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Search results for: PARTIAL SHADING (PS) PARTICLE SWARM OPTIMIZATION (PSO) MAXIMUM POWER POINT TRACKING (MPPT) SWARM INTELLIGENCE (SI) DYNAMIC GROUP-BASED COOPERATIVE OPTIMIZATION (DGBCO) RELATIVE ERROR (RE)
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Highly efficient maximum power point tracking control technique for PV system under dynamic operating conditions
PublicationThe application of small-scale electrical systems is widespread and the integration of Maximum Power Point Tracking (MPPT) control for Photovoltaic systems with battery applications further enhances the techno-economic feasibility of renewable systems. For this purpose, a novel MPPT control system using Dynamic Group based cooperation optimization (DGBCO) algorithm is utilized for PV systems. The population in the DGBCO is divided...
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Modal parameters identification with Particle Swarm Optimization
PublicationThe paper presents method of the modal parameters identification based on the Particle Swarm Optimization (PSO) algorithm [1]. The basic PSO algorithm is modified in order to achieve fast convergence and low estimation error of identified parameters values. The procedure of identification as well as algorithm modifications are presented and some simple examples for the SISO systems are provided. Results are compared with the results...
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Spectrum-based modal parameters identification with Particle Swarm Optimization
PublicationThe paper presents the new method of the natural frequencies and damping identification based on the Artificial Intelligence (AI) Particle Swarm Optimization (PSO) algorithm. The identification is performed in the frequency domain. The algorithm performs two PSO-based steps and introduces some modifications in order to achieve quick convergence and low estimation error of the identified parameters’ values for multi-mode systems....
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A Salp-Swarm Optimization based MPPT technique for harvesting maximum energy from PV systems under partial shading conditions
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Estimation of structural stiffness with the use of Particle Swarm Optimization
PublicationThe paper presents the theoretical background and four applications examples of the new method for the estimation of support stiffness coefficients of complex structures modelled discretely (e.g. with the use of the Finite Element Model (FEM) method based on the modified Particle Swarm Optimization (PSO) algorithm. In real-life cases, exact values of the supports’ stiffness coefficients may change for various reasons...
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Modelling of Curvature of the Railway Track Geometrical Layout Using Particle Swarm Optimization
PublicationA method of railway track geometrical layout design, based on application of cubic C-Bezier curves for describing the layout curvature is presented in the article. The control points of a cubic C-Bezier curve are obtained in an optimization process carried out using Particle Swarm Optimization algorithm. The optimization criteria are based on the evaluation of the dynamic interactions and satisfaction of geometrical design requirements.
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Spectral measurement of birefringence using particle swarm optimization analysis
PublicationThe measurement of birefringence is useful for the examination of both technical and biological objects. One of the main problems is that the polarization state of light in birefringent media changes periodically. Without the knowledge of the period number, the birefringence of a given medium cannot be determined reliably. We propose to analyse the spectrum of light in order to determine the birefringence. We use a Particle Swarm...
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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
PublicationRecent research reveals that multi-phase motors in electric propulsion systems are highly recommended due to their improved reliability and efficiency over traditional three phase motors. This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). A six phase squirrel cage induction...
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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
PublicationAbstract: Recent research reveals that multi-phase motors in electric propulsion systems are highly recommended due to their improved reliability and efficiency over traditional three phase motors. This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). A six phase squirrel cage induction...
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Designing of Track Axis Alignment with the Use of Satellite Measurements and Particle Swarm Optimization
PublicationDesigning of the track’s alignment is a key issue from the point of view of maintaining of proper geometries. The paper presents a design method for sections of railway line located in the horizontal arch. The method is adapted to the technique of mobile satellite measurements. The general principles of this measurement method have been described in the article. A project's solution has been presented using mathematical notation...
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Testing Stability of Digital Filters Using Multimodal Particle Swarm Optimization with Phase Analysis
PublicationIn this paper, a novel meta-heuristic method for evaluation of digital filter stability is presented. The proposed method is very general because it allows one to evaluate stability of systems whose characteristic equations are not based on polynomials. The method combines an efficient evolutionary algorithm represented by the particle swarm optimization and the phase analysis of a complex function in the characteristic equation....
