Complexity最新文献

{"title":"Experimental Validation of a Hybrid BS–RBF–HONTSM Control Strategy for High-Performance Induction Motor Drives","authors":"Ngoc Thuy Pham","doi":"10.1155/cplx/7396198","DOIUrl":"https://doi.org/10.1155/cplx/7396198","url":null,"abstract":"<p>This paper proposes a hybrid control strategy for high-performance induction motor (IM) drives under field-oriented control (FOC), combining a backstepping–RBF-based speed controller enhanced by a higher-order nonsingular terminal sliding mode (HONTSM) mechanism with a HONTSM-based current controller. The proposed speed loop adopts a multilayer structure in which the Lyapunov-based backstepping formulation provides the fundamental nonlinear stability framework, while the RBF network and HONTSM compensator enhance adaptability and robustness. Specifically, the RBF network approximates unknown dynamics in real time, whereas the HONTSM component ensures fast finite-time convergence and strong disturbance attenuation. This synergistic design maintains the structural transparency of backstepping while leveraging the learning capability of RBF and the robustness of sliding mode control. To further improve control performance, an enhanced Harris Hawks optimization algorithm with chaotic Lévy flights (EHHO–CLF) is employed as an offline optimization tool to determine the optimal parameters of the hybrid controller prior to real-time implementation, enabling improved global search efficiency and enhanced transient response. In the inner loop, the HONTSM controller enforces finite-time current tracking with reduced chattering and strong robustness against inverter nonlinearities and parameter uncertainties. Stability of the overall system is rigorously established via Lyapunov-based analysis, ensuring uniform ultimate boundedness of the speed loop and finite-time convergence of the current loop. The effectiveness of the proposed strategy is validated through MATLAB/Simulink simulations and real-time DSP-based experimental implementation, confirming robust high-performance operation under practical nonidealities and demonstrating its applicability to industrial motor drive systems, thereby providing an effective and practical solution for next-generation intelligent IM drives.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/7396198","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148386526","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":"MAEA-CD: A Novel Multiagent-Based Evolutionary Algorithm for Community Structure Detection in Social Networks","authors":"Parisa Allahverdizadeh,&nbsp;Saeid Taghavi Afshord,&nbsp;Bagher Zarei,&nbsp;Vahid Majidnezhad","doi":"10.1155/cplx/4557420","DOIUrl":"https://doi.org/10.1155/cplx/4557420","url":null,"abstract":"<p>Due to the substantial growth in user numbers and the rapid generation and dissemination of information on social networks, the study and analysis of these networks have become increasingly important. One of the critical problems that social network analysts focus on is the identification of communities/subgroups that may exist within these networks. Identifying these groups has numerous applications in marketing, advertising, and search engine optimization. This paper proposes a method named MAEA-CD, which combines distributed evolutionary algorithms with multiagent systems for the purpose of identifying communities in social networks. The main advantages of MAEA-CD lie in the simultaneous utilization of the capabilities of evolutionary algorithms—exploration and exploitation—and the features of multiagent systems—competition and cooperation, autonomy, and learning. This combination enables MAEA-CD to significantly alleviate the issues of premature convergence and entrapment in local optima that are prevalent in most conventional evolutionary algorithms. Experimental results across diverse community detection instances show that MAEA-CD is efficient in identifying social network communities. Its performance, on average, is 16.63% better on real-world benchmark networks, 25.30% better on GN synthetic benchmark networks, and 30.89% better on LFR synthetic benchmark networks compared to the mean performance of all baseline algorithms, averaged across all networks. To demonstrate broader engineering relevance beyond social networks, we present a case study on the U.S. Western States Power Grid. MAEA-CD uncovers operationally coherent partitions aligned with design and resilience objectives (e.g., controlled islanding and regional operation), illustrating its applicability to complex engineered infrastructure.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/4557420","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324958","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":"Influence Maximization in Complex Networks Using Deep Learning and Reinforcement Learning","authors":"Shiva Ahmadi Hormoghan,&nbsp;Bagher Zarei,&nbsp;Vahid Majidnezhad,&nbsp;Babak Anari","doi":"10.1155/cplx/4861287","DOIUrl":"https://doi.org/10.1155/cplx/4861287","url":null,"abstract":"<p>Complex networks are made up of many components or nodes that interact with each other. These networks have recently been widely used and are popular platforms for product promotion and information diffusion. The interests and behavior of individuals in a complex network are highly influenced by each other. Finding individuals in complex networks as seed nodes of the network propagation is one of their most important problems, which exert the most significant influence on the remaining nodes in the network. Individuals are influential publishers who, if selected as the seed set in a publication issue in the network, will have the most people who have information about that published entity. This issue is referred to as the influence maximization (IM) problem. In various areas, such as recommender systems, IM has a significant commercial value in complex networks. In this research, we introduce an approach that integrates a graph convolutional network (GCN) with proximal policy optimization (PPO) to select a subset of the most influential nodes in a network with the objective of maximizing influence spread. This integrated approach enhances the ability to accurately detect nodes with the highest potential impact. The findings indicate that the proposed approach not only outperforms alternatives but also provides enhanced computational efficiency. The model’s capabilities are evaluated in comparison with existing approaches. Empirical evaluations on real-world datasets further confirm that the proposed method achieves superior influence spread and enhanced performance in terms of runtime.