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Multi-ant colony algorithm based on the Stackelberg game and incremental learning

Soft Computing 2025年第4期29卷 2107-2128页

作者： Wu, Qihuan You, Xiaoming Liu, Sheng School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai201620 China School of Management Shanghai University of Engineering Science Shanghai201620 China

To address the difficulties of slow convergence and inadequate accuracy of traditional ant colony algorithms in solving the traveling salesman problem (TSP), we propose a multi-ant colony algorithm based on the Stackelberg game and incremental learning (SGIACO). We incorporate the Stackelberg game strategy across multiple colonies, where the leader guides the follower to optimize population co-evolution, ensuring a balance between convergence and diversity of the algorithm. Furthermore, we propose an incremental learning strategy that enhances efficient paths on the public routes and ignores inefficient ones, thus accelerating the convergence speed of the algorithm. Finally, when the algorithm stagnates, a pheromone balance mechanism is implemented to help the ants escape from local optima. We conducted experiments on 23 TSP instances to validate the algorithm's performance and compare it to ACS, MMAS, as well as other recent algorithms. In addition, non-parametric tests were conducted for comprehensive performance analysis. Moreover, we verified the feasibility of SGIACO through simulations in robot path planning scenarios. The experimental results show that SGIACO has good convergence and accuracy, which is competitive with other algorithms. Future research aims to scale SGIACO for larger real-world applications, enhancing its adaptability and scalability. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Ant colony optimization

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Improving Power Response of Single-Controllable VSG-Based Active Distribution Network

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CSEE Journal of Power and Energy Systems 2025年第1期11卷 102-114页

作者： Shah Fahad Arman Goudarzi Pierluigi Siano Ji Xiang Department of Electrical and Computer Engineering Missouri University of Science and TechnologyUSA University of Victoria Canada Department of Management&Innovation Systems University of SalernoItaly Department of Electrical and Electronic Engineering Science University of JohannesburgJohannesburg2006South Africa National Laboratory of Industrial Control Technology College of Electrical EngineeringZhejiang UniversityHangzhou310058China

Controlling an active distribution network(ADN)from a single PCC has been advantageous for improving the performance of coordinated Intermittent RESs(IRESs).Recent studies have proposed a constant PQ regulation approach at the PCC of ADNs using coordination of non-MPPT based ***,due to the intermittent nature of DGs coupled with PCC through uni-directional broadcast communication,the PCC becomes vulnerable to transient *** address this challenge,this study first presents a detailed mathematical model of an ADN from the perspective of PCC regulation to realize rigidness of PCC against ***,an H_(∞)controller is formulated and employed to achieve optimal performance against disturbances,consequently,ensuring the least oscillations during transients at ***,an eigenvalue analysis is presented to analyze convergence speed limitations of the newly derived system ***,simulation results show the proposed method offers superior performance as compared to the state-of-the-art methods.

关键词： Cooperative control of DGs hierarchical control system high penetration of intermittent RESs H_(∞)control optimal control in power systems single-controllable active distribution networks

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Internet of things technology, research, and challenges: a survey

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Multimedia Tools and Applications 2025年第11期84卷 8455-8490页

作者： Vishwakarma, Amit Kumar Chaurasia, Soni Kumar, Kamal Singh, Yatindra Nath Chaurasia, Renu Management science and technology Khalifa University Abu Dhabi United Arab Emirates Computer science & Engineering SGT University Gurugram India Department of Information Technology IGDTUW New Delhi India Electrical Engineering IIT Kanpur Kanpur India Computer science & Engineering AIT Rooma Kanpur India

The world of digitization is growing exponentially;data optimization, security of a network, and energy efficiency are becoming more prominent. The Internet of Things (IoT) is the core technology of modern society. This paper is based on a survey of recent and past technologies used for IoT optimization models, such as IoT with Blockchain, IoT with WSN, IoT with ML, and IoT with big data analysis. Suppose anyone wants to start core research on IoT technologies, research opportunities, challenges, and solutions. In that case, this paper will help me understand all the basics, such as security, interoperability, standards, scalability, complexity, data management, and quality of service (QoS). This paper also discusses some recent technologies and the challenges in implementation. Finally, this paper discusses research possibilities in basic and applied IoT Domains. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Internet of things

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Impact of dissolution and precipitation on pore structure in CO2 sequestration within tight sandstone reservoirs

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Petroleum science 2025年第2期22卷 868-883页

作者： Hui Gao Kai-Qing Luo Chen Wang Teng Li Zhi-Lin Cheng Liang-Bin Dou Kai Zhao Nan Zhang Yue-Liang Liu School of Petroleum Engineering Xi'an Shiyou University Engineering Research Center of Development and Management for Low to Ultra-Low Permeability Oil & Gas Reservoirs in West China Ministry of Education Xi'an Key Laboratory of Tight Oil (shale Oil) Development Department of Electrical Engineering and Computer Science University of Stavanger School of Petroleum Engineering China University of Petroleum (Beijing)