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Multimodal Particle Swarm Optimization with Phase Analysis to Solve Complex Equations of Electromagnetic Analysis
PublicationIn this paper, a new meta-heuristic method of finding roots and poles of a complex function of a complex variable is presented. The algorithm combines an efficient space exploration provided by the particle swarm optimization (PSO) and the classification of root and pole occurrences based on the phase analysis of the complex function. The method initially generates two uniformly distributed populations of particles on the complex...
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Swarm Algorithms in Modern Engineering Optimization Problems
PublicationComplexity of today engineering problems is constantly increasing. Scientists no longer are facing issues, for which simple, mathematical programming methods are sufficient. Issues like autonomic vehicle navigation or classification are considered to be challenging, and although there exist valid means to solve them, in some cases there still is some place for improvement. With emergence of a new type of optimization techniques...
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The Maximum Power Point Tracking (MPPT) of a Partially Shaded PV Array for Optimization Using the Antlion Algorithm
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Optimal Power Flow Problem Using Particle Swarm Optimization Algorithm
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Particle swarm optimization algorithms for autonomous robots with deterministic leaders using space filling movements
PublicationIn this work the swarm behavior principles of Craig W. Reynolds are combined with deterministic traits. This is done by using leaders with motions based on space filling curves like Peano and Hilbert. Our goal is to evaluate how the swarm of agents works with this approach, supposing the entire swarm will better explore the entire space. Therefore, we examine different combinations of Peano and Hilbert with the already known swarm...
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Example of Using Particle Swarm Optimization Algorithm with Nelder–Mead Method for Flow Improvement in Axial Last Stage of Gas–Steam Turbine
PublicationThis article focuses principally on the comparison baseline and the optimized flow efficiency of the final stage of an axial turbine operating on a gas–steam mixture by applying a hybrid Nelder– Mead and the particle swarm optimization method. Optimization algorithms are combined with CFD calculations to determine the flowpaths and thermodynamic parameters. The working fluid in this study is a mixture of steam and gas produced...
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Fuzzy Based Maximum Power Point Tracking (MPPT) Control System for Photovoltaic Power Generation System
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublicationIn the present scenario, air quality prediction (AQP) is a complex task due to high variability, volatility, and dynamic nature in space and time of particulates and pollutants. Recently, several nations have had poor air quality due to the high emission of particulate matter (PM2.5) that affects human health conditions, especially in urban areas. In this research, a new optimization-based regression model was implemented for effective...
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An Optimal Power Point Tracking Algorithm in a Solar PV Generation System
PublicationThe non-linearity in I-V characteristics of a PV panel requires to be operated at knee point to extract maximum power. In order to operate the panel at optimal point, maximum power point tracking (MPPT) algorithm is employed in the control structure. The main objective of MPP tracking is to keep the operation at knee point of I-V characteristics under varying condition of temperature and solar insolation. Under non uniform solar...
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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublicationIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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SPECTRAL-BASED MODAL PARAMETERS IDENTIFICATION WITH MULTIPLE PARTICLE SWARMS OPTIMIZATION
PublicationThe paper presents usage of a Particle Swarm Optimization [1] based algorithm for spectral-based modal parameters identification. The main algorithm consists of two groups of swarms, namely, scouts and helpers. For the first group additional penalizing process is provided to force separation of scouting swarms in frequency space. The swarms have an ability to communicate with each other. At first stage, each swarm focuses on a...
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Photovoltaic Maximum Power Point Technique based on Incremental Conductance (INCON) control algorithm
PublicationMaximum output power status can significantly improve the deployment rate of solar energy system. In order to get the maximum power output, issue of tracking maximum power point (MPP), reduced harmonics around MPP and improve efficiency of the solar power energy system, this paper presents the improved maximum power point tracking (MPPT) control...
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Improved maximum power point tracking algorithms by using numerical analysis techniques for photovoltaic systems
PublicationSolar photovoltaic (PV) panels generate optimal electricity when operating at the maximum power point (MPP). This study introduces a novel MPP tracking algorithm that leverages the numerical prowess of the predictor-corrector method, tailored to accommodate voltage and current fluctuations in PV panels resulting from variable environmental factors like solar irradiation and temperature. This paper delves into the intricate dynamics...
