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33rd Southern African Universities Power engineering Conference, SAUPEC 2025

作者： Johnson, Rayner Krishnamurthy, Senthil Mataifa, Haltor Esmail, Mohammed Cape Peninsula University of Technology Center for Substation Automation and Energy Management Systems Department of Electrical Electronic and Computer Engineering Cape Town7530 South Africa

ISBN: (纸本)9798331535162

The growing adoption of renewable energy primary plants has been seen globally. South Africa has seen a significant development in utility-scale photovoltaic (PV) farms in recent years due to the alleviated regulations stipulated in the latest Electricity Regulation Amendment Act. Connecting the PV plants to the power grid has also undergone a technical evolution by incorporating modern embedded computers known as Intelligent Electronic Devices (IEDs). The International Electrotechnical Committee (IEC) 61850 standard defines a suite of protocols used in modern power systems. This study compares the IEC 61850 Manufacturing Messaging Specification (MMS) with the well-known MODBUS protocol. The comparison is achieved by simulating a solar farm's Power Plant Controller (PPC). © 2025 IEEE.

关键词： Solar power plants

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An Algorithmic Approach to Intrusion Detection in Ad Hoc Wireless Networks Based on Artificial Intelligence

An Algorithmic Approach to Intrusion Detection in Ad Hoc Wir...

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Sonekar, Shrikant V. Kshirsagar, Pravin R. Unhelkar, Bhuvan Chakrabarti, Prasun Maram, Balajee Upreti, Kamal J D College of Engineering & Management Department of Computer Science & Engineering Nagpur India J D College of Engineering & Management Department of Electronics & Telecommunication Engineering Nagpur India Muma College of Business University of South Florida Department of Infornation Systems and Decision Sciences Sarasata United States Sir Padampat Singhania University Department of Computer Science & Engineering Rajasthan Udaipur3313606 India Sr University Department of Computer Science and Artificial Intelligence Telangana Warangal506371 India Christ University Department of Computer Science Delhi NCR Ghaziabad India

ISBN: (纸本)9798331527495

The self-configured, autonomous, and framework-free modes of communication that mobile adhoc networks (MANETs) offer have revolutionized our culture. As a result, efforts have been made to explore ways to maximize the potential of MANETs through increased and improved utilization. Standards for AI have been developed thanks to the most recent release of new machine learning technologies. Different security-related issues from malware assaults affect mobile ad hoc networks (MANETs). Any node operates as a router to move data without centralized control, making nodes more vulnerable to threats from other nodes or attackers because of their brief existence. Because of this, MANET needs particular security policies to detect the incorrect entrance of misbehaving nodes. If all nodes are self-assured and correctly collaborate, the networks function better. The paper presents a practical artificial intelligence algorithm-based security system that uses AdaBoost and DT algorithms to recognize and identify packet falling nodes, classify information packets as normal or abnormal, and detect insider threats in real-time. The results showed that DT performed better than AdaBoost, with a 98% accurate prediction rate. Consequently, DT is better able to recognize damaging attacks in MANETs. © 2025 IEEE.

关键词： Computer viruses

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Early Time Series Anomaly Prediction with Multi-Objective Optimization

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IEEE Transactions on Emerging Topics in Computational Intelligence 2025年第1期9卷 972-987页

作者： Chao, Ting-En Huang, Yu Dai, Hao Yen, Gary G. Tseng, Vincent S. National Yang Ming Chiao Tung University Institute of Information Management Hsinchu300093 Taiwan Oklahoma State University Department of Electrical and Computer Engineering StillwaterOK74078 United States National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300093 Taiwan National Chung Hsing University Department of Management Information Systems Taichung402 Taiwan