Complex physical and chemical reactions during CO2sequestration alter the microscopic pore structure of geological formations,impacting sequestration *** investigate CO2sequestration dynamics,comprehensive physical simulation experiments were conducted under varied pressures,coupled with assessments of changes in mineral composition,ion concentrations,pore morphology,permeability,and sequestration capacity before and after ***,a method using NMR T2spectra changes to measure pore volume shift and estimate CO2sequestration is *** quantifies CO2needed for mineralization of soluble ***,when CO2dissolves in crude oil,the precipitation of asphaltene compounds impairs both seepage and storage ***,the impact of dissolution and precipitation is closely associated with storage pressure,with a particularly pronounced influence on smaller *** pressure levels rise,the magnitude of pore alterations progressively *** a pressure threshold of 25 MPa,the rate of change in small pores due to dissolution reaches a maximum of 39.14%,while precipitation results in a change rate of-58.05% for small *** observed formation of dissolution pores and micro-cracks during dissolution,coupled with asphaltene precipitation,provides crucial insights for establishing CO2sequestration parameters and optimizing strategies in low permeability reservoirs.

关键词： Dissolution Precipitation Pore structure CO 2 sequestration Unconventional reservoirs

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Optimizing Autonomous Intersection Control Using Single Agent Reinforcement Learning 25

Optimizing Autonomous Intersection Control Using Single Agen...

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26th International Conference on Distributed Computing and Networking, ICDCN 2025

作者： Ganar, Yash Kumar, Vinay Dulera, Shraddha Yadav, Ram Narayan Electrical and Computer Science Engineering Institute of Infrastructure Technology Research and Management Ahmedabad India

ISBN: (纸本)9798400710629

Autonomous intersection management (AIM) presents significant challenges due to the complexity of real-world traffic scenarios and the reliance on a costly centralized server to manage and coordinate all vehicles simultaneously. In this work, we address the challenge of efficiently and safely navigating intersections using a Reinforcement Learning (RL). In this work, we proposed two autonomous intersection management algorithms based on (i) Proximal Policy Optimization (PPO), and (ii) Advantage Actor-Critic (A2C). We design a reward function to encourage the system to reduce collisions while maintaining high throughput. By training and testing these algorithms in complex traffic scenarios, we aim to identify which algorithm demonstrates better decision-making capabilities under different conditions. We evaluated performance across multiple metrics, including collision avoidance, safe and efficient travel speed, time to reach the destination, and reward functions. We have established a structured approach to help researchers make informed decisions regarding suitable algorithm selection. It provides a balanced comparison between the algorithms and suggests a recommendation system for intersection traffic environments, considering various performance metrics such as reward, collision, speed, and travel time. © 2025 Copyright held by the owner/author(s).

关键词： Travel time

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End-To-End Encryption Enabled Lightweight Mutual Authentication Scheme for Resource Constrained IoT Network

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Computers, Materials & Continua 2025年第2期82卷 3223-3249页

作者： Shafi Ullah Haidawati Muhammad Nasir Kushsairy Kadir Akbar Khan Ahsanullah Memon Shanila Azhar Ilyas Khan Muhammad Ashraf Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Computer Engineering Section Malaysian Institute of Technology Universiti Kuala LumpurKuala Lumpur50250Malaysia Electrical Engineering Section Universiti Kuala LumpurBritish Malaysian InstituteSalengor53100Malaysia Electrical Engineering Department Mehran UniversityKhairpur-Mirs76062Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backbone for Industrial IoT, smart cities, and other autonomous systems. Due to the limited computing and memory capacity, these devices cannot maintain strong security if conventional security methods are applied such as heavy encryption. This article proposed a novel lightweight mutual authentication scheme including elliptic curve cryptography (ECC) driven end-to-end encryption through curve25519 such as (i): efficient end-to-end encrypted communication with pre-calculation strategy using curve25519;and (ii): elliptic curve Diffie-Hellman (ECDH) based mutual authentication technique through a novel lightweight hash function. The proposed scheme attempts to efficiently counter all known perception layer security threats. Moreover, the pre-calculated key generation strategy resulted in cost-effective encryption with 192-bit curve security. It showed comparative efficiency in key strength, and curve strength compared with similar authentication schemes in terms of computational and memory cost, communication performance and encryption robustness.

关键词： Mutual authentication lightweight end-to-end encryption elliptic curve cryptography industrial internet of things curve25519 machine-to-machine communication

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Application of Particle Swarm Optimization Tuned Controllers for Automatic Voltage Regulator

Application of Particle Swarm Optimization Tuned Controllers...

