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Wyniki wyszukiwania dla: REINFORCED SWARM OPTIMIZATION ALGORITHM
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Optimal Power Flow Problem Using Particle Swarm Optimization Algorithm
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublikacjaIn 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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Computer-Aided System for Layout of Fire Hydrants on Boards Designed Vessel Using the Particle Swarm Optimization Algorithm
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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
PublikacjaThis 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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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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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublikacjaIn 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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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublikacjaEfficient 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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ESTYMACJA WSPÓŁCZYNNIKÓW SZTYWNOŚCI ZAMOCOWANIA PODATNEGO PRZEDMIOTU OBRABIANEGO NA STOLE FREZARKI
PublikacjaW pracy przedstawiono metodę estymacji współczynników sztywności Elementów Sprężystych (ES) modelujących zamocowanie podatnego wielkogabarytowego przedmiotu obrabianego na stole frezarki. Proponowana metoda bazuje na algorytmie optymizacji za pomocą roju cząstek (ang. Particle Swarm Optimization), który pozwala na uzyskanie dobrej zgodności (aktualizacji) modelu Metody Elementów Skończonych (MES) z modelem pochodzącym z identyfikacji...
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Projektowanie układów geometrycznych toru z zastosowaniem optymalizacji wielokryterialnej
PublikacjaW pracy przedstawiono metodę projektowania odcinków trasy kolejowej położonych w łuku, dostosowaną do techniki mobilnych pomiarów satelitarnych. Rozwiązanie problemu projektowego wykorzystuje zapis matematyczny i polega na wyznaczeniu uniwersalnych równań opisujących całość układu geometrycznego. Odbywa się to sekwencyjnie, obejmując kolejne fragmenty tegoż układu. Procedura projektowania ma charakter uniwersalny, gdyż w ogólnym...
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Metody zwiększania dostępności i efektywności informatycznej infrastruktury w inteligentnym mieście
PublikacjaW pracy omówiono metody zwiększania dostępności i efektywności informatycznej infrastruktury w inteligentnym mieście. Sformułowano dwa kryteria do oceny rozmieszczenia kluczowych zasobów w systemie smart city. Zobrazowano proces wyznaczania rozwiązań kompromisowych spośród rozwiązań Pareto-optymalnych. Omówiono metaheurystyki inteligencji zbiorowej, w tym roju cząstek, kolonii mrówek, roju pszczół oraz ewolucji różnicowej, za pomocą...
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Modal parameters identification with Particle Swarm Optimization
PublikacjaThe 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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Uniwersalna metoda projektowania regulacji osi toru z wykorzystaniem pomiarów satelitarnych i optymalizacji
PublikacjaW pracy zwrócono uwagę na ograniczenia stosowanej w naszym kraju metodyki regulacji osi toru związane w głównym stopniu z uzyskiwaną dokładnością określania istniejącego kształtu toru. Jako rozwiązanie alternatywne wskazano opracowaną przez interdyscyplinarny zespół naukowy Politechniki Gdańskiej i Akademii Marynarki Wojennej / Akademii Morskiej w Gdyni i stosowaną od 2009 roku nowatorską technikę mobilnych pomiarów satelitarnych....
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Optymalizacja zasobów chmury obliczeniowej z wykorzystaniem inteligentnych agentów w zdalnym nauczaniu
PublikacjaRozprawa dotyczy optymalizacji zasobów chmury obliczeniowej, w której zastosowano inteligentne agenty w zdalnym nauczaniu. Zagadnienie jest istotne w edukacji, gdzie wykorzystuje się nowoczesne technologie, takie jak Internet Rzeczy, rozszerzoną i wirtualną rzeczywistość oraz deep learning w środowisku chmury obliczeniowej. Zagadnienie jest istotne również w sytuacji, gdy pandemia wymusza stosowanie zdalnego nauczania na dużą skalę...
