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Data-Driven Evolutionary Algorithms for Optimizing Pumping Stations in Water Distribution Networks: Classifier-Guided Search Space Reduction 27th

Data-Driven Evolutionary Algorithms for Optimizing Pumping S...

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27th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, computer Vision, and Applications, CIARP 2024

作者： Faúndez-Lizama, Thalía Gajardo-Sepúlveda, Nicolás Gutiérrez-Bahamondes, Jimmy H. Mora-Melia, Daniel Astudillo, César A. Master’s in Operations Management Faculty of Engineering Universidad de Talca Curicó3340000 Chile Department of Computer Science Faculty of Engineering Universidad de Talca Curicó3340000 Chile Department of Engineering and Construction Management Faculty of Engineering Universidad de Talca Curicó3340000 Chile

ISBN: (纸本)9783031766060

In the context of increasing water scarcity and the need to enhance water distribution network efficiency, this study focuses on optimizing the design of pumping stations using data-driven evolutionary algorithms guided by classification models. These facilities are critical components in water networks due to their high energy consumption and role in maintaining necessary water pressure. The proposed approach integrates a machine learning classifier model within the evolutionary process to pre-label solutions as feasible or infeasible, thereby reducing search space and computational costs associated with hydraulic simulations. Classification models include support vector classifier, artificial neural networks, and random forest. These models are trained on data generated from initial evolutionary optimization, enabling the classifier to predict the viability of new solutions. Results show that all tested classification models reduced the number of objective function evaluations and consequently, required hydraulic simulations. In some cases, the optimal solution defined by the original method was improved, demonstrating dual benefits by reducing both cost and computational effort. This work highlights that data-driven evolutionary optimization can effectively tackle highly complex problems, offering potential future applications in other areas of civil engineering and water resource management. Implementing this methodology promises significant time and resource savings in large-scale optimization processes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Hydraulic models

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PlantCare AI: An AI based Solution for Plant Disease Diagnosis and Assistance 6

PlantCare AI: An AI based Solution for Plant Disease Diagnos...

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6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Ghogare, Snehal Dhupe, Shivkanya Kulkarni, Abhijit Shingane, Tanish Gound, Renuka Department of Computer Science and Business Systems JSPM’s Rajarshi Shahu College of Engineering Tathawade Maharashtra Pune India

ISBN: (纸本)9798331522667

The advancement of Artificial Intelligence (AI) and machine learning (ML) has introduced trans- formative solutions in plant care. This review investigates the integration of deep learning and image recognition technologies for identifying and managing plant diseases. The proposed project focuses on developing a user-centric web application designed to detect plant diseases automatically, provide treatment recommendations, suggest nearby nurseries for obtaining necessary supplies, and offer chatbot assistance for user inquiries. Leveraging advanced image recognition techniques, this system aims to make plant care more efficient and accessible. The integration of Google Maps enhances navigation to local nurseries, further simplifying access to resources and promoting better plant care practices. This study outlines current methodologies, explores challenges and opportunities, and proposes a structured framework for creating an intelligent plant care platform to meet the evolving demands of farmers and horticulture professionals. © 2025 IEEE.

关键词： Convolutional neural networks

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Efficient One-Stage Deep Learning for Text Detection in Scene Images

EEA - Electrotehnica, Electronica, Automatica

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EEA - Electrotehnica, Electronica, Automatica 2024年第4期72卷 65-71页

作者： Tibermacine, Ahmed Guettala, Walid Tibermacine, Imad Eddine Faculty of Exact Sciences Natural And Life Sciences University Mohamed Khider of Biskra Algeria Computer Science Department University Mohamed Khider of Biskra Algeria Department of Computer Automation and Management Engineering Sapienza University of Rome Italy

Text detection in natural images is a crucial task for extracting and recognizing valuable information, but it comes with significant challenges. Traditional image processing methods often rely on synthetic features, which may not be suitable for handling the diverse range of unstructured text scenarios encountered in real-world environments. To overcome this challenge, deep learning techniques have emerged as a powerful tool for adaptively learning and extracting features to digitize text. In this paper, we introduce a novel approach based on the YOLOv5 architecture for text detection. Our method leverages the strengths of YOLOv5, including its efficient and lightweight architecture, multi-scale prediction capability, and advanced data augmentation techniques. By employing these features, our proposed model can accurately identify regions in an image that are more likely to contain text. Through extensive experimentation on popular benchmark datasets, we have evaluated the performance of our proposed model. The results have demonstrated that our method outperforms state-of-the-art approaches in terms of both detection efficiency and accuracy. This indicates the effectiveness of our approach in handling the challenges posed by text detection in natural images. © Editura ELECTRA 2024. All rights reserved.