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International Conference on Computational Intelligence and Smart Technologies in electrical engineering, CISTEE 2023

作者： Shukla, Hiramani Rai, Shiwani Mundra, Pratik Ansari, Aftab Ahmad Raju, More Department of Electrical Engineering U.V. Patel college of Engineering Ganpat University Mehsana-Gozaria Highway Gujarat 384012 India Department of Electrical and Electronics Engineering IES Institute of Technology and Management IES University M.P Bhopal India Electrical Engineering Department G H Raisoni College of Engineering and Management Pune India Department of Electrical and Electronics Engineering Bansal Institute of Research Technology and Science Bhopal India Electrical Engineering Department Maulana Azad National Institute of Technology Bhopal India

ISBN: (纸本)9789819604753

The present investigation examines the process of optimizing the gains for both the fractional order proportional integral derivative (FOPID) and PID controllers that are employed in automated voltage regulation (AVR). Investigating and assessing the effectiveness of the FOPID controller tuned with particle swarm optimization (PSO) using various optimization techniques is the main objective of this study. This study aims to evaluate and compare the overall efficacy of a PID controller with that of a PSO-tuned FOPID controller. The cost function employed in the evaluation procedure is the integral square error (ISE). The simulation results clearly demonstrate that the PSO-tuned FOPID controller outperforms the PSO-tuned PID controllers in terms of peak overshoot, undershoot, and settling time. The PSO's performance is also evaluated in comparison to other optimization approaches. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Particle swarm optimization (PSO)

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Detection of myocardial infarction diseases based on entropy, optimized stockwell time-frequency transform and extreme learning machine

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International Journal of Information Technology (Singapore) 2025年 1-7页

作者： Besfat, Henok Mezemr Galmecha, Demissie Jobir Singh, Ram Sewak Mishra, Satyasis Electronics and Communication Engineering Department College of Electrical Engineering and Computing Adama Science and Technology University P.Box. 1888 Adama Ethiopia Department of ECE Centurion University of Technology and Management Gajapati India

Early and accurate detection of myocardial infarction (MI) is pivotal in enhancing cardiac function, as it can result in a heart attack. Detecting MI arrhythmias from electrocardiogram (ECG) signals presents challenges in accurately extracting patterns, such as Q, R, S and T wave segments. This paper proposes an efficient automated MI detection based on optimized Stockwell transform (OptST), Renyi entropy, dispersion entropy, and extreme learning machine (ELM) algorithm. The OptST is employed to decompose the ECG signal to four frequency band. The renyi and dispersion entropy features are then extracted in each frequency band for training and validation of ELM model to classify the five MI diseases. To identify clinically significant features, a Wilcoxon rank sum test is conducted, and to test the robustness of the proposed method 5-fold cross-validation has been applied. The simulation results have demonstrated that the proposed model has achieved a highest accuracy of 96.86%, specificity of 98.04%, recall of 92.16%, and F-score of 92.18% for sine activation function at hidden number of 300. © Bharati Vidyapeeth's Institute of Computer Applications and management 2025.

关键词： Dispersion entropy ELM Myocardial infarction Renyi entropy Stockwell transform

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Adaptive observer-based bipartite tracking consensus for nonlinear multi-agent systems with unknown sensor failures

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ISA Transactions 2025年 161卷 73-87页

作者： Chen, Yun Xu, Huiling Lin, Zhiping Chen, Yuqing Li, Zhengcai Zhang, Jun School of Mathematics and Statistics Nanjing University of Science and Technology Nanjing210094 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore School of Economics and Management Nanjing University of Science and Technology Nanjing210094 China

This paper investigates the bipartite tracking consensus (BTC) problem for a broad class of nonlinear multi-agent systems (NMASs) with and without unknown sensor failures. In order to relax the constraint on nonlinear dynamics in signed graph, a general lemma that extends differential mean value theorem is first put forward. On this basis, an adaptive controller is designed to achieve the bounded BTC for the NMASs. Furthermore, when unknown sensor failures occur, an adaptive observer is devised to estimate the uncompromised system states and failure factors simultaneously. Combining the proposed adaptive observer and controller, the bounded BTC property can be maintained in the presence of unknown sensor failures. Lastly, two simulation examples are carried out to illustrate the effectiveness of the proposed methods. © 2025

关键词： Adaptive control systems

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Machine Learning for Wireless Network Optimization: Algorithms and Applications for Adaptive Communication 1

Machine Learning for Wireless Network Optimization: Algorith...

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1st International Conference on Advances in Computer science, electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Srinivas, Madhira Surya, S. Thakar, Prachi Deepak Jain, Amit Kumar Department of Computer Science & Engineering Hyderabad501301 India Chennai600116 India KJ college of Engineering & Management Research Department of Computer Engineering Pune India Poornima University Department of Electrical & Electronics Engineering Rajasthan Jaipur303905 India

ISBN: (纸本)9798331518578

This project looks into the possibility of applying machine learning to optimize wireless networks for adaptive communication. Using 5G resource data, it applies preprocessing, exploratory analysis, and visualization to identify key trends: signal strength, latency, and bandwidth utilization. Machine learning algorithms predict resource allocation based on latency-sensitive and bandwidth-demanding applications. The approach emphasizes energy efficiency, scalability, and service quality, and dynamically adjusts communication strategies to meet diverse network demands. The findings indicate the machine learning importance in enhancing elasticity and robustness in a wireless network and its general function. © 2025 IEEE.

关键词： 5G Optimization Adaptive Communication Bandwidth Data Pre-processing EDA Energy Efficiency Latency Machine Learning Network Elasticity Predictive Models Resource Allocation Scalability Signal Strength Wireless Networks

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