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wybranych: 2019
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- Publikacje 2019 wyników po odfiltrowaniu
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Wyniki wyszukiwania dla: NEURAL NETWORKS, SURROGATE-BASED OPTIMIZATION, HYPERPARAMETER OPTIMIZATION, SEQUENTIAL SAMPLING
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Complex multidisciplinary optimization of turbine blading systems
PublikacjaThe paper describes the methods and results of direct optimization of turbine blading systems using a software package Opti_turb. The final shape of the blading is obtained from minimizing the objective function, which is the total energy loss of the stage, including the leaving energy. The current values of the objective function are found from 3D RANS computations (from a code FlowER) of geometries changed during the process...
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Fast simulation-driven design optimization of UWB band-notch antennas
PublikacjaIn this letter, a simple yet reliable and automated methodology for rapid design optimization of ultra-wideband (UWB) band-notch antennas is presented. Our approach is a two-stage procedure with the first stage focused on the design of the antenna itself, and the secondstage aiming at identification of the appropriate dimensions of the resonator with the purpose of allocating the band-notch in the desired frequency range. For the...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublikacjaThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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Multi-fidelity robust aerodynamic design optimization under mixed uncertainty
PublikacjaThe objective of this paper is to present a robust optimization algorithm for computationally efficient airfoil design under mixed (inherent and epistemic) uncertainty using a multi-fidelity approach. This algorithm exploits stochastic expansions derived from the Non-Intrusive Polynomial Chaos (NIPC) technique to create surrogate models utilized in the optimization process. A combined NIPC expansion approach is used, where both...
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Design of microstrip antenna subarrays: a simulation-driven surrogate-based approach
PublikacjaA methodology for computationally efficient simulation-driven design of microstrip antenna subarrays is presented. Our approach takes into account the effect of the feed (here, a corporate network) on the subarray side-lobe level and allows adjustment of both radiation and reflection responses of the structure under design within a single automated process. This process is realized as surrogate-based optimization that produces...
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Preference-based evolutionary multi-objective optimization in ship weather routing
PublikacjaIn evolutionary multi-objective optimization (EMO) the aim is to find a set of Pareto-optimal solutions. Such approach may be applied to multiple real-life problems, including weather routing (WR) of ships. The route should be optimal in terms of passage time, fuel consumption and safety of crew and cargo while taking into account dynamically changing weather conditions. Additionally it must not violate any navigational constraints...
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Cost-efficient multi-objective design optimization of antennas in highly-dimensional parameter spaces
PublikacjaMulti-objective optimization of antenna structures in highly-dimensional parameter spaces is investigated. For expedited design, variable-fidelity EM simulations and domain patching algorithm are utilized. The results obtained for a monopole antenna with 13 geometry parameters are compared with surrogate-assisted optimization involving response surface approximation modeling.
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Low-Cost Multi-Objective Optimization Yagi-Uda Antenna in Multi-Dimensional Parameter Space
PublikacjaA surrogate-based technique for fast multi-objective optimization of a multi-parameter planar Yagi-Uda antenna structure is presented. The proposed method utilizes response surface approximation (RSA) models constructed using training samples obtained from evaluation of the low-fidelity antenna model. Utilization of the RSA models allowsfor fast determination of the best possible trade-offs between conflicting objectives in multi-objective...
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On deterministic procedures for low-cost multi-objective design optimization of miniaturized impedance matching transformers
PublikacjaPurpose This paper aims to investigate deterministic strategies for low-cost multi-objective design optimization of compact microwave structures, specifically, impedance matching transformers. The considered methods involve surrogate modeling techniques and variable-fidelity electromagnetic (EM) simulations. In contrary to majority of conventional approaches, they do not rely on population-based metaheuristics, which permit lowering...
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Performance Analysis of Convolutional Neural Networks on Embedded Systems
PublikacjaMachine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...
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Volume optimization of high-speed surface-mounted permanent magnet synchronous motor based on sequential quadratic programming technique and analytical solution
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Optimization of carbamazepine photodegradation on defective TiO2-based magnetic photocatalyst
PublikacjaIn this work, carbamazepine (CBZ) degradation over defective Fe3O4@SiO2/d-TiO2/Pt photocatalyst was studied. Within the titania structure, Ti vacancies and Pt nanoparticles were introduced to enhance the photocatalyst’s light absorption and influence charge carriers’ mobility. For the carbamazepine degradation, process parameters, e.g., temperature, flux intensity, photocatalyst loading, aeration, pH, and addition of H2O2, were optimized...