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Maximum Power Point Technique (MPPT) for PV System Based on Improved Pert and Observe (P&O) Method with PI Controller
PublicationPhotovoltaic power generation system has key rule in electricity production. Although, it is clean renewable energy with unlimited resources but it has some drawbacks in efficiency. In order to maximize the efficiency, PV array must drive at maximum power point. For the reason so, several algorithms are used in PV system to track MPP and reduce the...
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Interior Point Method Evaluation for Reactive Power Flow Optimization in the Power System
PublicationThe paper verifies the performance of an interior point method in reactive power flow optimization in the power system. The study was conducted on a 28 node CIGRE system, using the interior point method optimization procedures implemented in Power Factory software.
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Maximizing the output power of magnetically geared generator in low-speed applications using subdomain modeling and particle swarm optimization
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Swarm-Assisted Investment Planning of a Bioethanol Plant
PublicationBioethanol is a liquid fuel for which a significant increase in the share of energy sources has been observed in the economies of many countries. The most significant factor in popularizing bioethanol is the profitability of investments in construction of facilities producing this energy source, as well as the profitability of its supply chain. With the market filled with a large amount of equipment used in the bioethanol production...
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Efficient Simulation-Based Global Antenna Optimization Using Characteristic Point Method and Nature-Inspired Metaheuristics
PublicationAntenna structures are designed nowadays to fulfil rigorous demands, including multi-band operation, where the center frequencies need to be precisely allocated at the assumed targets while improving other features, such as impedance matching. Achieving this requires simultaneous optimization of antenna geometry parameters. When considering multimodal problems or if a reasonable initial design is not at hand, one needs to rely...
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Particle swarm optimization–artificial neural network modeling and optimization of leachable zinc from flour samples by miniaturized homogenous liquid–liquid microextraction
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Computer-Aided System for Layout of Fire Hydrants on Boards Designed Vessel Using the Particle Swarm Optimization Algorithm
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublicationThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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Novel MPPT techniques for photovoltaic systems under uniform irradiance and Partial shading
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Example of Using Particle Swarm Optimization Algorithm with Nelder–Mead Method for Flow Improvement in Axial Last Stage of Gas–Steam Turbine
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Point cloud unification with optimization algorithm
PublicationTerrestrial laser scanning is a technology that enables to obtain three-dimensional data – an accurate representation of reality. During scanning not only desired objects are measured, but also a lot of additional elements. Therefore, unnecessary data is being removed, what has an impact on efficiency of point cloud processing. It can happen while single point clouds are displayed – user decides what he wants...
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Virtual spring damper method for nonholonomic robotic swarm self-organization and leader following
PublicationIn this paper, we demonstrate a method for self-organization and leader following of nonholonomic robotic swarm based on spring damper mesh. By self-organization of swarm robots we mean the emergence of order in a swarm as the result of interactions among the single robots. In other words the self-organization of swarm robots mimics some natural behavior of social animals like ants among others. The dynamics of two-wheel robot...
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Model Management for Low-Computational-Budget Simulation-Based Optimization of Antenna Structures Using Nature-Inspired Algorithms
PublicationThe primary objective of this study is investigation of the possibilities of accelerating nature-inspired optimization of antenna structures using multi-fidelity EM simulation models. The primary methodology developed to achieve acceleration is a model management scheme which the level of EM simulation fidelity using two criteria: the convergence status of the optimization algorithm, and relative quality of the individual designs...
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Impact of optimization of ALS point cloud on classification
PublicationAirborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...
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Adjusting the Stiffness of Supports during Milling of a Large-Size Workpiece Using the Salp Swarm Algorithm
PublicationThis paper concerns the problem of vibration reduction during milling. For this purpose, it is proposed that the standard supports of the workpiece be replaced with adjustable stiffness supports. This affects the modal parameters of the whole system, i.e., object and its supports, which is essential from the point of view of the relative tool–workpiece vibrations. To reduce the vibration level during milling, it is necessary to...
