{"title":"Fractal control of Julia sets generated by discrete fractional competitive model","authors":"Manoj Kumar,Syed Abbas,Michal Niezabitowski,Marko Kostic","doi":"10.1142/s0218348x26501471","DOIUrl":"https://doi.org/10.1142/s0218348x26501471","url":null,"abstract":"This article explores the fractal behavior of a general non-linear discrete fractionalorder competitive model. In particular, we focus on a discrete fractional competitive model that illustrates the growth of two competing species influenced by toxic compounds. The analysis in this paper can be extended to other discrete fractional competitive models. To date, such models influenced by toxic compounds have not been studied from a fractal perspective, nor has the innovative control method been applied to the control of Julia sets in discrete models. Initially, we presented the discrete fractional competitive model utilizing the Gr¨unwald-Letnikov operator. Following that, we introduced the Julia set produced by a discrete fractional competitive model with the help of a modified escape-time algorithm suitable for the fractional order scenario. The fractal dynamic characteristics and the influence of memory parameters on the Julia set are illustrated through graphical exploration and fractal dimension analysis. Controlling Julia sets of the discrete fractional map is achieved by stabilizing the equilibrium point. The stability of these equilibrium points and consequently, the Julia sets are controlled using two distinct control methods. As the control parameter values diminish in the gradient control method, the Julia set related to the controlled system begins to shrink. This effect is a result of the instability of the equilibrium point. We developed a control scheme that helps in the control of the Julia set. When the control parameter values increase within a specific range, the Julia set in the second new state control technique compresses both vertically and horizontally. Again, this is attributed to the instability of the equilibrium point. To synchronize the Julia sets of two similar systems with different system parameters, a new synchronous controller featuring an arbitrary constant has been developed. The effectiveness of this synchronous controller is evaluated using numerical simulations. Our methodologies and various theoretical studies are solidified with the help of numerical simulations. This analysis will also apply to analogous types of mathematical models with different dimensions.","PeriodicalId":501262,"journal":{"name":"Fractals","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148894805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
FractalsPub Date : 2026-08-31DOI: 10.1142/s0218348x26501410
Hamza Tabti,Abdelkader Benali,Ibrahim Alraddadi
{"title":"Triple Positive Solutions and Nonexistence Results for Mixed Fractional Differential Equations with p-Laplacian Operator","authors":"Hamza Tabti,Abdelkader Benali,Ibrahim Alraddadi","doi":"10.1142/s0218348x26501410","DOIUrl":"https://doi.org/10.1142/s0218348x26501410","url":null,"abstract":"In this paper, we investigate the existence of multiple positive solutions for a class of nonlinear fractional boundary value problems involving mixed fractional derivatives with a p-Laplacian operator. The analysis is carried out by combining Green’s function techniques with a generalized Avery-Henderson fixed point theorem in cones, which enables us to establish the existence of at least three positive solutions for the considered problem. Moreover, we derive eigenvalue-type conditions under which the associated problem admits no positive solutions. Finally, the theoretical results are illustrated and validated through several representative examples, clarifying the applicability of the obtained theoretical results.","PeriodicalId":501262,"journal":{"name":"Fractals","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148894746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
FractalsPub Date : 2026-08-31DOI: 10.1142/s0218348x26501483
Guang-Qing Feng,Chun-Hui He
{"title":"Non-Perturbative Analysis of Primary Resonance and Chaos in Fractal Mems Photoacoustic Transducers","authors":"Guang-Qing Feng,Chun-Hui He","doi":"10.1142/s0218348x26501483","DOIUrl":"https://doi.org/10.1142/s0218348x26501483","url":null,"abstract":"The present study proposes a cohesive analytical framework for the primary resonance and chaotic dynamics of fractal-structured MEMS photoacoustic transducers. The non-perturbative approach is extended to fractal MEMS systems, yielding closed-form equivalent linearisation that accurately captures amplitude-dependent behaviour with relative errors below 5%. The analysis demonstrates that fractal parameters significantly regulate dynamic stability. An increase