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Joint optimization of anycast and unicast flows in survivable optical networks
PublikacjaZnane z literatury dotychczasowe prace związane z ochroną ruchu przed awarią elementów sieci dotyczą transmisji typu unicast (jeden-do-jednego). Niniejszy artykuł jest pierwszym prezentującym rozwiązanie jednoczesnej ochrony transmisji anycast (jeden-do-jednego-z-wielu) oraz transmisji unicast. Proponowane podejście wykorzystuje model ochrony ścieżki (ang. path protection). Zagadnienie zostało sformułowane w postaci odpowiedniego...
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MULTI-OBJECTIVE OPTIMIZATION PROBLEM IN THE OptD-MULTI METHOD
PublikacjaNew measurement technologies, e.g. Light Detection And Ranging (LiDAR), generate very large datasets. In many cases, it is reasonable to reduce the number of measuring points, but in such a way that the datasets after reduction satisfy specific optimization criteria. For this purpose the Optimum Dataset (OptD) method proposed in [1] and [2] can be applied. The OptD method with the use of several optimization criteria is called...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublikacjaThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
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Fast multi-criterial statistical analysis and design optimization of compact microwave couplers
Publikacja—A rapid statistical analysis and yield estimation of compact microwave couplers involving multiple performance parameters has been presented. The analysis is realized using a fast surrogate model representing appropriate characteristic points of the coupler response. Because of less nonlinear dependence of the characteristic points on the structure geometry (compared to the original response, i.e., S-parameters vs. frequency),...
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Low-Cost EM-Simulation-Driven Multi-Objective Optimization of Antennas
PublikacjaA surrogate-based method for efficient multi-objective antenna optimization is presented. Our technique exploits response surface approximation (RSA) model constructed from sampled low-fidelity antenna model (here, obtained through coarse-discretization EM simulation). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. A low-cost RSA model construction is possible through...
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A Concept of Modeling and Optimization of Applications in Large Scale Systems
PublikacjaThe chapter presents the idea that includes modeling and subsequent optimization of application execution on large scale parallel and distributed systems. The model considers performance, reliability and power consumption. It should allow easy modeling of various classes of applications while reflecting key parameters of both the applications and two classes of target systems: clusters and volunteer based systems. The chapter presents...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublikacjaDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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A Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks
PublikacjaForward error correction is crucial for communication, enabling error rate or required SNR reduction. Longer codes improve correction ratio. Iterated codes offer a solution for constructing long codeswith a simple coder and decoder. However, a basic iterative code decoder cannot fully exploit the code’s potential, as some error patterns within its correction capacity remain uncorrected.We propose two neural network-assisted decoders:...
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Comprehensive comparison of compact UWB antenna performance by means of multi-objective optimization
PublikacjaAn optimization-based procedure for comprehensive performance comparison of alternative compact UWB antenna topologies is discussed. The assessment of the antenna performance is conducted with respect to the structure size and its reflection response. More specifically, the best possible tradeoffs between these two figures of merit are identified through multiobjective optimization at the level...
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Multi-objective optimization of tool wear, surface roughness, and material removal rate in finishing honing processes using adaptive neural fuzzy inference systems
PublikacjaHoning processes are usually employed to manufacture combustion engine cylinders and hydraulic cylinders. A crosshatch pattern is obtained that favors the oil flow. In this paper, Adaptive Neural Fuzzy Inference System (ANFIS) models were obtained for tool wear, average roughness Ra, cylindricity and material removal rate in finish honing processes. In addition, multi-objective optimization with the desirability function method...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Nested Kriging Surrogates for Rapid Multi-Objective Optimization of Compact Microwave Components
PublikacjaA procedure for rapid EM-based multi-objective optimization of compact microwave components is presented. Our methodology employs a recently developed nested kriging modelling to identify the search space region containing the Pareto-optimal designs, and to construct a fast surrogate model. The latter permits determination of the initial Pareto set, further refined using a separate surrogate-assisted process. As an illustration,...
