Complexity最新文献

{"title":"Complex Network Built From Stock Price Returns and Volumes to Predict Market Volatility and Volume","authors":"N-K-K. Nguyen,&nbsp;H-T. Dinh,&nbsp;Q. Nguyen","doi":"10.1155/cplx/5670093","DOIUrl":"https://doi.org/10.1155/cplx/5670093","url":null,"abstract":"<p>This study investigates if network features from stock return and trading volume correlations can improve one-month-ahead forecasts of Vietnam’s VNIndex volatility and volume (2018–2024). We construct dynamic financial networks using Threshold, Top-k, and minimum spanning tree (MST) filtering methods, calculating metrics like density, centrality, and clustering.</p><p>Using these features in linear regression and random forest models, we find that threshold-based networks yield the strongest volatility predictions (<i>R</i>² ≈ 0.56). Volume forecasts achieve very high accuracy (<i>R</i>² ≈ 0.95), reflecting strong underlying correlations. Notably, surges in network density and centrality often precede periods of heightened market volatility.</p><p>Our findings demonstrate that incorporating complex network measures derived from mixed return-volume correlations can meaningfully enhance market forecasts in an emerging market context.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/5670093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"(Non-) Human Coordination Dynamics: Scaling Transformative Processes Through Indigenous Knowledge Systems","authors":"T. Yunkaporta,&nbsp;J. Manning Bancroft,&nbsp;S. Beck,&nbsp;P. Punjabi Jagdish","doi":"10.1155/cplx/5554866","DOIUrl":"https://doi.org/10.1155/cplx/5554866","url":null,"abstract":"<p>This paper describes the theory, method and customary knowledge behind the design of a global systems change network grounded in Indigenous relational processes. The project leverages nested cohorts of human and nonhuman agents, affiliated through ancient borderwork protocols within biocultural governance structures. In our Australasian cultures, the coordination dynamics of traditional foraging groups scales outward as a holarchy of interdependent relations, expanding decentralised social organisation principles from local to nonlocal sovereignties far afield. Using Indigenous ritual, Lore, land-care and kin-making processes as methods of inquiry, we advance a creolised version of this system in dialogue with academic research on team optimisation, the limits of scale, the cognitive limits of social relations, homophilic clustering and network effects. We argue that social imaginaries engineered through land-based cultural narratives have the potential to overcome network saturation points, maintaining coherence in distributed governance systems beyond local spheres of trust. We propose that traditional Indigenous embassy processes provide models of borderwork that might resolve issues of organisational complexity in emergent systems change movements.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/5554866","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Buildings as Species: Competition and Scaling Rules in Cities","authors":"Sara Najem,&nbsp;Tarek Tohme,&nbsp;Martin Grant","doi":"10.1155/cplx/7148875","DOIUrl":"https://doi.org/10.1155/cplx/7148875","url":null,"abstract":"<p>We look at buildings’ competition over space in cities following the distribution of the perimeters <i>r</i> of the buildings’ circumscribing ellipses. <i>p</i>(<i>r</i>) is shown to follow a power-law behavior beyond a critical threshold of the density of the built environment. In this regime, <i>p</i>(<i>d</i>), where <i>d</i> is the distance to the nearest competitor, defined to be a building with a larger <i>r</i>, bifurcates with the buildings’ number <i>n</i>. This reveals two different competition laws: one which is linked to spatial homogeneity and segregation, as opposed to another favoring spatial diversity and intermixing between buildings with different sizes.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/7148875","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of a TSK Rule-Based Model With Granular Rules and Ensemble Learning in Big Data","authors":"Mohammad Nematpour,&nbsp;Farnaz Mahan,&nbsp;Witold Pedrycz,&nbsp;Habib Izadkhah","doi":"10.1155/cplx/3937849","DOIUrl":"https://doi.org/10.1155/cplx/3937849","url":null,"abstract":"<p>Nowadays, the management and analysis of big data have become major challenges for researchers in the field of data mining. The increasing rate of data generation, along with the need to extract meaningful patterns, highlights the necessity of developing scalable big data analysis methods. In this context, fuzzy rule-based models have emerged as powerful tools for knowledge extraction from data. However, designing these models typically requires the monolithic use of the entire dataset, which is impractical for big data scenarios due to computational limitations. This study introduces a novel concept and proposes a new framework for designing and evaluating the performance of rule-based models in big data environments. Within this framework, a set of rule-based submodels are randomly constructed using sampled data and trained through Bagging. The rules extracted from these submodels are then aggregated using an optimization-based weighting strategy combined with an information entropy method. This approach, which has not yet been explored in the literature, contributes to improving model efficiency. In the experimental section, large-scale datasets with high dimensionality and volume are employed to comprehensively evaluate the performance of the proposed model. The results demonstrate that the proposed model achieves significant improvements over comparable models.