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Wyniki wyszukiwania dla: MODEL SELECTION ALGORITHM
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An Attempt to Develop a Model Selection Algorithm of Computer Simulation during the Design Process of Mechanical Response of Any Mechanical Body
PublikacjaIn the literature, there are algorithms associated with the design of simulations of technological processes, in which the material model has always been defined previously. However, in none of the studies of computer simulation modelling of technological processes known to the authors of this article, is there a detailed description of how the algorithm, or the selection of plastic model used, is subject to this process. This...
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An attempt to develop a model selection algorithm of computer simulation during the design process of mechanical response of any mechanical body
Publikacjan the literature, there are algorithms associated with the design of simulations of technological processes, in which the material model has always been defined previously. However, in none of the studies of computer simulation modelling of technological processes known to the authors of this article, is there a detailed description of how the algorithm, or the selection of plastic model used, is subject to this process. This article...
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Clonal selection algorithm for vehicle routing
PublikacjaOver the years several successful computing techniques have been inspired by biological mechanisms. Studies of the mechanisms that allow the immune systems of vertebratesto adapt and learn have resulted in a class of algorithms called artificial immune systems. Clonal selection is a process that allows lymphocytes to launch a quick response to known pathogens and to adapt to new, previously unencountered ones. This paper presents...
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A New Cluster-based Instance Selection Algorithm
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Feature type and size selection for adaboost face detection algorithm
PublikacjaThe article presents different sets of Haar-like features defined for adaptive boosting (AdaBoost) algorithm for face detection. Apart from a simple set of pixel intensity differences between horizontally or vertically neighboring rectangles, the features based on rotated rectangles are considered. Additional parameter that limits the area on which the features are calculated is also introduced. The experiments carried out on...
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Computer experiments with a parallel clonal selection algorithm for the graph coloring problem
PublikacjaArtificial immune systems (AIS) are algorithms that are based on the structure and mechanisms of the vertebrate immune system. Clonal selection is a process that allows lymphocytes to launch a quick response to known pathogens and to adapt to new, previously unencountered ones. This paper presents a parallel island model algorithm based on the clonal selection principles for solving the Graph Coloring Problem. The performance of...
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Selection of energy storage units by genetic algorithm for mitigating voltage deviations
PublikacjaIn recent years, energy storage units have become very popular. They are applied both for economic and technical purposes. Unfortunately, the cost of such devices is still high and selecting their proper location and rated power have to be performed precisely. In this paper, a Genetic-Algorithm-based optimization method for selecting the best configuration of energy storage units in the power network is proposed. The presented...
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Automated Reduced Model Order Selection
PublikacjaThis letter proposes to automate generation of reduced-order models used for accelerated -parameter computation by applying a posteriori model error estimators. So far,a posteriori error estimators were used in Reduced Basis Method (RBM) and Proper Orthogonal Decomposition (POD) to select frequency points at which basis vectors are generated. This letter shows how a posteriori error estimators can be applied to automatically select...
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Prediction based on integration of Decisional DNA and a feature selection algorithm Relief-F
PublikacjaThe paper presents prediction model based on Decisional DNA and Set of experienced integrated with Relief_F algorithm for feature selection
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Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection
PublikacjaAn evolutionary algorithm with elitist selection has been developed for finding Pareto-optimal task assignments in logistics. A multi-criterion optimization problem has been formulated for finding a set of Pareto- optimal solutions. Three criteria have been applied for evaluation of task assignment: the workload of a bottleneck machine, the cost of machines, and the numerical performance of system. The machine constraints have...
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Genetic Algorithm Approach for Gains Selection of Induction Machine Extended Speed Observer
PublikacjaThe subject of this paper is gains selection of an extended induction machine speed observer. A high number of gains makes manual gains selection difficult and due to nonlinear equations of the observer, well-known methods of gains selection for linear systems cannot be applied. A method based on genetic algorithms has been proposed instead. Such an approach requires multiple fitness function calls; therefore, using a quality index...
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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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Selection of optimal location and rated power of capacitor banks in distribution network using genetic algorithm
PublikacjaIn this paper, the problem of placement and rated power of capacitor banks in the Distribution Network (DN) is considered. We try to suggest the best places for installing capacitor banks and define their reactive power. The considered formulation requires the optimization of the cost of two different objectives. Therefore the use of properly multiobjective heuristic optimization methods is desirable. To solve this problem we use...
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Auditory-model based robust feature selection for speech recognition
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The choice of parameters of induction motor model using a genetic algorithm.
PublikacjaRozważano problem doboru parametrów modeli matematycznych dużych 3 -fazowych silników indukcyjnych. Modele o prawidłowo dobranych parametrach mogą być pomocne podczas procedur projektowych. Podane silniki mogą być używane jako napędy sterów strumieniowych statków. Symulacje w środowisku Matlab, uwzględniają modele statyczne silników. Parametry silników dobierane są za pomocą przybornika Genetic Algorithm Toolbox. Skuteczność metody...