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FLUID BED COATING OF MINITABLETS AND PELLETS WITH OPTIMIZATION OF THE PROCESS BASED ON TAGUCHI METHOD
PublikacjaSmall particles like pellets are coated in fluid bed systems. This method can be also feasible for minitablets but the selection of optimal process parameters is complicated. The aim of the research was to optimize the coating process for minitablets and to compare the conditions required for pellets. Minimum fluidization velocities (umf) for 2.0 and 2.5 mm minitablets and 0.7-0.8 mm or 1.0-1.25 mm pellets were determined experimentally....
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Cost-efficient design optimization of compact patch antennas with improved bandwidth
PublikacjaIn this letter, a surrogate-assisted optimization procedure for fast design of compact patch antennas with enhanced bandwidth is presented. The procedure aims at addressing a fundamental challenge of the design of antenna structures with complex topologies, which is simultaneous adjustment of numerous geometry parameters. The latter is necessary in order to find a truly optimum design and cannot be executed-at the level of high-fidelity...
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
PublikacjaBearing defect is statistically the most frequent cause of an induction motor fault. The research described in the paper utilized the phenomenon of the current change in the induction motor with bearing defect. Methods based on the analysis of the supplying current are particularly useful when it is impossible to install diagnostic devices directly on the motor. The presented method of rolling-element bearing diagnostics used indirect...
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Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublikacjaDesign of contemporary antenna structures needs to account for several and often conflicting objectives. These are pertinent to both electrical and field properties of the antenna but also its geometry (e.g., footprint minimization). For practical reasons, especially to facilitate efficient optimization, single-objective formulations are most often employed, through either a priori preference articulation, objective aggregation,...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublikacjaThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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Nested Space Mapping Technique for Design and Optimization of Complex Microwave Structures with Enhanced Functionality
PublikacjaIn this work, we discuss a robust simulation-driven methodology for rapid and reliable design of complex microwave/RF circuits with enhanced functionality. Our approach exploits nested space mapping (NSM) technology, which is dedicated to expedite simulation-driven design optimization of computationally demanding microwave structures with complex topologies. The enhanced func-tionality of the developed circuits is achieved by means...
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Design of dimensionally stable composites using efficient global optimization method
PublikacjaDimensionally stable material design is an important issue for space structures such as space laser communication systems, telescopes, and satellites. Suitably designed composite materials for this purpose can meet the functional and structural requirements. In this paper, it is aimed to design the dimensionally stable laminated composites by using efficient global optimization method. For this purpose, the composite plate optimization...
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Multi-objective optimization for assessment of topological modification in UWB antennas
PublikacjaThis paper addresses an issue of systematic and rigorous assessment of effects of topological modifications on the performance of compact UWB antennas. Application of fast surrogate-assisted multi-objective optimization procedures allows us for obtaining, in a practically acceptable timeframe, a set of designs representing the best possible trade-offs between conflicting objectives (here, antenna size minimization and reduction...
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Rapid Yield Estimation and Optimization of Microwave Structures Exploiting Feature-Based Statistical Analysis
PublikacjaIn this paper, we propose a simple, yet reliable methodology to expediteyield estimation and optimization of microwave structures. In our approach,the analysis of the entire response of the structure at hand (e.g., $S$-parameters asa function of frequency) is replaced by response surface modeling of suitablyselected feature points. On the one hand, this is sufficient to determinewhether a design satisfies given performance specifications....
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Low-cost multi-objective optimization and experimental validation of UWB MIMO antenna
PublikacjaPurpose–The purpose of this paper is to validate methodologies for expedited multi-objective designoptimization of complex antenna structures both numerically and experimentally.Design/methodology/approach–The task of identifying the best possible trade-offs between theantenna size and its electrical performance is formulated as multi-objective optimization problem.Algorithmic frameworks are described for finding Pareto-optimal...
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EM-Driven Multi-Objective Optimization of Antenna Structures in Multi-Dimensional Design Spaces
PublikacjaFeasible multi-objective optimization of antenna structures is presented. An initial set of Pareto optimal solutions is found using a multi-objective evolutionary algorithm (MOEA) working with a fast surrogate antenna model obtained by kriging interpolation of coarse-discretization EM simulation data. To make the surrogate construction computationally feasible in multi-dimensional design space, the space subset containing non-dominated...
