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Al-Biruni Based Optimization of Rainfall Forecasting in Ethiopia

computer systems Science & engineering 2023年第6期45卷 2885-2899页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Fadwa Alrowais Mostafa Abotaleb Abdelhameed Ibrahim Doaa Sami Khafaga Department of Communications and Elecronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science F aculty of Computer and Infomation SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Progamming South Ual State UniversityChelyabinsk454080Russia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Rainfall plays a significant role in managing the water level in the *** unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the *** individuals,especially those in the agricultural sector,rely on rain *** rainfall is challenging because of the changing nature of the *** area of Jimma in southwest Oromia,Ethiopia is the subject of this research,which aims to develop a rainfall forecasting *** estimate Jimma's daily rainfall,we propose a novel approach based on optimizing the parameters of long short-term memory(LSTM)using Al-Biruni earth radius(BER)optimization algorithm for boosting the fore-casting accuracy.N ash-Sutcliffe model eficiency(NSE),mean square error(MSE),root MSE(RMSE),mean absolute error(MAE),and R2 were all used in the conducted experiments to assess the proposed approach,with final scores of(0.61),(430.81),(19.12),and(11.09),***,we compared the proposed model to current machine-learning regression models;such as non-optimized LSTM,bidirectional LSTM(BiLSTM),gated recurrent unit(GRU),and convolutional LSTM(ConvLSTM).It was found that the proposed approach achieved the lowest RMSE of(19.12).In addition,the experimental results show that the proposed model has R-with a value outperforming the other models,which confirms the superiority of the proposed *** the other hand,a statistical analysis is performed to measure the significance and stability of the proposed approach and the recorded results proved the expected perfomance.

关键词： Rainfall prediction long short-term memory Al-Biruni earth radius algorithm meta-heuristic optimization

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A Fast and Accessible Neural Network Based Eye-Tracking System for Real-Time Psychometric and HCI Applications 10

A Fast and Accessible Neural Network Based Eye-Tracking Syst...

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10th Scholar's Yearly Symposium of Technology, engineering and Mathematics, SYSTEM 2024

作者： Iacobelli, Emanuele Pelella, Davide Ponzi, Valerio Russo, Samuele Napoli, Christian Department of Computer Automatic and Management Engineering Sapienza University of Rome Rome00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Roma00185 Italy Department of Psychology Sapienza University of Rome Rome00185 Italy Department of Computational Intelligence Czestochowa University of Technology Czestochowa42-201 Poland

Eye-tracking technology has long been a valuable tool across various domains, and recent advancements in neural networks have significantly expanded its versatility and potential. However, real-world applications continue to face challenges such as accommodating users’ natural movements, variations in lighting, occlusions of the eyes, and the limited availability of large, open-source datasets for training models. To address these issues, we developed a comprehensive pipeline that produces a lightweight and efficient model, requiring only an RGB camera as external hardware, making it easily deployable on standard PCs. Key input features include facial images, eye regions, head pose angles, the Eye Aspect Ratio (EAR), and a face grid that determines the face’s location within the camera’s frame. The model was trained using a custom dataset, in which participants were instructed to fixate on both randomly positioned points and the standard 9-point grid commonly employed in eye-tracking calibration. The resulting system was integrated into a real-time application, offering fast and accessible gaze tracking, making it well-suited for studies requiring rapid gaze assessments across broad regions of the screen, such as psychometric research and Human-computer Interaction (HCI) tasks. Its design is particularly advantageous for gaze laterality studies, which explore hemispheric dominance and attentional bias in cognitive and emotional processing, key concepts relevant to ADHD and dyslexia. Moreover, the system’s capabilities naturally extend to emotional and decision-making tasks, where broad-area gaze tracking can support the analysis of preference formation and attentional patterns without the need for specialized hardware. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Open systems

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A Hybrid Intelligence Model Forecasts the Temperature of a Battery Used in Electric Vehicles 21st

A Hybrid Intelligence Model Forecasts the Temperature of a...