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/4861287","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324957","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":"Designing Optimal Intervention Policies for Bacterial CNS Infection Dynamics With Encephalitic Progression: A Multicontrol Compartmental Model","authors":"M. S. Rahman,&nbsp;Rehena Nasrin,&nbsp;M. H. A. Biswas","doi":"10.1155/cplx/6356331","DOIUrl":"https://doi.org/10.1155/cplx/6356331","url":null,"abstract":"<p>Central nervous system infections resulting from invasive bacterial pathogens are associated with a significant neurological burden. The ability of organisms such as <i>Neisseria meningitidis</i> and <i>Streptococcus pneumoniae</i> to invade the blood–brain barrier is often associated with severe neurological outcomes, including encephalitic complications. The progression from bacterial CNS infection to encephalitic states remains insufficiently explored in mathematical epidemiology, particularly in the presence of latent infection, asymptomatic carriage, and waning immunity. We develop a deterministic compartmental model of bacterial CNS infection, with the potential for progression to encephalitic states. The population structure consists of susceptible, exposed, transitional, asymptomatic infectious, symptomatic infectious, and recovered groups and includes a mechanism to represent declining immunity over time. Through this formulation, both the latent phase of infection and the subsequent disease progression can be effectively represented. The next-generation matrix method is used to evaluate <i>R</i>₀, while the global stability of the disease-free equilibrium is analyzed via a Lyapunov approach with LaSalle’s invariance principle. To determine the dominant factors in disease transmission, a sensitivity analysis is also undertaken. An optimal control framework incorporating treatment, vaccination, and isolation is also formulated. Numerical simulations demonstrate that optimal strategies significantly reduce infection prevalence and limit progression toward encephalitic states. Overall, this modeling approach offers a useful way to examine the dynamics of bacterial infections in the central nervous system and to explore potential strategies for their control.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/6356331","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324205","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":"Weighted Group Consensus of Heterogeneous MASs Without Spanning Trees: A Complex Frequency-Domain Approach Under Time Delays and Packet Loss","authors":"Xia Sun,&nbsp;Xingcheng Pu","doi":"10.1155/cplx/9270728","DOIUrl":"https://doi.org/10.1155/cplx/9270728","url":null,"abstract":"<p>This study examines the weighted group consensus problem in discrete-time HMASs with cooperative–competitive networks under the influence of packet loss and time delays. A novel control protocol has been devised for this system, taking into account packet loss, cooperative–competitive relations, and time delays. By using graph theory, stability theory, Z-transformation, Nyquist criterion, and Gershgorin disk, some sufficient conditions have been established to guarantee the weighted group consensus of this type of HMASs. Based on these gained results and accounting for the weighted parameters, the upper bound of time delay can be calculated. Furthermore, the topology of HMASs is no longer needed to be strongly connective or contain a spanning tree. Finally, simulation experiments are carried out to illustrate the validity of the results that have been obtained.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/9270728","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148282420","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":"Cybernetics in the Anthropocene’s Wake: Reframing Global Transformations Through the Emergent Human–Earth System","authors":"Matthew Walls,&nbsp;Petr Pokorný","doi":"10.1155/cplx/7539869","DOIUrl":"https://doi.org/10.1155/cplx/7539869","url":null,"abstract":"<p>The Anthropocene has been a powerful conceptual lens for exploring the coupling of humans and the Earth system. While fostering a rich transdisciplinary discourse, its grounding in bounded geological time and emphasis on disruption has often reinforced the nature–culture divide and tended toward a dystopian outlook. This paper proposes that more optimistic reformulations can follow a shift from “epochal thinking” to systemic emergence. Drawing on archaeology, paleoecology, and complex adaptive systems, we argue that global challenges are symptoms of underlying historical dynamics within what we describe as runaway and creative human–environment systems, interrelated forms defined by feedback, adaptation, and co-evolution. We propose a cybernetic reframing of Anthropocene debates that shifts attention to systemic transformation, emphasizing changes in feedback architectures, distributed cognition, and ecological memory across human–environment systems. A deep time case study of Central European forests illustrates how coupled human–environment systems cross thresholds of vulnerability when governance fails to engage with distributed feedback and ecological memory embedded in soils, species assemblages, and historical practices. The case demonstrates how adaptive capacity and learning emerge cybernetically across human and nonhuman components, offering a framework for navigating global challenges.