Anomaly prediction, aiming to predict abnormal events before occurrence, plays a key role in significantly reducing costs and minimizing potential threats to mechanical devices. Monitoring machines using fixed-length time windows faces challenges in accommodating the varying characteristics of anomaly events. The lengthy and imbalanced sequence data associated with anomaly events further complicates the resolution of these challenges. Additionally, the inherent trade-off between accurate prediction and timely alarm is a crucial concern, posing difficulties in decision-making. This study puts forward a novel framework for early anomaly prediction, named early time series Anomaly Prediction with Neighbor Over-sampling and Multi-objective Optimization (APNOMO), pronounced as 'abnormal'. The framework employs three key techniques: 1) sliding windows that divide long input sequences into segments for prediction at proper intervals, 2) over-sampling and proposed neighbor over-sampling that handle imbalanced data in a novel way, and 3) multi-objective optimization that searches optimal thresholds to balance accurately prediction and timely alarm the abnormal. Experiments on a real-world dataset demonstrate APNOMO's superior performance over some state-of-the-art designs, with higher recall, F1 score, and more suitable earliness. It can predict anomalies 0.78-3.56 hours in advance, showcasing excellent early anomaly prediction capabilities for enabling predictive maintenance. © 2017 IEEE.

关键词： Predictive maintenance

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Computations and Complexities of Tarski’s Fixed Points and Supermodular Games 18th

Computations and Complexities of Tarski’s Fixed Points an...

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18th International Joint Conference on Theoretical Computer Science-Frontier of Algorithmic Wisdom, IJTCS-FAW 2024

作者： Dang, Chuangyin Qi, Qi Ye, Yinyu Department of Systems Engineering City University of Hong Kong Kowloon Tong Hong Kong Gaoling School of Artificial Intelligence Renmin University of China Beijing China Department of Management Science and Engineering Stanford University StanfordCA94305-4026 United States

ISBN: (纸本)9789819777518

We consider two models of computation for Tarski’s order preserving function f related to fixed points in a complete lattice: the oracle function model and the polynomial function model. In both models, we find the first polynomial time algorithm for finding a Tarski’s fixed point. In addition, we provide a matching oracle bound for determining the uniqueness in the oracle function model and prove it is Co-NP hard in the polynomial function model. The existence of the pure Nash equilibrium in supermodular games is proved by Tarski’s fixed point theorem. Exploring the difference between supermodular games and Tarski’s fixed point, we also develop the computational results for finding one pure Nash equilibrium and determining the uniqueness of the equilibrium in supermodular games. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Nash equilibrium

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Single-Loop Variance-Reduced Stochastic Algorithm for Nonconvex-Concave Minimax Optimization

arXiv

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arXiv 2025年

作者： Jiang, Xia Zhu, Linglingzhi Zheng, Taoli So, Anthony Man-Cho Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong

Nonconvex-concave (NC-C) finite-sum minimax problems have broad applications in decentralized optimization and various machine learning tasks. However, the nonsmooth nature of NC-C problems makes it challenging to design effective variance reduction techniques. Existing vanilla stochastic algorithms using uniform samples for gradient estimation often exhibit slow convergence rates and require bounded variance assumptions. In this paper, we develop a novel probabilistic variance reduction updating scheme and propose a single-loop algorithm called the probabilistic variance-reduced smoothed gradient descent-ascent (PVR-SGDA) algorithm. The proposed algorithm achieves an iteration complexity of O(∊−4), surpassing the best-known rates of stochastic algorithms for NC-C minimax problems and matching the performance of the best deterministic algorithms in this context. Finally, we demonstrate the effectiveness of the proposed algorithm through numerical simulations. Copyright © 2025, The Authors. All rights reserved.

关键词： Consensus algorithm

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Understanding Organizational Transitions: Interpretable Top Manager Turnover Prediction using a Heterogeneous Graph Neural Network 24

Understanding Organizational Transitions: Interpretable Top ...