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Variable-Fidelity Simulation Models and Sparse Gradient Updates for Cost-Efficient Optimization of Compact Antenna Input Characteristics
PublikacjaDesign of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concerning size limitation. Fulfillment of stringent specifications necessitates the development of topologically complex structures described by a large number of geometry parameters that...
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Model Management for Low-Computational-Budget Simulation-Based Optimization of Antenna Structures Using Nature-Inspired Algorithms
PublikacjaThe 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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On Nature-Inspired Design Optimization of Antenna Structures Using Variable-Resolution EM Models
PublikacjaNumerical optimization has been ubiquitous in antenna design for over a decade or so. It is indispensable in handling of multiple geometry/material parameters, performance goals, and constraints. It is also challenging as it incurs significant CPU expenses, especially when the underlying computational model involves full-wave electromagnetic (EM) analysis. In most practical cases, the latter is imperative to ensure evaluation reliability....
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Design space reduction and variable-fidelity EM simulations for feasible Pareto optimization of antennas
PublikacjaA computationally efficient procedure for multi-objective optimization of antenna structures is presented. In our approach, a response surface approximation (RSA) model created from sampled coarse-discretization EM antenna simulations is utilized to yield an initial set of Pareto-optimal designs using a multi-objective evolutionary algorithm. The final Pareto front representation for the high-fidelity model is obtained using surrogate-based...
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Variable-fidelity CFD models and co-Kriging for expedited multi-objective aerodynamic design optimization
PublikacjaPurpose – Strategies for accelerated multi-objective optimization of aerodynamic surfaces are investigated, including the possibility of exploiting surrogate modeling techniques for computational fluid dynamic (CFD)-driven design speedup of such surfaces. The purpose of this paper is to reduce the overall optimization time. Design/methodology/approach – An algorithmic framework is described that is composed of: a search space reduction,...
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Rapid Microwave Design Optimization in Frequency Domain Using Adaptive Response Scaling
PublikacjaIn this paper, a novel methodology for cost-efficient microwave design optimization in the frequency domain is proposed. Our technique, referred to as adaptive response scaling (ARS), has been developed for constructing a fast replacement model (surrogate) of the high-fidelity electromagnetic-simulated model of the microwave structure under design using its equivalent circuit (low-fidelity model). The basic principle of ARS is...
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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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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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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublikacjaThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Decisional DNA and Optimization Problem
PublikacjaMany researchers have proved that Decisional DNA (DDNA) and Set of Experience Knowledge Structure (SOEKS or SOE) is a technology capable of gathering information and converting it into knowledge to help decision-makers to make precise decisions in many ways. These techniques have a feature to combine with different tools, such as data mining techniques and web crawlers, helping organization collect information from different sources...
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Optimization-Based Robustness Enhancement of Compact Microwave Component Designs with Response Feature Regression Surrogates
PublikacjaThe ability to evaluate the effects of fabrication tolerances and other types of uncertainties is a critical part of microwave design process. Improving the immunity of the device to parameter deviations is equally important, especially when the performance specifications are stringent and can barely be met even assuming a perfect manufacturing process. In the case of modern miniaturized microwave components of complex topologies,...
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Performance-driven yield optimization of high-frequency structures by kriging surrogates
PublikacjaUncertainty quantification is an important aspect of engineering design, as manufacturing toler-ances may affect the characteristics of the structure. Therefore, quantification of these effects is in-dispensable for adequate assessment of the design quality. Toward this end, statistical analysis is performed, for reliability reasons, using full-wave electromagnetic (EM) simulations. Still, the computational expenditures associated...
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Multi-objective optimization of microwave couplers using corrected domain patching
PublikacjaPractical design of microwave components and circuits is a compromise between various, often conflicting objectives. In case of compact structures, the trade-offs are typically concerned with the circuit size and its electrical performance. Comprehensive information about the best possible trade-offs can be obtained by means of multi-objective optimization. In this paper, we propose a computationally efficient technique for identifying...
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Adaptive stochastic and hybrid nonlinear optimization algorithms for improving the effectiveness of the biological processes at WWTP
PublikacjaWastewater treatment plays an important factor in the modern world. Insufficient treatment may result in environmental pollution which can further lead to disasters and diseases. However, processes that take place inside wastewater treatment plants (WWTP) are highly complex in nature, therefore it is difficult to design an efficient, optimal control system. The problem regarding biochemical reactions inside Sequential Batch Reactor...