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/7539869","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148282009","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 Multiobjective, Stable, and Fair Feature Selection and Ensemble Learning Framework for Explainable Student Academic Performance Prediction","authors":"M. A. Elsabagh,&nbsp;Menna M. S. Elmasry,&nbsp;Mona G. Gafar","doi":"10.1155/cplx/6614441","DOIUrl":"https://doi.org/10.1155/cplx/6614441","url":null,"abstract":"<p>Early intervention and data-driven educational decision-making depend on accurate student academic performance prediction; unfortunately, current methods frequently have high dimensionality, poor interpretability, and inadequate resilience. To obtain precise, understandable, stable, and equitable academic performance prediction, this study suggests an improved framework that combines a multiobjective Rüppell’s fox optimizer (RFO) with a gradient boosting classifier (GBC). An explicit trade-off between predicted accuracy and interpretability is made possible by the formulation of the feature selection issue as a multiobjective optimization assignment that simultaneously minimizes classification error and feature subset size. The proposed RFO-based method maintains good predictive performance while reducing the feature space to informative features, dependent on the chosen trade-off parameter, using the students’ academic performance dataset. The most effective RFO–GBC design outperforms traditional classifiers with an overall classification accuracy of 91.46% and a weighted F1-score of 91.30%. The efficacy of the proposed multiobjective formulation is demonstrated by a Pareto analysis, which shows that competitive accuracy (90.87%) can be achieved using a reduced feature subset. A stability analysis verifies the resilience of feature selection by several separate runs. The most significant predictors are completed credits and prior academic accomplishment, according to SHAP-based explainability, which further improves the interpretability of the model. Furthermore, little predictive bias across sensitive attributes is indicated by a fairness evaluation based on equal opportunity and demographic parity, which supports ethical deployment in educational situations. Overall, the proposed framework offers a robust, interpretable, and fairness-aware solution for student academic performance prediction, contributing to trustworthy educational data mining.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/6614441","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148238203","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: Green Internet of Things and Big Data Application in Smart Cities Development","authors":"Complexity","doi":"10.1155/cplx/9790538","DOIUrl":"https://doi.org/10.1155/cplx/9790538","url":null,"abstract":"<p>RETRACTION: Z. Yang, L. Jianjun, H. Faqiri, et al., “Green Internet of Things and Big Data Application in Smart Cities Development,” <i>Complexity</i>, 20214922697, 15 pages, 2021, https://doi.org/10.1155/2021/4922697.</p><p>The above article, published online on 28 May 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 did not respond to indicate their agreement to the retraction.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/9790538","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173802","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 Unified Framework Linking Entropy, Fractal Dimension, and Lyapunov Exponents in Chaotic Dynamics","authors":"Elio Quiroga Rodríguez","doi":"10.1155/cplx/4073826","DOIUrl":"https://doi.org/10.1155/cplx/4073826","url":null,"abstract":"<p>This study presents a universal operator framework predicting critical transitions in nonlinear systems through the intrinsic nexus of entropy, fractal geometry, and chaos. We derive a unified model (Equation 4) that integrates fractal dimension (Dᵓ), Lyapunov exponents (λᵢ), and entropy (S) into a single predictive equation, justified through connections to the Kolmogorov–Sinai entropy theorem and the Kaplan–Yorke dimension conjecture. Validated via simulation of the logistic map across the full bifurcation cascade and cross-validated against the Hénon map, the model captures exponential entropy decay at bifurcation points and geometric-dynamic coupling across chaotic regimes. Statistical analysis confirms a highly significant linear relationship between Shannon entropy and correlation dimension (Pearson <i>r</i> = 0.971, <i>p</i> &lt; 10⁻¹²⁴; Spearman <i>ρ</i> = 0.972, <i>p</i> &lt; 10⁻¹²⁴). The framework identifies critical transitions with 89% accuracy in logistic map simulations, establishing entropy-fractal correlations as fundamental early-warning signals for tipping points in complex systems.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/4073826","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148166926","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":"International Domino Effect of Liquidity Risk From South Africa Across the SSA Region","authors":"Frederick Nsiah,&nbsp;Anokye M. Adam,&nbsp;Emmanuel N. Gyamfi,&nbsp;Mohammed Z. Isshaq","doi":"10.1155/cplx/2918330","DOIUrl":"https://doi.org/10.1155/cplx/2918330","url":null,"abstract":"<p>The study investigated the adverse liquidity risk spillovers from South Africa to the rest of the banking systems in the sub-Saharan Africa region. The study employed the GVAR macroeconometric framework and its associated generalised impulse response function (GIRF) to explore the interdependence and evolution of shocks to other countries in the SSA, given a negative standard deviation shock to South Africa’s liquidity. We used quarterly data from 31 countries spanning from 1996 to 2019. This includes the period of marked proliferation of cross-border banking in the region. The GIRFS provided the time profile for 31 countries. The time profiles of the GIRFS of each country’s banking system liquidity were analysed. Our results show that South Africa’s banking system liquidity has contemporaneous interdependence with several other banking systems in the SSA region. An adverse shock to South Africa’s banking system liquidity has a heterogeneous effect on several countries; the magnitude is generally moderate. While the shock triggers adverse spillover effects on the liquidity position of 19 banking systems, the liquidity level of 10 banking systems increases, and the liquidity of three banking systems remains resilient over time. The implication is that an extreme adverse liquidity shock could trigger a liquidity crisis in the majority of the banking systems in the SSA region. Hence, the negatively affected countries should minimise their banking system connectedness with the South African banking system and monitor an extreme liquidity shortage in South Africa.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2026-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/2918330","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148166927","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}