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21st International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2024

作者： Rubiños, Manuel Arcano-Bea, Paula Díaz-Longueira, Antonio Michelena, Álvaro Vega, Rafael Vega Casteleiro-Roca, José-Luis Andújar, José Manuel CTC Department of Industrial Engineering CITIC University of A Coruña EPEF Calle Mendizábal s/n Campus de Esteiro A Coruña Ferrol15403 Spain Department of Electronic Engineering Computer Systems and Automatic University of Huelva Campus de El Carmen Huelva Huelva21071 Spain

ISBN: (纸本)9783031739095

Battery technology is advancing due to the requirement to store reliable energy in electric transportation systems and portable electronics devices. Assessing battery conditions and increasing the autonomy of electric vehicles requires to improve the behavior models. Prognosticating battery performance, nevertheless, is complex due to multiple variables, such as temperature, wear, and usage guidelines. Understanding battery performance requires a depth knowledge of, for example, time series analysis, above all forecasting. This research uses Artificial Neural Networks (ANN) modeled taking into account system dynamics, to create a Lithium Ion Battery (LIB) prediction model. Testing was performed with a 59.2 VDC, 120 Ah LIB, monitoring voltage, current and temperature while simulating charges and discharges. The model used is a hybrid type, which uses clustering to generate internal local models. This model predict the temperature development with very good results in terms of Mean Squared Error. From this research it is deduced that hybrid models are appropriate tools for prognostic battery performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Prediction models

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Stability and the Separation Principle in Output-Feedback Stochastic MPC with Random Packet Losses

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IFAC-PapersOnLine 2023年第2期56卷 3818-3823页

作者： Paul Trodden Paulo Loma-Marconi Iñaki Esnaola Department of Automatic Control & Systems Engineering University of Sheffield Sheffield S1 3JD UK

This paper considers a linear quadratic Gaussian (LQG) control problem with constraints on system inputs and random packet losses occurring on the communication channel between plant and controller. It is well known that, in the absence of constraints, the Separation Principle between estimator and controller holds when the channel employs a TCP-like protocol but not so under a UDP-like protocol. This paper gives a counterexample that shows that, under a model predictive control (MPC) scheme that handles the constraints, the Separation Principle does not hold even in the TCP-like case. Theoretical analysis characterizes and reveals a trade-off between estimation errors in the estimator and prediction errors in the controller. Counterintuitively, the poorer on-average performance of the estimator in the UDP case may be compensated by smaller prediction errors in the controller.

关键词： control and estimation with data loss Predictive control Kalman filtering Stochastic optimal control problems

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Analysis of YouTube Video Comments with NLP Methods 16

Analysis of YouTube Video Comments with NLP Methods

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16th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2024

作者： Mironela, Pirnau Iustin, Priescu Mihaela, Priescu Catalina Claudiu, Pirnau Daniel, Ghiculescu Liviu 'Titu Maiorescu' University Faculty of Informatics Department of Informatics Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Industrial Engineering and Robotics Manufacturing Engineering Department Bucharest Romania

ISBN: (纸本)9798350371154

This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They have become an important pillar in informal education, thus contributing to the rapid acquisition of skills and knowledge. Under these circumstances, we were interested in analysing the YouTube videos comments, knowing that the platform has a continuous increase in popularity, which is also due to the opportunities of sharing them. Since ChatGPT-themed YouTube videos have seen a significant surge in popularity since 2022, we were interested to analyse some videos that approach the topics of 'ChatGPT, AI clone, AI robot and Deep Learning.' © 2024 IEEE.

关键词： Deep learning

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Implementation of Justified Inspection Zone for Fault Location on Overhead Transmission Lines of 110 kV and Above

Implementation of Justified Inspection Zone for Fault Locati...

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International Youth Conference on Radio Electronics, Electrical and Power engineering (REEPE)

作者： Dmitriy Sharygin Galina Filatova Andrey Yablokov Department of electric power systems automatic control Ivanovo State Power Engineering University (ISPU) Ivanovo Russia

The existing normative and technical documentation of operating organizations does not allow for the reliable organization of the minimal possible inspection zone. The article presents research on the implementation of justified inspection zone for fault location on overhead transmission lines of 110 kV and above. The fault location research was carried out on an imitation model in the Simulink / MATLAB software package. Fault location formulae developed by the authors were used under consideration of multitude factors influencing the measurement using the Monte Carlo method. Only the methodological error of fault location was taken into account in the calculation for the implementation of the inspection zone. The most probable (justified) inspection zone was calculated based on the values of fault locations obtained using the calculation formulae. The generalized Gaussian distribution (GGD) and the functions of mathematical expectation and standard deviation were used to implement the justified inspection zone.

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A suite of MATLAB livescript files to support learning of elementary control and feedback concepts

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IFAC-PapersOnLine 2023年第2期56卷 7555-7560页

作者： J.A. Rossiter Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD UK

This paper builds on a body of work in the community which is focussed on sharing learning and teaching resources, especially those which might support a first course in control. Here attention is given to some of the mathematical, analytical and numerical computations which are required to support simple system and feedback analysis and design. The aim is to provide resources which allow students to focus on core concepts and understanding so that the numerical computations are not an obstacle to their investigations. More specifically, this paper focuses on a number of MATLAB livescript files which have been produced to help students visualise the impact of parameter and design choices on system behaviour, while simultaneously empowering them to understand the source code and thus upskill them for the future. The paper gives an overview of the livescripts available so users can decide whether these could be useful in their own context; all are freely available on the author's website (Rossiter, 2021).