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Swarm Algorithms in Modern Engineering Optimization Problems
PublikacjaComplexity 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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Modelling of Curvature of the Railway Track Geometrical Layout Using Particle Swarm Optimization
PublikacjaA 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
PublikacjaThe 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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Spectrum-based modal parameters identification with Particle Swarm Optimization
PublikacjaThe 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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Estimation of structural stiffness with the use of Particle Swarm Optimization
PublikacjaThe 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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Testing Stability of Digital Filters Using Multimodal Particle Swarm Optimization with Phase Analysis
PublikacjaIn 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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An optimized system for sensor ontology meta-matching using swarm intelligent algorithm
PublikacjaIt 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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Designing of Track Axis Alignment with the Use of Satellite Measurements and Particle Swarm Optimization
PublikacjaDesigning 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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Multimodal Particle Swarm Optimization with Phase Analysis to Solve Complex Equations of Electromagnetic Analysis
PublikacjaIn 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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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
PublikacjaRecent 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
PublikacjaAbstract: 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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Point cloud unification with optimization algorithm
PublikacjaTerrestrial 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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Adjusting the Stiffness of Supports during Milling of a Large-Size Workpiece Using the Salp Swarm Algorithm
PublikacjaThis 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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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublikacjaIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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Arterial cannula shape optimization by means of the rotational firefly algorithm
PublikacjaThe article presents global optimization results of arterial cannula shapes by means of the newly modified firefly algorithm. The search for the optimal arterial cannula shape is necessary in order to minimize losses and prepare the flow that leaves the circulatory support system of a ventricle (i.e. blood pump) before it reaches the heart. A modification of the standard firefly algorithm, the so-called rotational firefly algorithm,...
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Numerically efficient algorithm for compact microwave device optimization with flexible sensitivity updating scheme
PublikacjaAn efficient trust-region algorithm with flexible sensitivity updating management scheme for electromagnetic (EM)-driven design optimization of compact microwave components is proposed. During the optimization process, updating of selected columns of the circuit response Jacobian is performed using a rank-one Broyden formula (BF) replacing finite differentiation (FD). The FD update is omitted for directions sufficiently well aligned...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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Collision‐Aware Routing Using Multi‐Objective Seagull Optimization Algorithm for WSN‐Based IoT
PublikacjaIn recent trends, wireless sensor networks (WSNs) have become popular because of their cost, simple structure, reliability, and developments in the communication field. The Internet of Things (IoT) refers to the interconnection of everyday objects and sharing of information through the Internet. Congestion in networks leads to transmission delays and packet loss and causes wastage of time and energy on recovery. The routing protocols...
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Pareto Ranking Bisection Algorithm for Expedited Multi-Objective Optimization of Antenna Structures
PublikacjaThe purpose of this letter is introduction of a novel methodology for expedited multi-objective design of antenna structures. The key component of the presented approach is fast identification of the initial representation of the Pareto front (i.e., a set of design representing the best possible trade-offs between conflicting objectives) using a Pareto-ranking bisection algorithm. The algorithm finds a discrete set of Pareto-optimal...
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A Multi-Fidelity Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Optimization Problems
PublikacjaIntegrating data-driven surrogate models and simulation models of different accuracies (or fideli-ties) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple fidelities in global optimization is a major challenge. To address it, the two major contributions of this paper include:...
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Low-Cost Multi-Objective Optimization of Antennas By Means Of Generalized Pareto Ranking Bisection Algorithm
PublikacjaThis paper introduces a generalized Pareto ranking bisection algorithm for low-cost multi-objective design optimization of antenna structures. The algorithm allows for identifying a set of Pareto optimal sets of parameters (that represent the best trade-offs between considered objectives) by iterative partitioning of the intervals connecting previously found designs and executing a Pareto-ranking-based poll search. The initial...
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Optimization algorithm and filtration using the adaptive TIN model at the stage of initial processing of the ALS point cloud
PublikacjaAirborne laser scanning (ALS) provides survey results in the form of a point cloud. The ALS point cloud is a source of data used primarily for constructing a digital terrain model (DTM). To generate a DTM, the set of ALS observations must be first subjected to the point cloud processing methodology. A standard methodology is composed of the following stages: acquisition of the ALS data, initial processing (including filtration),...
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A Novel Trust-Region-Based Algorithm with Flexible Jacobian Updates for Expedited Optimization of High-Frequency Structures
PublikacjaSimulation-driven design closure is mandatory in the design of contemporary high-frequency components. It aims at improving the selected performance figures through adjustment of the structure’s geometry (and/or material) parameters. The computational cost of this process when employing numerical optimization is often prohibitively high, which is a strong motivation for the development of more efficient methods. This is especially...
