Complex & Intelligent Systems最新文献

Fractals in $$S_b$$ -metric spaces S_b$$$度量空间中的分形

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2025-04-03 DOI: 10.1007/s40747-025-01849-1

Fahim Ud Din, Sheeza Nawaz, Adil Jhangeer, Fairouz Tchier

{"title":"Fractals in $$S_b$$ -metric spaces","authors":"Fahim Ud Din, Sheeza Nawaz, Adil Jhangeer, Fairouz Tchier","doi":"10.1007/s40747-025-01849-1","DOIUrl":"https://doi.org/10.1007/s40747-025-01849-1","url":null,"abstract":"This study aims to discover attractors for fractals by using generalized F-contractive iterated function system, which falls within a distinct category of mappings defined on (S_b)-metric spaces. In particular, we investigate how these systems, when subjected to specific F-contractive conditions, can lead to the identification of a unique attractor. We achieve a diverse range of outcomes for iterated function systems that adhere to a unique set of generalized F-contractive conditions. Our approach includes a detailed theoretical framework that establishes the existence and uniqueness of attractors in these settings. We provide illustrative examples to bolster the findings established in this work and use the functions given in the example to construct fractals and discuss the convergence of the obtained fractals via iterated function system to an attractor. These examples demonstrate the practical application of our theoretical results, showcasing the convergence behavior of fractals generated by our proposed systems. These outcomes extend beyond the scope of various existing results found in the current body of literature. By expanding the applicability of F-contractive conditions, our findings contribute to the broader understanding of fractal geometry and its applications, offering new insights and potential directions for future research in this area.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"32 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A surrogate-assisted differential evolution algorithm with a dual-space-driven selection strategy for expensive optimization problems

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2025-04-02 DOI: 10.1007/s40747-025-01812-0

Hanqing Liu, Zhigang Ren, Chenlong He, Wenhao Du

{"title":"A surrogate-assisted differential evolution algorithm with a dual-space-driven selection strategy for expensive optimization problems","authors":"Hanqing Liu, Zhigang Ren, Chenlong He, Wenhao Du","doi":"10.1007/s40747-025-01812-0","DOIUrl":"https://doi.org/10.1007/s40747-025-01812-0","url":null,"abstract":"Surrogate-assisted evolutionary algorithms (SAEAs) have shown great potential to solve computationally expensive optimization problems (EOPs). Their two key components, i.e., the optimizer and the surrogate model, both need to select solutions to promote further evolution and to update the model, respectively. However, the corresponding selection strategies are designed independently and mainly consider the predicted fitness of candidate solutions. Consequently, they can hardly complement each other well and are much likely to mislead the population evolution since the surrogate model necessarily has some prediction errors. Directing against this issue, this study proposes a unified dual-space-driven selection (DSDS) strategy and develops a new SAEA by taking differential evolution and radial basis function as the optimizer and the surrogate model, respectively. Besides the predicted fitness in objective space of candidate solutions, DSDS also considers their distribution in decision space by measuring how close they are to the geometric centers of their respective neighborhoods with a new indicator called neighborhood centrality (NC). It tries to select the solutions with good fitness and small NC values under a multi-objective sample selection framework and thus helps the resulting SAEA steadily search in multiple neighborhoods of excellent solutions. The performance of the new SAEA was extensively tested on six commonly used benchmark functions with five different dimensions from 20 to 200 as well as two typical real-word traffic signal optimization cases. Experimental results demonstrate that it possesses more competitive performance and stronger robustness than state-of-the-art SAEAs.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"52 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143758697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cooperative path planning optimization for ship-drone delivery in maritime supply operations

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2025-04-02 DOI: 10.1007/s40747-025-01837-5

