検索結果 - Particle swarm optimization algorithm*

Autonomous Mobility (AM) is the next milestone in the history of the automotive industry. Radar, lidar, cameras, ultrasonic, and other sensor units provide the required information for highly automated driving and pave the way for AM. This popular and fast-developing technology aims to increase vehi...

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This article explores an intelligent and equitable approach to collective and participatory irrigation for small farmers, with an emphasis on the democratization of water use. It examines how this equitable irrigation approach can contribute to the social economy by improving irrigation efficiency a...

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The K-Means algorithm is a popular unsupervised learning method used for data clustering. However, its performance heavily depends on centroid initialization and the distribution shape of the data, making it less effective for datasets with complex or non-linear cluster structures. This study evalua...

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In recent years, Convolutional Neural Networks (CNNs) have emerged as powerful tools for solving complex real-world problems, particularly in the domain of image processing. The success of CNNs can be attributed to their ability to learn hierarchical representations from data. However, achieving opt...

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COVID-19, one of the most dangerous pandemics, is currently affecting humanity. COVID-19 is spreading rapidly due to its high reliability transmissibility. Patients who test positive more often have mild to severe symptoms such as a cough, fever, raw throat, and muscle aches. Diseased people experie...

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This paper presents a global optimization algorithm specifically tailored for ultra-compact aspherical lens design problems for extended LED sources. The main purpose is to obtain prescribed illumination patterns, particularly the uniform illuminance distribution. This method begins by calculating t...

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The default Kubernetes scheduling algorithm, Balanced Resource Allocation (BRA), has limitations in achieving resource balance. It primarily focuses on the instantaneous utilization of CPU and memory while neglecting the coordinated optimization of disk I/O and network bandwidth, resulting in an imb...

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The purpose of the paper is the investigation of the modern approaches and prospects for the application of swarm intelligence algorithms for educational data analysis, as well as the possibility of using of ant algorithm modifications for organizing educational content in adaptive systems for condu...

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This paper examines strategies aimed at improving search procedures in multimodal, low-dimensional domains. Here, <i>low-dimensional domains</i> refers to a maximum of five dimensions. The present analysis assembles strategies to form an algorithm named S-EPSO, which, at its core, locate...

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ABSTRACT The amount of power produced by a solar panel depends on the intensity of radiation and surrounding temperature. Optimizing the performance of photovoltaic systems requires the operation of solar panels at the maximum power point (MPP). In the present paper, a novel maximum power point trac...

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This paper proposes a combined optimization method for multi-period empty container repositioning and inventory control based on adaptive particle swarm optimization (APSO) algorithm, which addresses the limitations of existing research, such as decoupling empty container repositioning and inventory...

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This work presents a design approach of multi-segment directional couplers with ultra-broadband flat spectra and benign fabrication tolerance on the silicon nitride platform. Using particle swarm optimization, we optimize design parameters of multiple coupling regions and asymmetric decoupling regio...

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Decision trees in machine learning achieved satisfactory performance in classification. Decision trees offer the advantage of handling high-dimensional and complexly correlated data through feature combination and selection. Extreme Gradient Boosting (XGBoost) overcomes the issue of overfitting in d...

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In this modern era cloud computing and widespread use of it have led to a massive spike in users' requests. The infrastructure's resources would either not be able to handle the increased volume of traffic or the scenario would lead to some resources being over or underutilized. Due to th...

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We present a method for 3D gravity inversion using ellipsoidal parametrization and Particle Swarm Optimization (PSO), aimed at estimating the geometry, density contrast, and orientation of subsurface bodies from gravity anomaly data. The subsurface is modeled as a set of prolate ellipsoids whose par...

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This paper presents a digital twin-driven multi-objective optimization approach for enhancing the performance and productivity of a multi-product manufacturing system under complex operational challenges. More specifically, the concept of digital twin is applied to virtually replicate a physical sys...

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Computers are often used when problems are big or hard to solve. However, traditional ways to find solutions are not enough when problems are very serious. Hence, turning to nature may be the answer to find solutions for these problems. Artificial intelligence tries to simulate creatures and activi...

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This study focuses on optimizing two tandem columns to separate ethylbenzene and styrene. A steady-state model is developed to minimize total energy consumption (TEC) and total annualized cost (TAC) by optimizing the reflux flow rates. An integrated dynamic model is created using the Multi-Objective...

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The physical problem of element yield inversion is transformed into a mathematical problem of solving overdetermined equations, then the particle swarm optimization algorithm is used to find the optimal solution of the system of equations to obtain the yield of formation elements. During th...

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