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Mathematical Modelling of Dengue Transmission with Adaptive Fuzzy Backstepping Control and RK-5 Numerical Method

International Journal of Applied and Computational Mathematics 2025年第3期11卷 1-29页

作者： Vijayalakshmi, G.M. Ariyanatchi, M. Akgül, Ali Department of Mathematics Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Tamilnadu Avadi 600062 India Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Tamilnadu Chennai India Department of Mathematics Art and Science Faculty Siirt University Siirt 56100 Turkey Department of Computer Engineering Biruni University Istanbul Topkapı 34010 Turkey Department of Mathematics Mathematics Research Center Near East University Near East Boulevard Mersin 10 Nicosia 99138 Turkey

The aim of this research is to create an adaptive nonlinear fuzzy backstepping robust controller for a dengue disease outbreak model. We use an SIR-SI compartmental mathematical model to analyse the diffusion mechanism of dengue disease. A nonlinear adaptive controller regulates prevention strategies for susceptible human beings and enhances hospitalization-based treatment for the infected people. Besides, the spraying of chemical insecticides will reduce the infected mosquito population. Adaptation laws are used to derive fuzzy system parameters, enhancing the system's adaptability. Then we construct a suitable Lyapunov function, which guarantees convergence, robustness, and stability for a closed-loop system. Finally, we plot all the system's control variables graphically and calculate their numerical approximations using the Runge–Kutta technique of fifth order. These simulations demonstrate that the proposed adaptive controllers can effectively control the dengue disease and ensure the stability of the system. Hence, we conclude that adaptive backstepping control measures can protect more people from dengue infection. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2025.

关键词： Adaptive back stepping Dengue model Fuzzy system Lyapunov function Runge–Kutta method

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Design, Analysis and Fabrication of Dual Band Microstrip Patch Antenna for (L2) Band GPS and WiFi Applications

Design, Analysis and Fabrication of Dual Band Microstrip Pat...

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2022 International Conference for Advancement in technology, ICONAT 2022

作者： Oo, Wai Mar Tun, Hla Myo Nway, Tint May Pradhan, Devasis Sahu, Prasanna Kumar Naing, Zaw Min Yangon Technological University Department of Electronic Engineering Yangon Myanmar Yangon Technological University Faculty of Electrical and Computer Engineering Yangon Myanmar Acharya Institute of Technology Department of Electronics and Communication Engineering Bengaluru India National Institute of Technology Department of Electrical Engineering Odisha Rourkela India Ministry of Science and Technology Department of Research and Innovation Yangon Myanmar

ISBN: (纸本)9781665425773

Dual-frequency antennas are popular for many applications in communication systems. This work proposes a dual-band microstrip patch antenna design based on two-layer stacked patch for GPS and WiFi purposes. The targeted antenna is created to maneuver at the frequency range of 1.227GHz GPS L2 band (1.215GHz to 1.239GHz) and the 2.4GHz WiFi band frequency (2.4GHz to 2.48GHz). The antenna is fabricated on substrate of FR4 which dielectric constant 4.4 and the substrate material's height is 1.6mm. The created two-layer stacked patch antenna is compared with a conformist single patch antenna and analyzed the parameters of performance specifications for return loss (RL), bandwidth, VSWR, gain and pattern of radiation. It is recognized that the performance of the fabricated antenna improves when compared to the single-layer conventional antenna. © 2022 IEEE.

关键词： Global positioning system

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Energy Storage System with Dynamic Voltage Restorer Integrated for Wind Energy System 1

Energy Storage System with Dynamic Voltage Restorer Integrat...

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1st International Conference on Advances in Computational Science and engineering, ICACSE 2020

作者： Pattanaik, Balachandra Hussain, Syed Masood Karthikeyan, V. Giftson Samuel, G. Department of Electrical and Computer Engineering Faculty of Engineering and Technology Bule Hora University Bule Hora Ethiopia Department of Electrical and Computer Engineering Faculty of Engineering and Technology Bule Hora University Bule Hora Ethiopia Department of Electrical and Electronics Engineering AMET Deemed to Be University Chennai India Department of Electrical and Electronics Engineering Sir Issac Newton College of Engineering and Technology Nagapattinam India

The permanent magnet induction generator (PMSG) based wind system that integrates with dynamic voltage restorer (DVR) and the energy storage system (ESS) for backup power purpose is explained in this paper. The output power transmission of the wind energy generation is interfaced with the dynamic voltage restorer in series. The energy storage system and the dc-link capacitor are parallel to the PMSG based wind system. The proposed system is to control the fluctuations in wind power and compensate the disturbed grid voltages. The bidirectional converter controls the power flow in both directions as the power flow from the source to battery and battery to the voltage source inverter (VSI) compensates the grid voltage disturbances through the voltage injection performance and transformer. The DVR-based energy storage system results for the wind energy conversion system are validated using in MATLAB/Simulink. © Published under licence by IOP Publishing Ltd.