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/3937849","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147579849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Hybrid Deep Learning Framework for Early Detection of Ovarian Cancer Using Ultrasound and MRI Images on a Secure Cloud Platform","authors":"Umesh Kumar Lilhore,&nbsp;Vanusha D.,&nbsp;Srilatha Gundapaneni,&nbsp;Anto Lourdu Xavier Raj Arockia Selvarathinam,&nbsp;Rasmi A.,&nbsp;Sarita Simaiya,&nbsp;Lidia Gosy Tekeste,&nbsp;Ehab Seif Ghith,&nbsp;Heba G. Mohamed","doi":"10.1155/cplx/9924424","DOIUrl":"https://doi.org/10.1155/cplx/9924424","url":null,"abstract":"<p>Ovarian cancer continues to pose a major diagnostic challenge, as early-stage disease often presents with subtle and heterogeneous imaging characteristics that limit the effectiveness of single-modality analysis. In response to this challenge, this study proposes a novel hybrid deep learning framework for the early detection and classification of ovarian cancer using ultrasound and MRI imaging, designed for deployment on a secure cloud-based platform. The proposed framework departs from conventional convolutional and attention-driven models by introducing a capsule-based representation learning strategy that explicitly encodes lesion morphology and spatial hierarchies, enabling robust characterization of small and irregular tumor structures. To capture global contextual relationships across imaging regions without reliance on self-attention mechanisms, the framework integrates an attention-free token-mixing architecture, facilitating efficient long-range interaction while maintaining scalability. In addition, a hypergraph-based relational learning module is employed to model higher-order spatial and radiomic relationships among multiple lesion regions simultaneously, providing lesion-centric reasoning that aligns with clinical diagnostic practices. This combination allows the model to effectively distinguish malignant patterns from benign anatomical variations. Beyond binary cancer detection, the framework supports hierarchical classification, separating benign and malignant cases and further categorizing malignant tumors into clinically meaningful subtypes. To enhance fine-grained discrimination, pathology-guided semantic alignment is incorporated using histopathological knowledge as auxiliary supervision, enabling cross-modal knowledge transfer without the need for paired imaging–pathology data. The framework is evaluated on multiple publicly available datasets covering ultrasound, MRI/CT, and histopathology modalities, demonstrating consistent performance across heterogeneous data sources. To ensure suitability for real-world clinical use, an advanced chaos-based image encryption and secure transmission module is integrated to protect sensitive medical data during cloud-based processing. Experimental results indicate that the proposed framework achieves superior detection and classification performance compared to existing approaches, particularly in early-stage ovarian cancer cases, underscoring its potential as an accurate, interpretable, and clinically deployable decision-support system.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/9924424","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147615410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RETRACTION: Using Big Data Fuzzy K-Means Clustering and Information Fusion Algorithm in English Teaching Ability Evaluation","authors":"Complexity","doi":"10.1155/cplx/9852140","DOIUrl":"https://doi.org/10.1155/cplx/9852140","url":null,"abstract":"<p>RETRACTION: C. Zhen, “Using Big Data Fuzzy K-Means Clustering and Information Fusion Algorithm in English Teaching Ability Evaluation,” <i>Complexity</i> 2021, no. 1 (2021): 1–9, https://doi.org/10.1155/2021/5554444.</p><p>The above article, published online on 8 February 2021 in Wiley Online Library (https://wileyonlinelibrary.com), has been retracted by John Wiley &amp; Sons Ltd.</p><p>The presence of these indicators undermines our confidence in the integrity of the article’s content, and we cannot, therefore, vouch for its reliability. Please note that this notice is intended solely to alert readers that the content of this article is unreliable. We have not investigated whether authors were aware of or involved in the systematic manipulation of the publication process.</p><p>The author was informed of the decision to retract but remained unresponsive.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/9852140","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147615174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RETRACTION: The Role of Artificial and Nonartificial Intelligence in the New Product Success with Moderating Role of New Product Innovation: A Case of Manufacturing Companies in China","authors":"Complexity","doi":"10.1155/cplx/9795686","DOIUrl":"https://doi.org/10.1155/cplx/9795686","url":null,"abstract":"<p>RETRACTION: H. Jianjun, Y. Yao, J. Hameed, et al., “The Role of Artificial and Nonartificial Intelligence in the New Product Success with Moderating Role of New Product Innovation: A Case of Manufacturing Companies in China,” <i>Complexity</i>, vol. 2021 (2021). https://doi.org/10.1155/2021/8891298.</p><p>The above article, published online on 22 January 2021 in Wiley Online Library (https://wileyonlinelibrary.com), has been retracted by John Wiley &amp; Sons Ltd.</p><p>The presence of these indicators undermines our confidence in the integrity of the article’s content, and we cannot, therefore, vouch for its reliability. Please note that this notice is intended solely to alert readers that the content of this article is unreliable. We have not investigated whether authors were aware of or involved in the systematic manipulation of the publication process.</p><p>The authors had been informed of this retraction but did not provide a response.