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Hard Lessons Learned: A Model that Facilitates the Selection of Methods of IT Project Management
PublikacjaThe article presents the results of research conducted in an international enterprise responsible for IT project implementation. The carried out analysis of the case study with the use of surveys and data synthesis allowed the major factors causing problems connected with project management to be identified. The identified factors were aggregated and then, by using four key variables, a rhomboidal model adaptation was proposed...
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Simulation model for evaluation of QoS routing algorithm in large packet networks
PublikacjaThe variety of traffic transferred via current telecommunication networks includes also voice, which should meet quality requirements. One of mechanisms, which can support QoS in current packet networks, is routing. There exist many routing proposals which should introduce the QoS into the network but practically they don't. Following paper presents the realization of simulation model for evaluation of a new routing algorithm DUMBRA...
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Quality model for UML tools in application to UML tool selection and market analysis
PublikacjaJęzyki modelowania i wspierające je narzędzia odgrywają istotną rolę w procesie wytwarzania i utrzymania oprogramowania. Wraz ze wzrostem liczby narzędzi UML na rynku pojawia się potrzeba ich porównania i oceny. Artykuł prezentuje wielowymiarowy model oceny narzędzi UML, opisuje ankietę przydatną do oceny narzędzi UML oraz przedstawia system oceny narzędzi UML wraz ze studium przypadku jego zastosowania do poszukiwania narzędzi...
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Tree-based homogeneous ensemble model with feature selection for diabetic retinopathy prediction
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Preselection of a sorption model based on a column test: the algorithm and an example of its application
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Selection and Setting of an Intelligent Fuzzy Regulator based on Nonlinear Model Simulations of a Helicopter in Hover
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A Conception of Pairwise Comparisons Model for Selection of Appropriate Body Surface Area Calculation Formula
PublikacjaBody surface area (BSA) may be computed using a variety of formulas, but the computed BSA differs from real BSA values for particular subjects. This is presented in the paper by computing BSA values for selected subject and comparing them to the real BSA value obtained with the use of a 3D body scanner. The results show inequalities in the relevant BSA computing formulas. Hence, there is a need to determine a method that will allow...
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A Novel Divisive iK-Means Algorithm with Region-Driven Feature Selection as a Tool for Automated Detection of Tumour Heterogeneity in MALDI IMS Experiments
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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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ARTIFICIAL MODEL IN THE ASSESSMENT OF THE ALGORITHM OF OBJECTS RECORDED BY LASER SCANNING SHAPE DETECTION (ALS/TLS)
PublikacjaBrief description of the study and used methods. Brief description of the study and used As part of the preparatory work aimed to create the application solution allowing for the automation of searching objects in data, obtained in the scanning process using ALS (Airborne Laser Scanning) or TLS (Terrestrial Laser Scanning), the authors prepared a artificial (synthetic, theoretical) model of space, used for the verification of operation...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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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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The hybrid estimation algorithm for wastewater treatment plant robust model predictive control purposes at medium time scale
PublikacjaThe paper proposes an approach to designing the hybrid estimation algorithm/module (HEA) with moving measurements window for Wastewater Treatment Plant (WWTP) Robust Model Predictive Control (RMPC) purposes at medium time scale. The RMPC uses a dedicated grey-box model of biological reactor for the system outputs prediction purposes. The grey-box model parameters are dependant on the plant operating point. Hence, these parameters...
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An inverse algorithm for contact heat conduction problems with an interfacial heat source based on a first-order thermocouple model
PublikacjaInverse problems of contact heat conduction with an interfacial heat source are common in various fields of science, engineering and technology. In this study, an algorithm for their solution is developed based on an inverse parametric optimisation method with an impulse response function describing the heat partition and contact heat transfer. A first-order thermocouple model with a time constant parameter is embedded in the impulse...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublikacjaThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Model studies to identify input parameters of an algorithm controlling electric supply/consumption process by underground iron ore enterprises
PublikacjaPurpose is the development of the research format of a mathematical model to select and assess input parameters of an algorithm controlling distribution of electric energy flows in the monitoring structure of electricity supply/ consumption by using equipment of mining enterprises engaged in underground iron ore raw materials extraction. Methods. The analytical research involved a theory of random processes adapted to the real...
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The chapter analyses the K-Means algorithm in its parallel setting. We provide detailed description of the algorithm as well as the way we paralellize the computations. We identified complexity of the particular steps of the algorithm that allows us to build the algorithm model in MERPSYS system. The simulations with the MERPSYS have been performed for different size of the data as well as for different number of the processors used for the computations. The results we got using the model have been compared to the results obtained from real computational environment.