in fractal dimension or a decrease in scale factor has been shown to enhance electrostatic softening, reduce effective nonlinearity, and lower the chaotic threshold through a period-doubling cascade. A fundamental trade-off is evident between sensitivity and stability. The fractal geometries that optimise photoacoustic performance are precisely those that compromise dynamic reliability. The establishment of a design criterion is imperative for ensuring stable operation within the hardening regime. The framework also offers pathways towards fractional-order damping and digital twin integration, providing both theoretical foundations and practical guidelines for robust fractal MEMS design.","PeriodicalId":501262,"journal":{"name":"Fractals","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148894787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
FractalsPub Date : 2026-08-31DOI: 10.1142/s0218348x26501501
Muhammad Farman,Muhammad Asad Ullah,Yuyang Cai,Yang Ling,Usama Ghafoor,Mustafa Bayram,Mohamed Hafez
{"title":"Assessing the Impact of Quarantine Behavior Among Individuals Infected with Mpox: A Fractional Artificial Neural Network Approach","authors":"Muhammad Farman,Muhammad Asad Ullah,Yuyang Cai,Yang Ling,Usama Ghafoor,Mustafa Bayram,Mohamed Hafez","doi":"10.1142/s0218348x26501501","DOIUrl":"https://doi.org/10.1142/s0218348x26501501","url":null,"abstract":"This study proposed a combination of compartmental modeling with a bio-inspired machine learning (ML) framework for the dynamical analysis of monkeypox (MPOX) transmission. A Caputo fractional-order model is developed based on human infection data from the USA to understand the long-term fluctuation in disease propagation and inherent memory effects. The transmission dynamics of MPOX incorporating vaccination, quarantine, recovery, loss of immunity, and both human to human and animal to human transmission pathways are considered. The fractional-order model is numerically solved using the Adams-Bashforth-Moulton (ABM) method to investigate the effects of fractional order on disease dynamics. Global sensitivity analysis based on Latin hypercube sampling and partial rank correlation coefficient (LHS-PRCC) analysis identifies the key parameters influencing the human reproduction number (R2). To provide an efficient surrogate for the numerical solutions, an artificial neural network (ANN) based on the Levenberg-Marquardt backpropagation (LMB) algorithm is developed. The dataset obtained through ABM is used to reduce the mean square error (MSE) with the statistics of 70% as training and 15% for both testing and validation. The results indicate that human to human transmission is a major driver of the epidemic, whereas timely quarantine and vaccination substantially reduce transmission. The fractional-order formulation further shows that decreasing the fractional order slows epidemic progression and delays the infection peak, highlighting the influence of memory effects on disease dynamics. The proposed fractional-order and neural network framework provides an efficient and reliable approach for eradicating the infectious diseases transmission within the population and for assessing the effectiveness of key intervention strategies.","PeriodicalId":501262,"journal":{"name":"Fractals","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148894786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Generalized\u0000 p\u0000 -Convex Inequalities on Fractal Sets with Neural Network Modeling","authors":"Saad Ihsan Butt,Muhammad Mehtab,Mohammed Alammar,Youngsoo Seol","doi":"10.1142/s0218348x26501409","DOIUrl":"https://doi.org/10.1142/s0218348x26501409","url":null,"abstract":"In this article, we developed a new variant of discrete Jensen-type inequality for p-convex functions over fractal sets. Improvement and generalization of some Jensen-Mercer-type estimates for [Formula: see text]-convex function in the framework of fractal fractional calculus are obtained. Using this Jensen-Mercer inequality, we establish a Hermite-Hadamard-Mercer (HHM) type inequalities for [Formula: see text]-convex functions in fractal dimensions. We drive a new integral identity and HHM type inequalities for differentiable [Formula: see text]-convex functions. Some of the results presented here for [Formula: see text]-convex functions are extensions of earlier results for harmonically convex and convex functions. Finally, we also provide a neural network-based numerical analysis of the obtained results, showing the accuracy and effectiveness of the proposed inequalities for [Formula: see text]-convex functions.","PeriodicalId":501262,"journal":{"name":"Fractals","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148894792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}