Xiang Li, Hongguang Zhang

{"title":"Cooperative path planning optimization for ship-drone delivery in maritime supply operations","authors":"Xiang Li, Hongguang Zhang","doi":"10.1007/s40747-025-01837-5","DOIUrl":"https://doi.org/10.1007/s40747-025-01837-5","url":null,"abstract":"Drone-assisted ship supply has recently garnered widespread attention for its faster, cheaper, and greener advantages, reshaping shore-to-vessel deliveries and expected to become fundamental to future maritime logistics. Facing challenges like time-dependent locations and coordination, we introduce a novel path planning problem for supply ship-drone delivery, in which drones launch from the supply ship to serve anchored and underway vessels. We then formulate a supply ship-drone delivery model and devise a synchronized drone rendezvous strategy that determines the rendezvous points between drones and underway vessels. To address this, we propose an adaptive ship-drone path coordination algorithm (ASDPC) that accounts for the movement of both the supply ship and vessels. The supply ship path is optimized using a grid-based approach, ensuring full vessel coverage with tailored operators and enhancing search diversity and intensity. Building upon this, drone path optimization employs the receding vessel priority delivery strategy, leveraging relative motion between the supply ship and vessels to select targets with low delays and short distances. Subsequently, a removal-and-insertion approach is applied to further coordinate multi-drone paths. Besides, with supply ship and drone parameters varying, ASDPC consistently outperforms the baseline algorithms in terms of reducing delivery cost and time, indicating the satisfactory performance and practicability of ASDPC across various scenarios. Generally, this work presents a scalable framework for drone collaboration with mobile platforms to address critical challenges in coordination and synchronization with moving targets, thereby offering new perspectives for maritime logistics operations.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"58 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143758241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reducing hallucinations of large language models via hierarchical semantic piece

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2025-04-02 DOI: 10.1007/s40747-025-01833-9

Yanyi Liu, Qingwen Yang, Jiawei Tang, Tiezheng Guo, Chen Wang, Pan Li, Sai Xu, Xianlin Gao, Zhi Li, Jun Liu, Yingyou Wen

{"title":"Reducing hallucinations of large language models via hierarchical semantic piece","authors":"Yanyi Liu, Qingwen Yang, Jiawei Tang, Tiezheng Guo, Chen Wang, Pan Li, Sai Xu, Xianlin Gao, Zhi Li, Jun Liu, Yingyou Wen","doi":"10.1007/s40747-025-01833-9","DOIUrl":"https://doi.org/10.1007/s40747-025-01833-9","url":null,"abstract":"With the widespread application of large language models (LLMs) in natural language processing (NLP), hallucinations have become a significant impediment to their effective use of LLMs in industry applications. To address this challenge, we integrate existing hallucination detection and mitigation methods into a unified hallucination detection and mitigation framework. The framework consists of four main components: output parser, reference parser, fact verifier, and mitigator. These components collectively consolidate various hallucination detection and mitigation methods. Within this unified framework, we introduce the hierarchical semantic piece (HSP) for hallucination detection and mitigation. The HSP method extracts multi-granularity semantic pieces from both the reference material and the generated text. Sentence-level semantic pieces encapsulate global semantic information, while entity-level semantic pieces handle local semantic information. This method verifies the consistency between the generated text and the reference text at corresponding granularities, thereby enhancing the effectiveness of hallucination detection and mitigation. Experimental results show that the HSP method is very effective in detecting and mitigating hallucinations and shows lower computational resource consumption. Our method has great potential and promises for industry applications that rely on professionalism and reliability.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"133 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143758607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Knowledge graph-based entity alignment with unified representation for auditing

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2025-03-28 DOI: 10.1007/s40747-025-01843-7

Youhua Zhou, Xueming Yan, Han Huang, Zhifeng Hao, Haofeng Zhu, Fangqing Liu

{"title":"Knowledge graph-based entity alignment with unified representation for auditing","authors":"Youhua Zhou, Xueming Yan, Han Huang, Zhifeng Hao, Haofeng Zhu, Fangqing Liu","doi":"10.1007/s40747-025-01843-7","DOIUrl":"https://doi.org/10.1007/s40747-025-01843-7","url":null,"abstract":"Auditing is facilitated by audit knowledge graphs, while the biggest challenge in constructing an audit knowledge graph is entity alignment. Entity alignment involves linking entity pairs with the same real-world identity and aims to integrate heterogeneous knowledge across different knowledge graphs. However, most existing works do not effectively combine both attribute and relation representations into a unified framework for entity alignment, which is essential to link entities within an audit knowledge graph accurately. In this study, we propose a knowledge graph-based entity alignment approach with multi-attribute and weighted-relation fusion (KG-Marfia) for intelligent auditing. Our proposed KG-Marfia first extracts entity representations by addressing the imbalance of attributes and relations, and then designs a stacked graph convolutional network as an encoder to fuse attribute and relation information, learning unified representations for entities. In particular, we adopt an SVM-based classifier for the alignment task in intelligent auditing. Experiments conducted on two public datasets, as well as three audit datasets, demonstrate that our KG-Marfia outperforms state-of-the-art entity alignment methods.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"183 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143723538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A study of enhanced visual perception of marine biology images based on diffusion-GAN

