step 1. Constructing feature trees
The feature tree is constructed using example features derived from digital Chinese flower and bird painting theory and practice course education resources. The data categories and centers of different categories are determined after all of the sample data resources are scanned. These are divided into different categories according to the fixed criteria. The process describes the building feature tree S. The constructed feature tree uses the root of the leaf node to store the observed quantity of Chinese flower and bird painting theory and practice course teaching resources, and the information of all the variables contained is reflected through the leaf node. The existing nodes and subsequent observations are compared using the similarity measure. When the comparison result is the phase, the frost-like observation will be added to the fire now, and the book point A is similar to the result. New nodes are established in the feature tree until the comparison of all Chinese flower and bird painting theory and practice course teaching resources data is completed to realize the feature tree construction.
Step 2. Feature tree leaf node grouping
Selecting hierarchical cohesion algorithm grouping of the constructed feature tree leaf nodes, the algorithm operation process through the square root of the Euclidean square distance to achieve continuous variable measure, Euclidean distance measure formula is
The likelihood log distance is used to treat both continuous and categorical variables. It is the probability value obtained based on the distance. The likelihood logarithm decreases when different categories are combined into the same category, and the distance varies between categories.
Continuous variables and categorical variables need to conform to a normal distribution and polynomial distribution in the process of likelihood logarithm operation. When using likelihood logarithm distance to merge and classify digital Chinese flower and bird painting theory and practice course teaching resources, different variables are set to be independent.
The expression of the distance between category and category is defined as follows:
where denotes the classes obtained by the subsumption process.
The number of obtained classifications is initially estimated using the results of the classification operations of the above process using the BIC criterion. The number of clusters with the maximum growth distance between the two most similar classes in the initial classification is the final number of clusters.
The number of clusters is expressed by . The formula for calculating the final subsumption classification is as follows:
In the above formula, and denote the total number of continuous variables and the total number of observations in the merging classification process, denotes the number of leaf nodes, and and denote the number of the th variable to be classified and the total number of all categorical variables used in the merging classification process, respectively.
3. Analysis
The experimental item was a collection of digital Chinese flower and bird painting theory and practice course teaching tools from a college of Chinese flower and bird painting theory and practice course and science. The total memory was 5.98 GB (Gigabytes). The subsumption classification of the gathered materials was implemented using the two-step clustering algorithm.
The digital teaching Chinese flower and bird painting theory and practice course resources were set as the test variables, and the BIC results were used to determine the best classification. The BC automatic clustering results are shown in Table 1.
In general, the lower BIC value acquired by the clustering method indicates the better the clustering algorithm’s performance. In this way, the best quality of the clustered data created. The BIC values acquired decrease as the number of clusters increases, as shown in Table 1. Thus, the distance measurement ratio and the BIC change rate must be determined to identify the appropriate number of clusters. When the clustering measurement ratio findings are high and the BIC rate of change is similarly high, the clustering scheme is ideal. The experimental findings in Table 1 demonstrate that clustering produces the greatest clustering measurement ratio and the largest BC rate of change when the clustering category obtained is 4.
Figure 1 shows that the running time of various methods for grouping and classifying digital Chinese flower and bird painting theory and practice course teaching resources decreases as the window size increases. However, when the window size exceeds 600, the running time of various methods for grouping increases. The fundamental reason is that if the operation window is too narrow, the techniques must extract data from the buffer region, which takes too long. If the operation window is too big, the decomposition time of digital Chinese flower and bird painting theory and practice course teaching resources teaching materials features is improved.
Therefore, the best efficiency of digital Chinese flower and bird painting theory and practice course teaching resources subsumption and classification is achieved when the window interval is between 300 and 600. Compared with the other two methods, the subsumption classification efficiency of the two-step clustering algorithm is the highest in different window sizes. It indicates that the subsumption classification operation efficiency of this method is higher than the other two methods.
The correctness of subsumption classification of digital Chinese flower and bird painting theory and practice course teaching resources teaching materials is evaluated using the evaluation indices of recall, accuracy, and F1 estimate, which are often employed in subsumption classification.
When the F1 estimate value is more than 90%, the approach is more efficient in classifying objects. Statistics of the subsumption classification performance findings of this paper’s adaptive clustering approach are provided in Table 2.
The experimental results in Table 2 show that the accuracy of the subsumption classification of digital Chinese flower and bird painting theory and practice course teaching resources using the adaptive clustering algorithm of this paper and the degree of completeness of the search are higher than 98%. The F1 estimates are higher than 93%. The statistical results effectively verify that this method has a high performance of subsumption classification with a high accuracy rate and high applicability.
To further illustrate the performance advantages of the adaptive clustering algorithm proposed in this paper, the performance of the algorithm is analyzed on different artificial data sets, as shown in Figure 2. From Figure 2, it can be seen that the adaptive clustering proposed in this paper works better.
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4. Conclusion
In a nutshell, this research paper explains paintings with flowers and birds as an aesthetic ideal. It serves as a peaceful coexistence with natural items for Chinese people. Flower and bird painting should transcend beyond the sensual portrayal of plants and animals, individualized lyricism, and the commercialization trend, based on the modern context and the concept of environmental aesthetics. It aids in examining the significant role of plants and animals in human spiritual existence from the perspective of the human destiny community. It also arouses current people’s concern for the natural environment and the long-term viability of natural items. Here, the adaptive two-step clustering algorithm is applied to the classification of theoretical and practical teaching resources of Chinese flower and bird painting courses. It is used to improve the effectiveness of the classification of theoretical and practical teaching of a large number of samples. It can play an important role in the classification of theoretical and practical teaching resources and replaces the inefficient method of manual classification. The findings demonstrate that the technique can effectively categorize and classify Chinese flower and bird painting theory and practice course teaching resources.
Data Availability
The data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The authors declare that they have no conflicts of interest.