In response to the inadequate color-matching effectiveness and the difficulty of restoring color intentions in cultural heritage recreation, a Cultural Color interactive genetic algorithm (Cultural Color IGA) is propo...
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In response to the inadequate color-matching effectiveness and the difficulty of restoring color intentions in cultural heritage recreation, a Cultural Color interactive genetic algorithm (Cultural Color IGA) is proposed, which combines a color network model and a color harmony prediction model. First, the role of the color network model in providing color genes for subsequent design is emphasized. Then, a dataset of 10,743 color and color rating data points is used to train 12 color harmony prediction models, with the most efficient stacking model selected to improve the efficiency of user evaluation of color schemes. A prototype system for color regeneration is built in Python, and a user interface is designed. The example analysis is conducted using the Yungang Grottoes as the source of color imagery, and image colorization is tested. Independent experiments compare the proposed method with traditional IGA in terms of average fitness, maximum fitness, and evaluation time. Fuzzy evaluation is applied to assess the effectiveness of cultural heritage color regeneration design. The results show that the trained stacking model achieves an accuracy of 65.52% in color harmony prediction, outperforming previous methods. Compared to the traditional IGA algorithm, Cultural Color IGA reduces the number of user evaluations by 67.4%, improves the average fitness by 22.68%, and increases the maximum fitness by approximately 13.37%. Regarding cultural heritage color regeneration effectiveness, 80.6% of respondents considered the generated color schemes to be of good or higher quality. This method not only generates design solutions with high cultural representation and color harmony but also improves the efficiency and sustainability of the design process by reducing trial numbers and manual evaluation workload. It demonstrates the potential of digital technologies in the protection and sustainable application of cultural heritage color, offering valuable references for the dig
With the change in consumption environment and habits, the active feedback from users on online shopping platforms serves as a valuable source of information for analyzing user demand. Color design is an important fac...
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With the change in consumption environment and habits, the active feedback from users on online shopping platforms serves as a valuable source of information for analyzing user demand. Color design is an important factor in shaping product style and influencing user's purchase decisions. This study combines the Latent Dirichlet Allocation (LDA) and an interactive genetic algorithm (IGA) to investigate the usability of the interactivegenetic color selection method for wardrobe color design. Firstly, the LDA model was employed to cluster online review data to identify customer requirements (CRs), then summarize the perceptual evaluation factors (EFs) of color selection. Subsequently, the color selection information from market examples was used as reference to establish the initial population, and the interactivegenetic color design process was completed with CorelDraw. Then, the fuzzy comprehensive evaluation method was employed to evaluate the color scheme generated from IGA. The empirical analysis demonstrated that the interactivegenetic color selection method can effectively enhance both efficiency and satisfaction in wardrobe design. This study has substantial implications for both theory and practice in the field of wardrobe design and offers designers novel design concepts and methodologies.
interactive genetic algorithms can combine people's subjective emotions with geneticalgorithms, and can be used to solve some related problems that cannot be constructed functions. Many problems in people's d...
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interactive genetic algorithms can combine people's subjective emotions with geneticalgorithms, and can be used to solve some related problems that cannot be constructed functions. Many problems in people's daily lives can be seen as optimization problems with hidden goals. Because the main objective of this problem is difficult to quantify, corresponding calculation methods and subjective evaluations are needed to optimize these problems. This article demonstrates through the use of interactive genetic algorithms and relevant experimental results that this calculation method can improve customer satisfaction, thereby improving the optimization of some problems. This paper uses interactive genetic algorithm to protect the images of intangible cultural heritage of Guangxi ethnic groups, and establishes a VR display system of intangible cultural heritage images unique to Guangxi ethnic groups, and carries out relevant experiments and evaluations on these technologies, finally verifying the feasibility of this system. This system analyzes the corresponding genetic images of non-material culture, extracts some relevant characteristics, and establishes a relevant database. Finally, let some users experience the system and conduct relevant evaluations.
To show the unique charm of Jiangxis traditional culture, it is of great importance to apply Jiangxis unique red culture to products creative designs. This paper aims to apply Kansei Engineering (KE) and interactive g...
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To show the unique charm of Jiangxis traditional culture, it is of great importance to apply Jiangxis unique red culture to products creative designs. This paper aims to apply Kansei Engineering (KE) and interactive genetic algorithm (IGA) to extract the apparent symbol elements of Jiangxi red culture and then transform them into the creative watch design with modern culture. First of all, KE is used to extract customers emotional resonance to red culture, and 16 pairs of Kansei image vocabulary pairs are preliminarily collected. The theory of semiotics is used to extract symbols such as shapes, colors, and patterns from the perspective of Jiangxis red architecture. Secondly, through the designers subjective aesthetic thinking, these cultural symbols are broken up and reconstructed, thus forming the morphological deconstruction table combined with the case of the watch. Finally, IGA is implemented to code and decode the cultural symbols, thus building a product forms evolutionary design system. Through biological genetic manipulation, cultural symbols of refinement, particularity, and regionality are retained. Then these superior cultural genes are integrated into the innovation of the watch to get creative products with the characteristics of Jiangxi red culture. The model proposed in this paper optimizes the decision-making process of cultural creative product design, and also explores a sustainable development path of culture.