关键词： Deep Learning Natural scene image Text detection Yolov5

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Modernizing The Shopping Experience: The Smart Shopping Cart 6

Modernizing The Shopping Experience: The Smart Shopping Cart

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6th Iraqi International Conference on engineering Technology and its Applications, IICETA 2023

作者： Shakir, Aboothar Mahmood Mudhafar, Yousif Al-Muqarm, Abbas M. Ali The Islamic University College of Technical Engineering Computer Techniques Engineering Department Najaf Iraq University of Kufa Faculty of Computer Science and Mathematics Department of Computer Science Najaf Iraq

ISBN: (纸本)9798350303339

The holiday season brings out the crowds at shopping centers in major cities. When there are substantial savings to be obtained, this becomes even more true. People today often fill their shopping carts with a wide selection of products. Once a customer has finished shopping, he or she should head to the counter to settle the payment. It takes time for the cashier to create the bill using a barcode scanner. Because of this, there are often substantial wait times at the cash registers. This project proposes a solution for retail centers to address the issues mentioned above. This might be accomplished by installing RFID tags on all mall merchandise and retrofitting all shopping carts with a radio-frequency identification reader and a liquid crystal display. Any item placed in the shopping cart will have its barcode scanned automatically, and the trolley's digital signboard will update to show the item's name and price. When an item is removed from a shopping cart, its cost is subtracted from the grand total, and the relevant data is transmitted to the central billing unit through radio-frequency (RF) modules. Customers may save a ton of time since billing can be done right on the tram. The researchers worked on developing a shopping cart, which is smart, and this system allows for faster checkout and payment of the bill in a secure manner, and the adoption of technology in the store increases the demand for it continuously, the computer will remember the barcode data you enter and compare it to its database, from which it will get the necessary data. The database and RF model will be connected through software. Small radio-frequency (RF) electrical modules called a 'transmitter' and 'receiver' can be used to transmit and receive signals between any two devices. The data is sent from the transmitter module to the receiver module, which then processes the data. The group believes that the intelligent shopping cart will result in a more dependable checkout procedure and

关键词： Liquid crystal displays

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Accelerating Gradient Tracking with Periodic Global Averaging 63

Accelerating Gradient Tracking with Periodic Global Averagin...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Feng, Shujing Jiang, Xin Lehigh University Department of Computer Science and Engineering BethlehemPA United States Lehigh Univeristy Department of Industrial and Systems Engineering BethlehemPA United States

ISBN: (纸本)9798350316339

Decentralized optimization algorithms have recently attracted increasing attention due to its wide applications in all areas of science and engineering. In these algorithms, a collection of agents collaborate to minimize the average of a set of heterogeneous cost functions in a decentralized manner. State-of-the-art decentralized algorithms like Gradient Tracking (GT) and Exact Diffusion (ED) involve communication at each iteration. Yet, communication between agents is often expensive, resource intensive, and can be very slow. To this end, several strategies have been developed to balance between communication overhead and convergence rate of decentralized methods. In this paper, we introduce GT-PGA, which incorporates GT with periodic global averaging. With the additional PGA, the influence of poor network connectivity in the GT algorithm can be compensated or controlled by a careful selection of the global averaging period. Under the stochastic, nonconvex setup, our analysis quantifies the crucial trade-off between the connectivity of network topology and the PGA period. Thus, with a suitable design of the PGA period, GT-PGA improves the convergence rate of vanilla GT. Numerical experiments are conducted to support our theory, and simulation results reveal that the proposed GT-PGA accelerates practical convergence, especially when the network is sparse. © 2024 IEEE.