关键词： Wind power

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Implementation of Cloud Computing and Internet of Things (IoT) by Performance Evaluation

Implementation of Cloud Computing and Internet of Things (Io...

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International Electrical engineering Congress (iEECON)

作者： Jiran Sithiyopasakul Tuanjai Archevapanich Saran Sithiyopasakul Attasit Lasakul Boonchana Purahong Chawalit Benjangkaprasert School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Electronics and Communication Engineering Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi Nonthaburi Thailand Department of Computer Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9798350383591

ISBN: (纸本)9798350383607

The integration of cloud computing and the Internet of Things (IoT) holds transformative potential across diverse industries. Performance assessment is essential to gauge the quality and efficiency of cloud computing and IoT systems. This paper presents a comprehensive performance evaluation of cloud computing and IoT systems, focusing on three major platforms: Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Experimental results encompass various scenarios, including normal operation, heavy load conditions, IoT applications, and scalability testing. The outcomes reveal distinct performance metrics such as response time, throughput, latency, and reliability for each cloud platform.

关键词： Performance evaluation Cloud computing Web services System performance Throughput Internet of Things Time factors

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Optimizing Cloud Computing Performance using Adaptive and Evolutionary Algorithms for Large Scale Applications

Optimizing Cloud Computing Performance using Adaptive and Ev...

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Distributed Computing and Electrical Circuits and electronics (ICDCECE), IEEE International Conference on

作者： Parashiva Murthy B M Vidhyadar Unni Krishnan M K Pushpa Madhu B K Falguni Tlajiya Aparajita Mohanty Department of Computer Science and Engineering SJCE JSS Science and Technology University Mysuru India Visa Commercial Solutions Division Visa Inc Foster City USA Department of Electronics and Instrumentation Engineering Ramaiah Institute of Technology Bangalore India Department of Computer Science and Engineering Vidya Vikas Institute of Engineering and Technology Mysore India Department of Electrical Engineering Faculty of Engineering and Technology Parul Institute of Engineering and Technology Parul University Vadodara India Faculty of Law Symbiosis Law School Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331533663

ISBN: (纸本)9798331533670

An increasing number of applications are straining cloud computing structures which require novel optimization strategies to boost performance measurements as well as resource utilization. The research methodology incorporates adaptive algorithms together with evolutionary algorithms which provide real-time workload adaptation and distributed system resource optimization. The project implemented machine learning models which predicted resource needs to trigger automatic parameter modification for computing systems. The three major cloud platforms provided results which showed a 37.8% decrease in response latency and a 42.3% lower resource wastage rate and a 29.5% enhanced throughput capacity than static allocation techniques. The cost efficiency rose 31.7% while service reliability maintained 99.4% during the period. A proposed adaptable-evolutionary framework provides an effective solution that leads to improved performance measurements of large-scale cloud programs while reducing operational expenses for transitioning between dynamic computing settings.

关键词： Performance evaluation Cloud computing Machine learning Evolutionary computation Predictive models Throughput Real-time systems Resource management Reliability Optimization

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Optimization of Quality Power Distribution System using Artificial Intelligence

Optimization of Quality Power Distribution System using Arti...