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2025-03-25 DOI: 10.1007/s40747-025-01832-w

Feifan Yao, Huiying Zhang, Yifei Gong, Qinghua Zhang, Pan Xiao

{"title":"A study of enhanced visual perception of marine biology images based on diffusion-GAN","authors":"Feifan Yao, Huiying Zhang, Yifei Gong, Qinghua Zhang, Pan Xiao","doi":"10.1007/s40747-025-01832-w","DOIUrl":"https://doi.org/10.1007/s40747-025-01832-w","url":null,"abstract":"Aiming at the influence of factors such as the special optical characteristics of water bodies on the perceptual quality of generated images, this paper proposes the DifSG2-CCL model for reducing the special optical characteristics of water bodies and the DPL-SG2 model for introducing perceptual loss. Combining the ideas of cyclic consistency and style migration, this paper builds the Underwater Cycle Consistency Loss (U-CCL) module. The DifSG2-CCL model is based on the method of image reconstruction, which converts the underwater image into the style of the land image to reduce the influence of the water body factors. VGG16 is introduced as a perceptual loss into the DPL-SG2 to enhance the visual perception of the image by feature extraction with different layers and tonal weighting. Furthermore, in addition to the already disclosed SA dataset, a T dataset with a resolution of 256 × 256 in 9.366k sheets is provided in this paper. The experimental results show that DifSG2-CCL and DPL-SG2 can effectively enhance the perceptual quality of the images. The unique underwater image generation of DifSG2-CCL produces excellent results in qualitative analysis and reduces its FID value to 8.97. DPL-SG2 is more outstanding in the training of T dataset, and its FID value is reduced to 5.39. Therefore, the U-CCL and VGG16 can be applied as an innovative approach to enhance visual perception of underwater images. The experimental code with pre-trained models will be published shortly at https://github.com/yff0428/DPL-SG2/tree/main.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"71 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143695315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A parallel large-scale multiobjective evolutionary algorithm based on two-space decomposition

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2025-03-25 DOI: 10.1007/s40747-025-01835-7

Feng Yin, Bin Cao

{"title":"A parallel large-scale multiobjective evolutionary algorithm based on two-space decomposition","authors":"Feng Yin, Bin Cao","doi":"10.1007/s40747-025-01835-7","DOIUrl":"https://doi.org/10.1007/s40747-025-01835-7","url":null,"abstract":"Decomposition is an effective and popular strategy used by evolutionary algorithms to solve multiobjective optimization problems (MOPs). It can reduce the difficulty of directly solving MOPs, increase the diversity of the obtained solutions, and facilitate parallel computing. However, with the increase of the number of decision variables, the performance of multiobjective evolutionary algorithms (MOEAs) often deteriorates sharply. The advantages of the decomposition strategy are not fully exploited when solving such large-scale MOPs (LSMOPs). To this end, this paper proposes a parallel MOEA based on two-space decomposition (TSD) to solve LSMOPs. The main idea of the algorithm is to decompose the objective space and decision space into multiple subspaces, each of which is expected to contain some complete Pareto-optimal solutions, and then use multiple populations to conduct parallel searches in these subspaces. Specifically, the objective space decomposition approach adopts the traditional reference vector-based method, whereas the decision space decomposition approach adopts the proposed method based on a diversity design subspace (DDS). The algorithm uses a message passing interface (MPI) to implement its parallel environment. The experimental results demonstrate the effectiveness of the proposed DDS-based method. Compared with the state-of-the-art MOEAs in solving various benchmark and real-world problems, the proposed algorithm exhibits advantages in terms of general performance and computational efficiency.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"41 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143695310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on knowledge tracing based on learner fatigue state

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2025-03-24 DOI: 10.1007/s40747-025-01831-x