关键词： Cost functions

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Data-Driven Genetic Algorithm for the Optimization of Water Distribution Networks: A New Surrogate Model for Estimating Investment and Operational Costs in Pumping Stations 27th

Data-Driven Genetic Algorithm for the Optimization of Water ...

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27th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, computer Vision, and Applications, CIARP 2024

作者： Gajardo-Sepúlveda, Nicolás Faúndez-Lizama, Thalía Gutiérrez-Bahamondes, Jimmy H. Mora-Melia, Daniel Astudillo, César A. Master’s in Operations Management Faculty of Engineering Universidad de Talca Curicó3340000 Chile Department of Computer Science Faculty of Engineering Universidad de Talca Curicó3340000 Chile Department of Engineering and Construction Management Faculty of Engineering Universidad de Talca Curicó3340000 Chile

ISBN: (纸本)9783031766039

The increase in water consumption and demand has highlighted the need to improve the efficiency of water distribution networks (WDNs). Pumping stations (PS) represent a significant challenge due to their high energy consumption and associated operational costs. This study presents a data-driven evolutionary optimization methodology focused on predicting cost and penalties in the design and operation of PS. The methodology integrates the functioning of genetic algorithms with machine learning techniques, developing a surrogate model capable of predicting associated costs and increasing the computational efficiency of optimization models. A case study is presented to validate the methodology, showing a significant reduction of 31.8% in evaluation times and a decrease in optimization time compared to traditional models. The results indicated that despite the reduction in computational effort, the increase in the final cost of the network was minimal, with only a 2.42% increase compared to the baseline model. These findings underscore the effectiveness of combining machine learning with genetic algorithms for the optimization of PS in WDNs, improving computational efficiency while maintaining high standards in solution quality. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Genetic algorithms

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Functional Verification of Extended Kalman Filter on FPGA for Railway Wheelset Parameters Estimation

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IEEE Access 2025年 13卷 96646-96659页

作者： Mal, Khakoo Memon, Tayab Din Kalwar, Imtiaz Hussain Junejo, Allah Rakhio Memon, Majid Hussain Memon, Tarique Rafique Memon, Sufyan Ali Chowdhry, Bhawani Shankar Sukkur IBA University Sukkur65200 Pakistan Mehran University of Engineering & Technology NCRA-Condition Monitoring Systems Lab Jamshoro76062 Pakistan Torrens University Center for Artificial Intelligence Research and Optimization Faculty of Design and Creative Technology Melbourne Australia Iqra University Faculty of Engineering Sciences and Technology Karachi75500 Pakistan Iqra University Department of Artificial Intelligence Karachi75500 Pakistan Department of Electronic Engineering Quaid-e-Awam University of Engineering Science and Technology Nawabshah67450 Pakistan Department of Defense Systems Engineering Sejong University Seoul Korea Republic of

The forces generated at the wheel-rail contact patch are important and crucial to the railway vehicle's operation because they control the dynamic behavior of the entire rolling stock. The transfer of the tractive force applied by the locomotive's traction and braking system requires a certain amount of adhesion force at the wheel-rail contact area. The wheel may skid while decelerating and slip when accelerating due to the maximal adhesion force at the wheel-rail interface may be less than the applied tractive force. A major difficulty is accurately estimating adhesion conditions and implementing them in real time because the contact forces between the wheel and rail are complicated and are highly non-linear. The fast-processing speed and hardware flexibility of field programmable gate arrays (FPGAs) make them ideal for the implementation of nonlinear condition monitoring systems. The goal of our work is to estimate various railway wheelset characteristics relating to wheel-rail contact forces under variable track-contact situations by designing and implementing the extended Kalman filter (EKF) model utilizing MATLAB and FPGA. The onboard estimation of wheel-rail interaction parameters is verified using the Xilinx® System-On-Chip (SoC) Zynq and Xilinx Spartan-3 FPGA devices, built-in with the National Instruments (NI) myRIO® development board and sbRIO® single-board controller. Two FPGA platforms are used to test the dataset generated by the MATLAB railway nonlinear wheelset model under different track circumstances, which include the vehicle's acceleration and deceleration modes. The 95% of the simulation results achieved. The proposed model's hardware synthesizes on FPGA are validated, and the area-performance is analyzed. Both FPGA devices take 52 cycles per sample and hence throughput becomes 769 kilo samples per second. Comparing the Xilinx System-On-Chip Zynq FPGA device to the Spartan-3, it is found that the latter offers a worse area-performance tradeoff fo