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EM-Driven Multi-Objective Optimization of a Generic Monopole Antenna by Means of a Nested Trust-Region Algorithm
PublikacjaAntenna structures for modern applications are characterized by complex and unintuitive topologies that are difficult to develop when conventional experience-driven techniques are of use. In this work, a method for automatic generation of antenna geometries in a multi-objective setup has been proposed. The approach involves optimization of a generic spline-based radiator with adjustable number of parameters using a nested trust-region-based...
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Particle swarm optimization algorithms for autonomous robots with deterministic leaders using space filling movements
PublikacjaIn 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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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublikacjaIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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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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A Tabu Search Algorithm for Optimization of Survivable Overlay Computing Systems
PublikacjaParadygmat obliczeń rozproszonych ostatnio zyskuje coraz większą uwagę, ponieważ zarówno instytucje przemysłowe, jak i uczelnie wymagają coraz większej mocy obliczeniowej do przetwarzania i analizy danych. Z uwagi na dużą podatność systemów obliczeń na awarie różnych typów (podobnie do systemów sieciowych), gwarancje przeżywalności niniejszych systemów są nieodzowne w celu zapewnienia nieprzerwanego działania usług. Z tego powodu,...
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Dynamic Route Discovery Using Modified Grasshopper Optimization Algorithm in Wireless Ad-Hoc Visible Light Communication Network
PublikacjaIn recent times, visible light communication is an emerging technology that supports high speed data communication for wireless communication systems. However, the performance of the visible light communication system is impaired by inter symbol interference, the time dispersive nature of the channel, and nonlinear features of the light emitting diode that significantly reduces the bit error rate performance. To address these problems,...
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Efficient Gradient-Based Algorithm with Numerical Derivatives for Expedited Optimization of Multi-Parameter Miniaturized Impedance Matching Transformers
PublikacjaFull-wave electromagnetic (EM) simulation tools have become ubiquitous in the design of microwave components. In some cases, e.g., miniaturized microstrip components, EM analysis is mandatory due to considera¬ble cross-coupling effects that cannot be accounted for otherwise (e.g., by means of equivalent circuits). These effects are particularly pronounced in the structures in¬volving slow-wave compact cells and their numerical...
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Innovative optimization algorithm of variable speed pumps in district heating systems.
PublikacjaW referacie przedstawiono innowacyjny algorytm matematyczny optymalizacji pracy pomp zmienno prędkościowych w systemach ciepłowniczych. Algorytm wykorzystuje procedurę iterecyjnego wyznaczania parametrów pracy pomp, których charakterystyki są linearyzowane odcinkami w układzie dwóch współrzędnych. Do rozwiązania modelu całkowitoliczbowego zaproponowano wykorzystanie systemu GAMS. W pracy przedstawiono podstawy metodologiczne i...
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A Biased-Randomized Iterated Local Search Algorithm for Rich Portfolio Optimization
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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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Design and optimization of IIR digital filters with non-standard characteristics using continuous ant colony optimization algorithm
PublikacjaW pracy przedstawiono metodę projektowania i optymalizacji stabilnych filtrów cyfrowych IIR o niestandardowych charakterystykach amplitudowych, przy zastosowaniu ''mrówkowego'' algorytmu optymalizującego ACO. W proponowanej metodzie (nazwanej ACO-IIRFD), wprowadzono dynamiczne zmiany parametrów. Dzięki tym zmianom parametrów filtru cyfrowego możliwe jest uzyskanie małych odchyłek charakterystyk między założonymi i aktualnymi....
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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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Drawing Functions and NLP Algorithm Steps for Optimization Problems by using O&G Software.
PublikacjaPraca opisuje program służący do wizualizacji problemów programowania nieliniowego (funkcja celu, ograniczenia) oraz pracy rozwiązującego je algorytmu. Wizualizacja może być realizowana w przestrzeni dwu- lub trójwymiarowej.
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Application of a modified evolutionary algorithm for the optimization of data acquisition to improve the accuracy of a video-polarimetric system
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