Haoyu Wang, Qianxi Wu, Chengke Bao, Weidong Ji, Guohui Zhou

{"title":"Research on knowledge tracing based on learner fatigue state","authors":"Haoyu Wang, Qianxi Wu, Chengke Bao, Weidong Ji, Guohui Zhou","doi":"10.1007/s40747-025-01831-x","DOIUrl":"https://doi.org/10.1007/s40747-025-01831-x","url":null,"abstract":"Knowledge tracing aims to predict how learners will perform in future exercises on related concepts and to track changes in their knowledge state. Existing models have not fully considered the physical and mental fatigue that occurs in learners during prolonged learning tasks, which leads to reduced problem-solving ability and affects their learning efficiency and performance. This article proposes Attention-Centric Knowledge Tracing to address the above issues. This method combines the Grit theory to evaluate the learner’s fatigue state and explores the potential impact of learning tasks on the learner’s fatigue state through deep graph convolutional networks. In particular, this article employs a multilayer perceptual network with scaled dot-product attention to process information dynamically, focusing on the critical information the learner needs at a given moment and effectively incorporating it into the knowledge framework. This article compared the fourteen knowledge tracing models in the experiment to the two benchmark data sets. The results indicate that knowledge tracing in the center of attention outperforms the baseline model in predicting learners’ future responses.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"94 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An exploration-enhanced hybrid algorithm based on regularity evolution for multi-objective multi-UAV 3-D path planning

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2025-03-24 DOI: 10.1007/s40747-025-01846-4

Zhenzu Bai, Haiyin Zhou, Juhui Wei, Xuanying Zhou, Yida Ning, Jiongqi Wang

{"title":"An exploration-enhanced hybrid algorithm based on regularity evolution for multi-objective multi-UAV 3-D path planning","authors":"Zhenzu Bai, Haiyin Zhou, Juhui Wei, Xuanying Zhou, Yida Ning, Jiongqi Wang","doi":"10.1007/s40747-025-01846-4","DOIUrl":"https://doi.org/10.1007/s40747-025-01846-4","url":null,"abstract":"Path planning poses a complex optimization challenge essential for the safe operation and successful mission execution of unmanned aerial vehicles (UAVs). Developing objectives, constraints, and decision-making processes for three-dimensional path planning involving multiple UAVs presents substantial challenges within the multi-objective optimization community. Traditional modeling approaches primarily aim to minimize path length and collision risks, often overlooking the need for a quantitative assessment of communication quality among UAVs. This neglect causes an inadequate representation of their true cooperative capabilities. In addition, there is difficulty in achieving an optimal balance between convergence, diversity, and feasibility. Therefore, this study introduces a bi-objective, three-dimensional path planning model specifically designed for UAVs. This model features an objective function that quantitatively evaluates inter-UAV communication quality throughout their flights. To solve this problem, this study proposes the dual-population regularity evolution algorithm (DPREA), which incorporates an auto-switching regularity evolutionary reproduction operator known as autoRE. It conducts extensive experiments across six testing suites and three path-planning simulation cases to validate the effectiveness of DPREA. The simulation results showed that its performance in addressing constrained multi-objective problems is significantly superior or at least comparable to that of state-of-the-art algorithms in most instances.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"9 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The opinion dynamics model for group decision making with probabilistic uncertain linguistic information

IF 5.8 2区计算机科学

Complex & Intelligent Systems Pub Date : 2025-03-22 DOI: 10.1007/s40747-025-01844-6

Jianping Fan, Zhuxuan Jin, Meiqin Wu

{"title":"The opinion dynamics model for group decision making with probabilistic uncertain linguistic information","authors":"Jianping Fan, Zhuxuan Jin, Meiqin Wu","doi":"10.1007/s40747-025-01844-6","DOIUrl":"https://doi.org/10.1007/s40747-025-01844-6","url":null,"abstract":"Multi-criteria group decision making (MCGDM) is the important part in decision-making process, which has been used in many industries. Coordinating differing opinions and ultimately reaching group consensus in a group decision-making process has become an important area of research. This paper uses probabilistic uncertain linguistic term sets (PULTSs) to express the uncertainty of evaluation information, and proposes a group consensus reaching method based on the opinion dynamics model which exhaustively considers how decision-makers’ (DMs) viewpoints can influence each other and evolve over time in MCGDM environments. First, we gathers the group’s preference information regarding the alternatives and their stubbornness to peer influence. Next, an influence matrix is determined based on the authority index of the DMs, and a probabilistic uncertain linguistic Friedkin–Johnsen model (PUL-FJ) is constructed. Then, a group consensus reaching method based on the PUL-Friedkin-Johnsen model is proposed to address the feedback mechanism in the consensus-reaching process (CRP). Finally, we proposes a novel approach for ranking. To better achieve group decision-making, we constructs an improved PUL similarity measure that based on the Wasserstein distance. Additionally, this paper proposes a new approach for expert weight, resulting in a comprehensive expert weight that balances individual expertise of the different criteria and group consensus. In the end, an example is provided, and the method’s feasibility is validated through sensitivity analysis and comparative analysis.","PeriodicalId":10524,"journal":{"name":"Complex & Intelligent Systems","volume":"24 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0