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8th International Conference on Computer Science and Artificial Intelligence, CSAI 2024

作者： Guo, Yameng Ren, Qiuzhen vanden Broucke, Seppe Ghent University Department of Business Informatics and Operations Management Ghent Belgium Ghent University Department of Economics Ghent Belgium KU Leuven Research Centre for Information Systems Engineering Leuven Belgium

ISBN: (纸本)9798400718182

Managerial turnover has garnered increasing attention with the growth of talent mobility and global competition. Top managers, being key figures in leadership groups, can significantly affect organizational performance, highlighting the importance of predicting turnover amongst them and understanding their transition patterns. Although extensive predictive modeling methodologies have been employed in previous research, most do not utilize the historical career trajectories of top managers and neglect the effects of transitions of co-workers. Additionally, works utilizing stronger predictive techniques typically do so at a trade-off of being able to extract interpretable insights from the constructed models. In an effort to enrich our understanding of top manager transitions, this work starts from the construction of a heterogeneous graph consisting of managers and the companies for which they have worked. Then, a graph neural network based model is utilized to predict potential turnover behavior. A novel interpretation framework capable of assigning attribution in terms of influence on the predicted outcome to all elements in the graph is then introduced to explain the factors affecting turnover in practice. The complete methodology is executed on a large data set stemming from the China Stock Market & Accounting Research Database (CSMAR). © 2024 Copyright held by the owner/author(s).

关键词： Graph neural networks

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Empowering self-sustained agriculture: an IoT field tracking model driven by fog computing

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Discover Internet of Things 2025年第1期5卷 1-18页

作者： Singh, Gurpreet Singh, Jaspreet Juneja, Sapna Gulzar, Yonis Gupta, Deepali Ghafoor, Kayhan Zrar Kumar, Mukesh Department of Computer Science and Engineering Chandigarh University Punjab Chandigarh140413 India KIET Group of Institutions Delhi-NCR Uttar Pradesh Ghaziabad201206 India Department of Management Information Systems College of Business Administration King Faisal University Al-Ahsa31982 Saudi Arabia Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Department of Information and Communication Technology Eng Erbil Polytechnic University 42VQ+756 120 Meter St Erbil Erbil Governorate Iraq Mechanical Engineering College of Engineering Assosa University Assosa5220 Ethiopia

Increasing availability of cost effective IoT (Internet of Things) devices have led to the development of IoT- based farm management systems. Smart Agriculture is a demanding approach that employs the use of technology-enabled information and communication to monitor farms. In India, somewhere around 60% of the organization’s operations mostly dependent on agriculture directly or indirectly. A nation’s advancement is typically influenced by concerns with agriculture. The most effective approach to addressing agriculture’s challenges is always to improve traditional agricultural practices as well as modernize them into smart agriculture. The smart agriculture technique offers beneficial data collection, highly precise control as well as automated monitoring strategies. This research proposed a IoT assisted fog-based model that promises to provide the cost-effective smart agriculture system. Fog platform brings computation and storing nearer at the network’s the border, allowing for the efficient processing of data produced by IoT devices across smart agricultural systems. The bibliometric evaluation of the Web of Science database for the adoption of the IoT-Fog base infrastructure in the creation of smart agriculture systems is also highlighted in this paper. The proposed solution when implemented as well as when contrasted with existing IoT-based agriculture system exhibit better efficiency. The result revealed that proposed system brings down response time, error rate and standard deviation to significant level and improves the accuracy of current system exponentially. © The Author(s) 2025.

关键词： Agricultural robots

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Multiagent reinforcement learning-based dispatching model for overhead hoist transfer in automated material handling system

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Computers and Industrial engineering 2025年 204卷

作者： Chou, Che-Wei Chiu, Wei-Cheng Hsu, Yu-Teng Department of Industrial Engineering and Systems Management Feng Chia University Taiwan Taichung China

Advances in wafer fabrication technology and production processes have increased the complexity of the operations of automated material handling systems (AMHS) in semiconductor foundries. The wafer transport demand fluctuates on production plans, equipment status, and the production statuses of other areas. The challenges of OHT allocation approaches are to consider the fluctuations in wafer transport demands and their effect on dispatching overhead hoist transport (OHT) vehicle dispatch. This study develops a novel dispatching model that employs multiagent reinforcement learning to optimize the allocation of OHT vehicles in an AMHS within a semiconductor foundry. This dynamic OHT vehicle dispatching model utilizes the multiagent independent proximal policy optimization algorithm (MAIPPO), which incorporates an attention network architecture within the framework of a partially observable Markov game. In this model, each production bay within AMHS is treated as a reinforcement learning agent responsible for OHT vehicle dispatch decisions within the bay. Simulation results demonstrate that the proposed multiagent reinforcement learning-based dispatching model approaches outperform classical dispatching rules in AMHS transport efficiency. It learns to allocate idle OHT vehicles to regions with higher transport demand. The developed model's scalability in managing complex high-dimensional state spaces enables it to provide robust support for the optimization of large-scale AMHS in real-world scenarios. © 2025 Elsevier Ltd