关键词： Virtual laboratories independent learning visualisation livescripts

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Driver Behaviour Soft-Sensor based on Neurofuzzy systems and Weighted Projection on Principal Components

arXiv

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arXiv 2025年

作者： Escaño, Juan Manuel Ridao-Olivar, Miguel A. Ierardi, Carmelina Sánchez, Adolfo J. Rouzbehi, Kumars Department of Systems Engineering and Automatic Control Universidad de Sevilla Sevilla41092 Spain Department of Engineering Universidad Loyola Andalucía Sevilla41704 Spain

This work has as main objective the development of a soft-sensor to classify, in real time, the behaviors of drivers when they are at the controls of a vehicle. Efficient classification of drivers’ behavior while driving, using only the measurements of the sensors already incorporated in the vehicles and without the need to add extra hardware (smart phones, cameras, etc.), is a challenge. The main advantage of using only the data center signals of modern vehicles is economical. The classification of the driving behavior and the warning to the driver of dangerous behaviors without the need to add extra hardware (and their software) to the vehicle, would allow the direct integration of these classifiers into the current vehicles without incurring a greater cost in the manufacture of the vehicles and therefore be an added value. In this work, the classification is obtained based only on speed, acceleration and inertial measurements which are already present in many modern vehicles. The proposed algorithm is based on a structure made by several Neurofuzzy systems with the combination of projected data in components of various Principal Component Analysis. A comparison with several types of classical classifying algorithms has been made. © 2025, CC BY.

关键词： Smartphones

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Oligopoly Game Stabilisation Through Multilayer Congestion Dynamics

arXiv

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arXiv 2024年

作者： Willis, Toby Punzo, Giuliano Department of Automatic Control and Systems Engineering University of Sheffield Street South Yorkshire Sheffield100190 United Kingdom

International trade and logistics are subject to factors including geopolitical instability, climate change, and black swan events such as the unforeseen closure of the Suez Canal. The problem of predicting local price change under modification of an underlying transport network or change in supply characteristics unites elements of game theory, network theory and transport. The Cournot Oligopoly models economic actors as rational players attempting to maximise profit by optimising supply quantities with analytical results now consolidated about equilibrium characteristics where transport conditions are fixed. Similarly, where supply and demand are fixed, the routing of goods in a transport network can be analytically solved through a traffic assignment problem. Hence we can solve the coupled Cournot-congestion problem by means of a 2-layer network. Where the layers are linked, inter-layer feedback wherein players attempt to maximise their utility occurs. In this respect we find players benefit from taking advantage of non-simultaneous responses to the market rather than moving to a new equilibrium. We draw conclusions about the nature of equilibria, finding that the concave utility curve property results in unique and stable equilibrium for each uncoupled layer, while linked layers have a non-unique stable equilibria for which general solutions are stated. © 2024, CC BY.

关键词： International trade

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Network Intrusion Detection Based on Feature Selection and Hybrid Metaheuristic Optimization

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computers, Materials & Continua 2023年第2期74卷 2677-2693页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Manal Abdullah Alohali Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in IoT applications,have led to major security *** are on the rise as a result of the usage of these technologies since present security measures are *** artificial intelligence(AI)based security solutions,such as intrusion detection systems(IDS),have been proposed in recent *** technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection(FS)techniques to increase classification accuracy by minimizing the number of features *** the other hand,metaheuristic optimization algorithms have been widely used in feature selection in recent *** this paper,we proposed a hybrid optimization algorithm for feature selection in *** proposed algorithm is based on grey wolf(GW),and dipper throated optimization(DTO)algorithms and is referred to as *** proposed algorithm has a better balance between the exploration and exploitation steps of the optimization process and thus could achieve better *** the employed IoT-IDS dataset,the performance of the proposed GWDTO algorithm was assessed using a set of evaluation metrics and compared to other optimization approaches in 2678 CMC,2023,vol.74,no.2 the literature to validate its *** addition,a statistical analysis is performed to assess the stability and effectiveness of the proposed *** results confirmed the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.

关键词： Feature selection grey wolf optimization dipper throated optimization intrusion detection internet-of-things(IoT)

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