In recent years, the structure and function of suburban ecosystems have suffered severe damage due to unreasonable land use development and disorderly urban expansion. This has led to significant changes in regional c...
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ISBN:
(纸本)9798400709784
In recent years, the structure and function of suburban ecosystems have suffered severe damage due to unreasonable land use development and disorderly urban expansion. This has led to significant changes in regional climate, hydrological processes, biogeochemical cycles, biodiversity, and ecological environment problems. Consequently, it has become imperative to address the practical challenge of constructing a rational landscape safety pattern and reconciling the conflict between economic development and environmental protection within the spatial context. This challenge is particularly significant in the ongoing implementation of the national ecological civilization construction strategy. To optimize urban landscape planning schemes, this study proposes a method that incorporates resident opinions and utilizes interactive genetic algorithms (IGAs) for urban landscape design optimization. The method focuses on three key characteristics of the urban landscape: wall position, height, and building texture. An urban landscape design model is developed using OpenGL technology, and the IGA is employed to quantitatively evaluate user preferences. The design model is iteratively optimized based on the quantified results until users express satisfaction with the design. Experimental results demonstrate that this approach effectively quantifies user subjective opinions and ultimately achieves user-satisfactory design outcomes.
Grammatical error is an important problem in natural language processing, which can seriously affect the readability and comprehensibility of text. Traditional grammar error detection and correction systems based on r...
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In this study, we improved the dispensing accuracy of the automatic juice blending system in the previous study to optimize the mixing ratio of juices that match the preference of each user using an interactive geneti...
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ISBN:
(纸本)9783031428227;9783031428234
In this study, we improved the dispensing accuracy of the automatic juice blending system in the previous study to optimize the mixing ratio of juices that match the preference of each user using an interactive genetic algorithm (IGA). We verify the properties of the solution obtained by IGA by conducting subject experiments under an improved experimental environment that allows adjustment of the discharging of each juice with an accuracy of 100 ms. In addition, we analyze the difference in convergence tendency from the experimental results of the subject experiments when the design variable space is expanded.
In order to overcome the shortcomings of traditional fingerprint identification methods, such as low computational efficiency and high false classification rate, a new multi-information fingerprint identification meth...
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In order to overcome the shortcomings of traditional fingerprint identification methods, such as low computational efficiency and high false classification rate, a new multi-information fingerprint identification method based on interactive genetic algorithm is proposed. Firstly, the multi-information fingerprint image is pre-processed to extract the feature points. Then, combined with the interactive genetic algorithm, the rotation angle of the two fingerprint images is determined. At the same time, the fingerprint offset code is coded, and the matching setting function is set. The matching degree of the two fingerprints is determined by the interactive genetic algorithm, which effectively realises the multi-information fingerprint identification. Finally, the simulation experiment is carried out. The experimental results show that the proposed method can effectively reduce the false classification rate, reduce the average matching time of fingerprint image, and improve the operation efficiency. The minimum error rate is only 1.02%.
In the process of landscape design, the method can effectively establish the output data in the noise and make a comprehensive judgment on the effect of noise on the environment, so it is said that the tax payment alg...
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Traceability allows engineers to trace and monitor the relationships between software artifacts. Monitoring these relationships is vital to many software engineering activities such as software understanding and reuse...
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Traceability allows engineers to trace and monitor the relationships between software artifacts. Monitoring these relationships is vital to many software engineering activities such as software understanding and reuse. Grasping these relationships is studied in the framework of Requirement Traceability Recovery (RTR). RTR is vital to software reuse as it allows the identification and comparison of requirements of new and existing systems, and hence the reuse of software system components. Due to the difficulties in recovering the traceability links manually, only few software development processes take the monitoring of these relationships fully into account. Many attempts to automate the RTR task that enjoyed some success are based on methods from the field of information retrieval. However, these methods only concentrate on calculating the textual similarity between various software artifacts and do not take into account other properties of the artifacts. In this paper, we propose a search-based RTR approach using geneticalgorithms, that relies not only on semantic similarity between software artifacts, but also takes into account the history of reuse of the artifacts, and incorporates knowledge into RTR in the form of user (designer/developer) feedback. Experimental results show that the approach is promising.
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