PublikacjaThe chapter analyses the K-Means algorithm in its parallel setting. We provide detailed description of the algorithm as well as the way we paralellize the computations. We identified complexity of the particular steps of the algorithm that allows us to build the algorithm model in MERPSYS system. The simulations with the MERPSYS have been performed for different size of the data as well as for different number of the processors used...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublikacjaSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Multiprocessor Implementation of Parallel Multiobjective Genetic Algorithm for Optimized Allocation of Chlorination Stations in Drinking Water Distribution System a New Water Quality Model Approach
PublikacjaThe Critical Infrastructure Systems (CISs) have received in recent years a considerable attention due to their heavy impact on sustainable development of modern societies. Most CISs may be classied as large scale complex systems of network structure, in uenced by strong interactions form the surrounding environment, internal and external interconnections. The later is a result of inter-CIS dependencies. The control, monitoring...
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Multiprocessor implementation of Parallel Multiobjective Genetic Algorithm for Optimized Allocation of Chlorination Stations in Drinking Water Distribution System - a new water quality model approach
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Comparison and Analysis of Service Selection Algorithms
PublikacjaIn Service Oriented Architecture, applications are developed by integration of existing services in order to reduce development cost and time. The approach, however, requires algorithms that select appropriate services out of available, alternative ones. The selection process may consider both optimalization requirements, such as maximalization of performance, and constraint requirements, such minimal security or maximum development...
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EVALUATION OF THE SEMIVARIOGRAM SELECTION ON THE KRIGING INTERPOLATION
PublikacjaThe aim of the paper is to present the possibilities of geostatistical interpolation kriging method using in the process of generating digital terrain models (DTM). The source of data is a direct measurements realized with a precision GNSS positioning kinematic measurement technique RTN. Kriging algorithm was analysed, especially in the meaning of a semivariogram every step. Theoretical semivariogram selection influence on the...
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Interoperability Constraints in Service Selection Algorithms
PublikacjaIn Service Oriented Architecture, composite applications are developed by integration of existing, atomic services that may be available in alternative versions realizing the same functionality but having different Quality of Service (QoS) attributes. The development process requires effective service selection algorithms that balance profits and constraints of QoS attributes. Additionally, services operate in a heterogeneous environment,...
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Low-fidelity model considerations for simulation-based optimisation of miniaturised wideband antennas
PublikacjaHere, variable-fidelity electromagnetic (EM)-based design optimisation of miniaturised antennas is discussed. The authors focus on an appropriate selection of discretisation density of the low-fidelity EM model, which results in good performance of the optimisation algorithm in terms of its computational complexity and reliability. Trust-region gradient search with low-fidelity model corrected by means of non-linear frequency scaling...
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Integrated algorithm for selecting the location and control of energy storage units to improve the voltage level in distribution grids
PublikacjaThis paper refers to the issue that mainly appears in distribution grids, where renewable energy sources (RES) are widely installed. In such grids, one of the main problems is the coordination of energy production time with demand time, especially if photovoltaic energy sources are present. To face this problem, battery energy storage units (ESU) can be installed. In recent years, more and more attention has been paid to optimizing...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Greedy Multipoint Model-Order Reduction Technique for Fast Computation of Scattering Parameters of Electromagnetic Systems
PublikacjaThis paper attempts to develop a new automated multipoint model-order reduction (MOR) technique, based on matching moments of the system input–output function, which would be suited for fast and accurate computation of scattering parameters for electromagnetic (EM) systems over a wide frequency band. To this end, two questions are addressed. Firstly, the cost of the wideband reduced model generation is optimized by automating a...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublikacjaIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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On low-fidelity models for variable-fidelity simulation-driven design optimization of compact wideband antennas
PublikacjaThe paper addresses simulation-driven design optimization of compact antennas involving variable-fidelity electromagnetic (EM) simulation models. Comprehensive investigations are carried out concerning selection of the coarse model discretization density. The effects of the low-fidelity model setup on the reliability and computational complexity of the optimization process are determined using a benchmark set of three ultra-wideband...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublikacjaBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Locally Adaptive Cooperative Kalman Smoothing and Its Application to Identification of Nonstationary Stochastic Systems
PublikacjaOne of the central problems of the stochastic approximation theory is the proper adjustment of the smoothing algorithm to the unknown, and possibly time-varying, rate and mode of variation of the estimated signals/parameters. In this paper we propose a novel locally adaptive parallel estimation scheme which can be used to solve the problem of fixed-interval Kalman smoothing in the presence of model uncertainty. The proposed solution...
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Reduced-Cost Microwave Design Closure by Multi-Resolution EM Simulations and Knowledge-Based Model Management
PublikacjaParameter adjustment through numerical optimization has become a commonplace of contemporary microwave engineering. Although circuit theory methods are ubiquitous in the development of microwave components, the initial designs obtained with such tools have to be further tuned to improve the system performance. This is particularly pertinent to miniaturized structures, where the cross-coupling effects cannot be adequately accounted...
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Machining process sequencing and machine assignment in generative feature-based CAPP for mill-turn parts
PublikacjaProcess selection and sequencing, as one of the most complex issues when evaluated from a mathematical point of view and crucial in CAPP, still attract research attention. For the current trend of intelligent manufacturing, machining features (MFs) are the information carriers for workpiece geometry and topology representation. They are basically derived from CAD models and are used by downstream engineering applications. A feature-based...