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/9795686","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147615175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Centralized and Decentralized Event-Triggered Consensus Control for Leader–Follower Connected Vehicle Systems","authors":"Azmat Ullah Khan Niazi,&nbsp;Waqar Ul Hassan,&nbsp;Kinda Abuasbeh,&nbsp;Aseel Smerat,&nbsp;Naveed Iqbal","doi":"10.1155/cplx/3838599","DOIUrl":"https://doi.org/10.1155/cplx/3838599","url":null,"abstract":"<p>This paper investigates the consensus problem in leader–follower connected vehicle systems (CVSs) under deception attacks—including coordinated position, velocity, and acceleration attacks as well as delays and disturbances. Centralized and decentralized event-triggered control strategies are proposed, allowing follower actuators to update at nonuniform intervals while significantly reducing communication overhead. To further enhance resilience, a delayed controller is designed to mitigate the effects of disturbances. The decentralized strategy relies solely on locally available information, and a refined triggering function is developed that requires neither topology knowledge nor Laplacian eigenvalues, using only each follower’s own data and the most recent event instants of its neighbors. Consensus is guaranteed even when certain followers lack direct access to the leader. Lyapunov-based analysis establishes stability in the presence of measurement errors and adversarial deception attacks, and comprehensive simulations demonstrate the robustness and effectiveness of the proposed framework.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/3838599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolutionary Game of Multiple Subjects Collaborative Innovation Under Double Uncertainty","authors":"Xumei Yuan,&nbsp;Ming Zhang,&nbsp;Fuli Wei,&nbsp;Xu Zhang","doi":"10.1155/cplx/3743541","DOIUrl":"https://doi.org/10.1155/cplx/3743541","url":null,"abstract":"<p>Multisubject technology collaborative innovation serves as an essential driving force to improve technology transfer efficiency as well as implement the innovation-driven strategy. Particularly, collaborative innovation in accordance with technological orientation and market demand enables the efficient resource allocation that stimulates innovation willingness and improves innovation performance. This study explores the strategies and conditions for multiagent collaborative innovation under technological and market uncertainties, employing a government–enterprise–university evolutionary game model. Numerical simulations demonstrate that both technology and market factors are critical drivers of collaborative innovation systems, with market influences outweighing technological ones. Notably, technological universality proves more impactful than novelty. When technology and market drivers are weak, government willingness becomes the decisive factor in shaping other participants’ strategic choices. Punitive measures have a stronger effect on system evolution than government incentives. The study’s key contribution lies in emphasizing technological sophistication, technological universality, market price, participant willingness, and policy impacts. The findings underscore the dynamic interplay of technology, market, and government in collaborative innovation, offering novel theoretical and practical insights into its driving mechanisms and implementation pathways.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/3743541","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147566449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the Preservation of Input/Output Directed Graph Informativeness Under Crossover","authors":"Andreas Duus Pape,&nbsp;J. David Schaffer,&nbsp;Hiroki Sayama,&nbsp;Christoper Zosh","doi":"10.1155/cplx/9057003","DOIUrl":"https://doi.org/10.1155/cplx/9057003","url":null,"abstract":"<p>There exists a broad class of networks that connect inputs to outputs. These networks include chemical transformation networks, electrical circuits, municipal water systems, and neural networks. The goals of this paper are to provide a theoretical foundation for evolutionary crossover on this class of graphs and connect crossover to informativeness, a measure of the connectedness of inputs to outputs. Informativeness is defined as a partially informative graph has at least one path from an input to some output, a very informative graph has a path from every input to some output, and a fully informative graph has a path from every input to every output. A neural network with nonzero weights and any number of layers is fully informative. As links are removed (assigned zero weight), it may become very, partially, or not informative (the complement of informativeness is actionability, which is a measure of how connected outputs are from inputs). We define a crossover operation on Input/Output Directed Graphs (IOD Graphs) in which we find subgraphs with matching sets of forward and backward directed links to “swap.” With this operation, IOD Graphs can be subject to evolutionary computation methods. We show that fully informative parents may yield a noninformative child. We also show that under certain conditions, crossover compatible, partially informative parents yield partially informative children and very informative input parents with partially informative output parents yield very informative children. However, even under these conditions, full informativeness may not be retained. Similar results hold for actionability.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/9057003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147565853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}