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International Conference on Smart Systems and Inventive technology (ICSSIT)

作者： Satya Prakash Awasthi Sanjay Singh Urmila Pilania Manoj Kumar A.S. Sindhu A.S. Sarika Faculty of Computer Engineering Poornima University Ramchandraoura Jaipur India Dept. of Computer Science & Technology Manav Rachna University Faridabad India Department of Electronics and Communication Engineering Rajas Institute of Technology Tamil Nadu India Department of Electronics and Communication Engineering Amrita College of Engineering and Technology Tamil Nadu India

A maximum power point tracker is used in this study to determine incremental conductance (INC) (MPPT). Artificial Intelligence (AD based analysis and simulation of a solar photovoltaic module and associated electric circuit is presented, along with an examination of the effects of various environmental conditions on the behavior of the PV module. To fully appreciate the operating parameters of a PV module, basic PV cell attributes are addressed. A block diagram model of a PV module was made in Simulink and used to illustrate the curves. The results of simulations using a solar module demonstrate that the suggested method is quick and precise. This model is effectively used utilizing steady conductance in light of most maximum power point tracking methodologies for testing the behavior of the suggested system and forestall this output in the simulation via MATLAB. Controller can be implemented using a number of different techniques and algorithms. Power Point is liked here and is likewise reasonable for business purposes due to the minimal oscillations while establishing the Maximum.

关键词： Maximum power point trackers Photovoltaic systems Software packages Power quality Mathematical models Behavioral sciences Steady-state

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Design and Analysis of High-Speed Communication Systems for 5G and Beyond

Design and Analysis of High-Speed Communication Systems for ...

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International Conference on Science technology engineering and Management (ICONSTEM)

作者： R. Jegadeesan Dava Srinivas M. Deivakani Sunita Joshi P M Dinesh M Jogendra Kumar Department of Computer Science and Engineering Jyothishmathi Institute of Technology and Science Karimnagar Telangana India Department of Electronics and Communication Engineering PSNA College of Engineering and Technology Dindigul Tamil Nadu Department of Faculty of Computer Applications Manav Rachna International Institute of Research and Studies Faridabad Haryana India Department of Electronics and Communication Engineering Sona College of Technology Salem Tamil Nadu India Department of Computer Science and Engineering KoneruLakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

Fifth Era Innovation (5G) is the late portable network in wireless communications. This article presents an assessment of the advancements in portable communications. The different issues that arise at each stage are reported in our guide to state-of-the-art wearable networks. The fifth era (5G) of portable networks offers everybody admittance to high-speed web at whatever point they need, any place they are. Since to its inventive qualities, such connecting individuals and controlling contraptions, machines, and items, 5G is somewhat unique. Various levels of execution and capacities presented by the 5G versatile innovation will make new client encounters and connection new organizations. It is pivotal to comprehend where the business can utilize5G's benefits. This work examines and models a microstrip fix antenna working at 29 GHz for impending 5G communication innovation. The result of this reproduction is better than past work that was finished. It can then be used as a significant source of strength for 5G wireless technologies. The ongoing logic diary demonstrates that the proposed antenna performs better than those currently in use. This antenna may therefore be adequate for his 5G wireless connection architecture.

关键词： Wireless communication Technological innovation 5G mobile communication Millimeter wave technology Microstrip antennas Organizations Microstrip

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Enhancing Remote Sensing Image Classification Using Arithmetic Optimization Algorithm with Deep Learning Approach

Enhancing Remote Sensing Image Classification Using Arithmet...

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International Conference on Advances in Information technology (ICAIT)

作者： R. Shanthi Balasubramaniam D R. Venkatesh C. Sankari V. Manimaran Shaik Hedayath Basha Department of computer applications Faculty of science and humanities SRM Institute of science and Technology Chengalpattu Tamilnadu Department of Biomedical Engineering VelTech Rangarajan Dr Sagunthala R & D Institute of Science and Technology Chennai Computer Science and Engineering Ramco Institute of Technology Rajapalayam Electrical and Electronics Engineering Chennai Institute of Technology Department of Computer Science and Engineering Kongu Engineering College Erode Tamilnadu Department of ECE R.M.K. College of Engineering and Technology

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

The classification of Remote sensing image (RSI)is a vital task in field of geospatial analysis where aerial or satellite images are classified into predefined classes or land cover sorts. It plays a main part in diverse fields namely agriculture, disaster management, environmental surveillance, urban planning, and natural resource management. With the machine learning (ML) and deep learning (DL) models, these images examined and categorized depending on their spatial, spectral and temporal features. The exact detection of remote sensing images simplifies decision-making procedures, aiding governments, environmental agencies, and companies to make knowledgeable decisions and policies. It authorizes experts to observe variations in lands, discover land use trends, and evaluate environmental effects and making it a vital device in addressing present difficult challenges connected to weather change, urban development, and natural resource protection. This study presents an enhanced remote sensing image classification utilizing arithmetic optimization algorithm with DL (ERSC-AODL) Approach. The ERSC-AODL technique concentrates on the accurate recognition of the RSI into dissimilar classes. It begins with the use of an EfficientNet feature extractor, which derives complex spectral and spatial data, and acts as a base of proper representation of the images. Moreover, the recognition process takes place by a bidirectional long short-term memory (BiLSTM). Finally, the hyperparameter optimization procedure is performed by the ERSC-AODL technique. To portray the proficient classification outputs of the ERSC-AODL technique, a range of experiments were utilized. The investigational outputs stated that the ERSC-AODL technique attains improved accomplishment over other models.