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An optimized system for sensor ontology meta-matching using swarm intelligent algorithm
PublicationIt is beneficial to annotate sensor data with distinct sensor ontologies in order to facilitate interoperability among different sensor systems. However, for this interoperability to be possible, comparable sensor ontologies are required since it is essential to make meaningful links between relevant sensor data. Swarm Intelligent Algorithms (SIAs), namely the Beetle Swarm Optimisation Algorithm (BSO), present a possible answer...
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Ship weather routing optimization with dynamic constraints based on reliable synchronous roll prediction
PublicationShip routing process taking into account weather conditions is a constrained multi-objective optimization problem and it should consider various optimization criteria and constraints. Formulation of a stability-related, dynamic route optimization constraint is presented in this paper. One of the key objectives of a cross ocean sailing is finding a compromise between ship safety and economics of operation. This compromise should...
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Optimization of the Relative Humidity of Reactant Gases in Hydrogen Fuel Cells Using Dynamic Impedance Measurements
PublicationWater management is a key factor affecting the efficiency of proton exchange membrane fuel cells (PEMFCs). The currently used monitoring methods of PEMFCs provide limited information about which processes or components that humidity has a significant impact upon. Herein, we propose the use of a novel approach of impedance measurements using a multi-sinusoidal perturbation signal, which enables impedance measurements under dynamic...
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Low-Cost and Precise Automated Re-Design of Antenna Structures Using Interleaved Geometry Scaling and Gradient-Based Optimization
PublicationDesign of contemporary antennas is an intricate endeavor involving multiple stages, among others, tuning of geometry parameters. In particular, re-designing antennas to different operating frequencies, makes parametric optimization imperative to ensure the best achievable system performance. If the center frequency at the current design is distant from the target one, local tuning methods generally fail, whereas global algorithms...
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Voltage and Reactive Power Load Flow Optimization in the Power System Using Fuzzy Logic
PublicationThe paper presents issues related to voltage control in the power system. An original method of reactive power flow optimization is considered, which leads to improved voltages in the power system and reduced active power losses. The optimization method is based on a procedure that employs fuzzy logic and is supported by a gradient search algorithm. The method has been implemented in PLANS software and verified.
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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublicationEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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Aerodynamic Shape Optimization for Delaying Dynamic Stall of Airfoils by Regression Kriging
PublicationThe phenomenon of dynamic stall produce adverse aerodynamic loading which can adversely affect the structural strength and life of aerodynamic systems. Aerodynamic shape optimization (ASO) provides an effective approach for delaying and mitigating dynamic stall characteristics without the addition of auxiliary system. ASO, however, requires multiple evaluations time-consuming computational fluid dynamics models. Metamodel-based...
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A Reference Point Approach to Bi-Objective Dynamic Portfolio Optimization
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Green energy extraction for sustainable development: A novel MPPT technique for hybrid PV-TEG system
PublicationThe Photovoltaic (PV) module converts only a small portion of irradiance into electrical energy. Most of the solar energy is wasted as heat, resulting in a rise in PV cell temperature and a decrease in solar cell efficiency. One way to harvest this freely available solar thermal energy and improve PV cell efficiency is by integrating PV systems with thermoelectric generators (TEG). This cogeneration approach of the hybrid PV-TEG...
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Expedited Feature-Based Quasi-Global Optimization of Multi-Band Antenna Input Characteristics with Jacobian Variability Tracking
PublicationDesign of modern antennas relies—for reliability reasons—on full-wave electromagnetic simulation tools. In addition, increasingly stringent specifications pertaining to electrical and field performance, growing complexity of antenna topologies, along with the necessity for handling multiple objectives, make numerical optimization of antenna geometry parameters a highly recommended design procedure. Conventional algorithms, particularly...
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Expedited Metaheuristic-Based Antenna Optimization Using EM Model Resolution Management
PublicationDesign of modern antenna systems heavily relies on numerical opti-mization methods. Their primary purpose is performance improvement by tun-ing of geometry and material parameters of the antenna under study. For relia-bility, the process has to be conducted using full-wave electromagnetic (EM) simulation models, which are associated with sizable computational expendi-tures. The problem is aggravated in the case of global optimization,...