关键词： Extended Kalman filters

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Enhancing the Efficiency of Navigation systems: Dijkstra Algorithm Optimization Through Integration of Douglas-Peucker Line Simplification Technique 23

Enhancing the Efficiency of Navigation Systems: Dijkstra Alg...

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8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Haq, Muhammad Yasir Anshari Sianturi, Riswan Septriayadi Pinandito, Aryo Informatics Engineering Department Universitas Brawijaya Faculty of Computer Science Indonesia Information System Department Universitas Brawijaya Faculty of Computer Science Indonesia

ISBN: (纸本)9798400708503

Smartphones have grown popular in the current digital era among people. Map-based applications are one of many that are used daily by people to acquire information about specific locations. Google Maps and Waze are two popular examples of map-based applications for travel and navigation, as they provide detailed information while the user navigates from one point to another. One of the most commonly used algorithms in map-based applications is the Dijkstra algorithm. Although the Dijkstra algorithm can determine the shortest route between two points, there is an issue when the selected route involves a large number of data points that need to be processed. The more data points involved, the longer it takes to do a route calculation in the Dijkstra algorithm. This can lead to a degradation in system performance, especially on smartphones with limited resources. To address this issue, the Douglas-Peucker algorithm is proposed as a solution to reduce the number of points involved in the calculation using the line simplification technique. Line simplification means reducing unnecessary points that are considered unimportant. This study suggested that integrating the Douglas-Peucker line simplification technique before Dijkstra could improve the system performance more than the system without integrating line simplification in terms of reducing both memory usage and the time required to compute the solution. © 2023 ACM.

关键词： Navigation systems

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Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

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computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： Asifa Mehmood Qureshi Naif Al Mudawi Mohammed Alonazi Samia Allaoua Chelloug Jeongmin Park Department of Creative Technologies Air UniversityIslamabad46000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection SIFT VAID

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Semi-analytical finite element method applied for characterizing micropolar fibrous composites

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Applied Mathematics and Mechanics(English Edition) 2024年第12期45卷 2147-2164页

作者： J.A.OTERO Y.ESPINOSA-ALMEYDA R.RODRIGUEZ-RAMOS J.MERODIO School of Engineering and Sciences Monterrey Institute of TechnologyEstado de Mexico 52926Mexico Institute of Engineering and Technology Autonomous University of Ciudad JuarezCiudad JuarezChihuahua 32310Mexico Postgraduate Program in Computational Modeling in Science and Technology Federal Fluminense UniversityRıo de Janeiro 27255-125Brazil Faculty of Mathematics and Computer Science University of HavanaLa Habana 10400Cuba Department of Mathematics Applied to ICT School of Informatics Systems EngineeringTechnical University of MadridMadrid 28031Spain

A semi-analytical finite element method(SAFEM),based on the two-scale asymptotic homogenization method(AHM)and the finite element method(FEM),is implemented to obtain the effective properties of two-phase fiber-reinforced composites(FRCs).The fibers are periodically distributed and unidirectionally aligned in a homogeneous *** framework addresses the static linear elastic micropolar problem through partial differential equations,subject to boundary conditions and perfect interface contact *** mathematical formulation of the local problems and the effective coefficients are presented by the *** local problems obtained from the AHM are solved by the FEM,which is denoted as the *** numerical results are provided,and the accuracy of the solutions is analyzed,indicating that the formulas and results obtained with the SAFEM may serve as the reference points for validating the outcomes of experimental and numerical computations.

关键词： semi-analytical approach fiber-reinforced composite(FRC) effective property finite element method(FEM) asymptotic homogenization method(AHM) micropolar elasticity

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