关键词： Natural resources Recurrent neural networks Feature extraction Spatial databases Classification algorithms Data mining Remote sensing Optimization Long short term memory Image classification

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Green Communication in 6G 8

Green Communication in 6G

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8th International Conference on Mechatronics engineering, ICOM 2022

作者： Hoque, Mahfara Binta Farhad, Syeda Sohana Dewanjee, Supriya Alom, Zulfikar Mokhtar, Rania A. Saeed, Rashid A. Khalifa, Othman O. Ali, E.S. Azim, M. Abdul Department of Computer Science Asian University for Women Chattogram Bangladesh Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Electrical and Electronics Engineering Faculty of Engineering International Islamic University Malaysia Malaysia The Libyan Center for Engineering Research and Information Technology Bani Walid Libya Sudan

ISBN: (数字)9781839538063

ISBN: (纸本)9781839538063

Green communication networking is a part of sustainable development. It aims to reduce energy consumption and serve the network to a vast number of servers cost-effectively. Green communication integrates artificial intelligence to solve complex mathematical problems for enhancing energy efficiency, flexibility, security, and quality of life services. One of the most remarkable characteristics of today's telecoms sector is wireless communication, used for more than a century. Infrared, radio frequency, satellite, and other electromagnetic waves are used in wireless communication technologies to send data over the air. More data is necessary for the 6G experience. More data is necessary and more excellent ambient sensing and awareness. Sensing systems in automated cars, for example, are exceedingly complicated and rely on cellular networks. Mobile and wireless networks, such as 6G, can use green communication to balance resource usage and conserve energy. In this study, 6G for green communication has been discussed to justify the necessity of 6G. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Wireless networks

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A Novel Hybrid Evolutionary Computing Framework for Scalable and Efficient Problem Solving

A Novel Hybrid Evolutionary Computing Framework for Scalable...

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Distributed Computing and Electrical Circuits and electronics (ICDCECE), IEEE International Conference on

作者： T. S. Umamaheswari Sharada Prasad N Mahesh Kumar A. S T. Vamshi Mohana Amit Gantra Vivek Nemane Department of Computer Science & Applications Jayagovind Harigopal Agarwal Agarsen College Chennai India Department of Electrical and Electronics Engineering RNSIT Bangalore India Department of Electronics and Communication Engineering Maharaja Institute of Technology Mysore India Department of Computer Science R.B.V.R.R. Women’s College Hyderabad India Department of Computer Science and Engineering Faculty of Engineering and Technology Parul Institute of Engineering and Technology Parul University Post Limda India Faculty of Law Symbiosis Law School Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331533663

ISBN: (纸本)9798331533670

Most of the conventional EA encounter scalability and performance issues in solving large-scale optimization problems. For these reasons, this research presents a sophisticated HECF that addresses all the aforementioned limitations. The application of genetic algorithms, particle swarm optimization, and differential evolution as another evolutionary paradigm in a selection mechanism such that the computational resources will be allocated based on a dynamic scheme will be proposed in this research. Because all the delay parameters used in the model are optimized at runtime by the help of learning functions, the methods of machine learning are used in this algorithm. In the benchmark problems, the results come up with 87.3% improvement of solution quality and 62.1% time reduction of the proposed hybrid framework over the traditional methods. Analysis of scalability: proven in scalability tests and problems of increasing dimensions (retained efficiency 95.8%). This framework of ECA can be used for a comprehensive solution when there is great specialization in the feasible region and the optimization problem is highly complex and large in size.

关键词： Runtime Machine learning algorithms Scalability Heuristic algorithms Machine learning Dynamic scheduling Problem-solving Particle swarm optimization Optimization Genetic algorithms

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