关键词： Hoists

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Intrusion Detection in NSL-KDD Dataset Using Hybrid Self-Organizing Map Model

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Computer Modeling in engineering & Sciences 2025年第4期143卷 639-671页

作者： Noveela Iftikhar Mujeeb Ur Rehman Mumtaz Ali Shah Mohammed J.F.Alenazi Jehad Ali Knowledge Unit of Systems and Technology University of Management and TechnologySialkot51310Pakistan Department of Computer Science University ofWahWah Cantt47010Pakistan Department of Computer Engineering College of Computer and Information Sciences(CCIS)King Saud UniversityRiyadh11451Saudi Arabia Department of AI Convergence Network Ajou UniversitySuwon16499Republic of Korea

Intrusion attempts against Internet of Things(IoT)devices have significantly increased in the last few *** devices are now easy targets for hackers because of their built-in security *** a Self-Organizing Map(SOM)hybrid anomaly detection system for dimensionality reduction with the inherited nature of clustering and Extreme Gradient Boosting(XGBoost)for multi-class classification can improve network traffic intrusion *** proposed model is evaluated on the NSL-KDD *** hybrid approach outperforms the baseline line models,Multilayer perceptron model,and SOM-KNN(k-nearest neighbors)model in precision,recall,and F1-score,highlighting the proposed approach’s scalability,potential,adaptability,and real-world ***,this paper proposes a highly efficient deployment strategy for resource-constrained network *** results reveal that Precision,Recall,and F1-scores rise 10%-30% for the benign,probing,and Denial of Service(DoS)*** particular,the DoS,probe,and benign classes improved their F1-scores by 7.91%,32.62%,and 12.45%,respectively.

关键词： Intrusion detection self-organizing map Internet of Things dimensionality reduction

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Multi-criteria analysis applied to ranking rehabilitation strategies of water distribution networks

Multi-criteria analysis applied to ranking rehabilitation st...

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作者： Brentan, Bruno Carpitella, Silvia Zanfei, Ariele Gabriel Souza, Rui Menapace, Andrea Meirelles, Gustavo Righetti, Maurizio Izquierdo, Joaquín Hydraulic Engineering and Water Resources Department School of Engineering Universidade Federal de Minas Gerais—UFMG Belo Horizonte Brazil Department of Manufacturing Systems Engineering and Management California State University NorthridgeCA United States Faculty of Engineering Free University of Bozen-Bolzano Bolzano Italy Institute for Multidisciplinary Mathematics Universitat Politécnica de Valéncia Valencia Spain

Rehabilitation of water distribution systems is a complex task that water companies have to tackle continually to keep high-quality service. The larger and more complex the network, the harder to make decisions about the network maintenance strategy to be implemented. Considering pipe replacement as a strategy for water network rehabilitation, this work presents a combination of water distribution system analysis and multi-criteria analysis to rank alternatives for pipe replacement. A set of eight performance criteria is used to evaluate the rehabilitation alternatives. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is herein adopted to rank the solutions, coupled with a final sensitivity analysis on criteria weights. The obtained results point out as pipe replacement is an essential strategy for rehabilitation since the eight evaluation criteria are improved. The sensitivity analysis shows the best solutions' robustness, with just a few variations in their position in the ranking. The most frequent best solution is then hydraulically evaluated, showing the real benefits of pipe replacement in terms of pressure deficit reduction. © 2023 John Wiley & Sons Ltd.

关键词： Water distribution systems

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