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Search results for: GENETIC ALGORITHM
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Energy Management for PV Powered Hybrid Storage System in Electric Vehicles Using Artificial Neural Network and Aquila Optimizer Algorithm
PublicationIn an electric vehicle (EV), using more than one energy source often provides a safe ride without concerns about range. EVs are powered by photovoltaic (PV), battery, and ultracapacitor (UC) systems. The overall results of this arrangement are an increase in travel distance; a reduction in battery size; improved reaction, especially under overload; and an extension of battery life. Improved results allow the energy to be used efficiently,...
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Design of dimensionally stable composites using efficient global optimization method
PublicationDimensionally 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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Zarządzanie opóźnieniami w ruchu kolejowym
PublicationZarządzanie opóźnieniami w ruchu kolejowym zostało przedstawione jako wielokryterialny problem optymalizacyjny, do rozwiązania którego został użyty model ogólny (job-shop) szeregowania zadań. W artykule przedstawiono sposób zastosowania trzech algorytmów metaheurystycznych: algorytmu genetycznego (Genetic Algorithm), algorytmu roju (Particle Swarm Optimization) i algorytmu mrówkowego (Ant Colony Optimization) do znalezienia optymalnego...
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Optimizing control by robustly feasible model predictive control and application to drinking water distribution systems
PublicationThe paper considers optimizing Model Predictive Control (MPC) for nonlinear plants with output constraints under uncertainties. Although the MPC technology can handle the constraints in the model by solving constraint model based optimization task, satisfying the plant output constraints under the model uncertainty still remains a challenge. The paper proposes Robustly Feasible MPC (RFMPC), which achieves feasibility of the outputs...
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Marine and Cosmic Inspirations for AI Algorithms
PublicationArtificial Intelligence (AI) is a scientific area that currently sees an enormous growth. Various new algorithms and methods are developed and many of them meets practical, successful applications. Authors of new algorithms draw different inspirations. Probably the most common one is the nature. For example, Artificial Neural Networks were inspired by the structure of human brain and nervous system while the classic Genetic Algorithm...
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Mean Crossover in evolutionary path planning method for maritime collision avoidance
PublicationAbstract: This paper presents the use of mean crossover genetic operator for path planning using evolutionary algorithm for collision avoidance on sea. Mean crossover ensures widening of the possible solutions' set that can be achieved in comparison to exchange crossover variant. The research shown, that the mean crossover allows to achieve results independent from the initial generation and quicker transition of thealgorithm from...
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A stochastic approach for the solution of single and multi – objective optimisation problems of biological processes in sequencing batch reactor
PublicationThis paper investigates the impact of implementing single and multi-optimisation solutions on the biological treatment process in a sequencing batch reactor (SBR). The research is based on a case study of the water resource recovery facility (WRRF) in Swarzewo, Northern Poland. The paper introduces the adaptive extremum seeking control (ESC) method for dissolved oxygen (DO) concentration control and places it in a layered control structure....
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Metoda diagnostyki cieplno-przepływowej turbin parowych wykorzystująca elementy algorytmów genetycznych
PublicationRozprawa doktorska poświęcona jest opisowi budowania metody diagnostyki cieplno-przepływowej z wykorzystaniem elementów algorytmów genetycznych. Do tworzenia założeń i algorytmów metody posłużono się przykładem funkcjonowania bloku elektrowni kondensacyjnej ze szczególnym uwzględnieniem układu łopatkowego turbiny parowej. Celem pracy jest zbudowanie metody diagnostyki cieplno-przepływowej. Zadaniem metody jest przeprowadzenie procesu...
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Parallelization of Selected Algorithms on Multi-core CPUs, a Cluster and in a Hybrid CPU+Xeon Phi Environment
PublicationIn the paper we present parallel implementations as well as execution times and speed-ups of three different algorithms run in various environments such as on a workstation with multi-core CPUs and a cluster. The parallel codes, implementing the master-slave model in C+MPI, differ in computation to communication ratios. The considered problems include: a genetic algorithm with various ratios of master processing time to communication...
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Mixed-use buildings as the basic unit that shapes the housing environment of smart cities of the future
PublicationThe contemporary approach to creating the residential function is confronted with the trend of increasing the volume of buildings and expectations regarding the future urban environment focused on sustainable development. This paper presents an overview of the residential structure in the context of defined thematic scopes. Namely, it is a systemic approach to the problem of designing mixed-use buildings which create a modern residential...
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Dobór parametrów silnika indukcyjnego dużej mocy
PublicationW artykule przedstawiono trzy typy statycznych modeli matematycznych silników klatkowych oraz metodę estymacji parametrów, przy wykorzystaniu algorytmów genetycznych. Korzystając z kryteriów: suma kwadratów, suma wartości bez-względnych oraz całkowego, oceniono przydatność badanych modeli. Opracowane modele matematyczne zostały wykorzystane przy doborze algorytmów sterownia sterów strumieniowych. Po-kazano metodykę doboru parametrów...
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Hierarchiczna Pareto-optymalizacja obserwatorów detekcyjnych
PublicationW niniejszym rozdziale omawiana jest nowa metoda nieostrego, eksperckiego uporządkowania funkcji kryterialnych odpowiednich dla ewolucyjnych i chmarowych podejść do (iteracyjnego) rozwiązywania wielokryterialnych zadań optymalizacyjnych, w których korzysta się z idei rodzajnika genetycznego opartego na podziale zbioru funkcji celu na odpowiednie podzbiory (subkryteria). Podział ten odnosi się do pokrewieństwa w przestrzeni kryterialnej...
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Evolutionary Algorithms in MPLS network designing
PublicationMPLS technology become more and more popular especially in core networks giving great flexibility and compatibility with existing Internet protocols. There is a need to optimal design such networks and optimal bandwidth allocation. Linear Programming is not time efficient and does not solve nonlinear problems. Heuristic algorithms are believed to deal with these disadvantages and the most promising of them are Evolutionary Algorithms....
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A Universal Gains Selection Method for Speed Observers of Induction Machine
PublicationProperties of state observers depend on proper gains selection. Each method of state estimation may require the implementation of specific techniques of finding those gains. The aim of this study is to propose a universal method of automatic gains selection and perform its verification on an induction machine speed observer. The method utilizes a genetic algorithm with fitness function which is directly based on the impulse response...
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Optymalizacja zasobów chmury obliczeniowej z wykorzystaniem inteligentnych agentów w zdalnym nauczaniu
PublicationRozprawa 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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Testing Stability of Digital Filters Using Optimization Methods with Phase Analysis
PublicationIn this paper, novel methods for the evaluation of digital-filter stability are investigated. The methods are based on phase analysis of a complex function in the characteristic equation of a digital filter. It allows for evaluating stability when a characteristic equation is not based on a polynomial. The operation of these methods relies on sampling the unit circle on the complex plane and extracting the phase quadrant of a function...
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Design of Cost-Efficient Optical Fronthaul for 5G/6G Networks: An Optimization Perspective
PublicationCurrently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient...
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Ternary Bismuthide SrPtBi2: Computation and Experiment in Synergism to Explore Solid-State Materials
PublicationA combination of theoretical calculation and the experimental synthesis to explore the new ternary compound is demonstrated in the Sr–Pt–Bi system. Because Pt–Bi is considered as a new critical charge-transfer pair for superconductivity, it inspired us to investigate the Sr–Pt–Bi system. With a thorough calculation of all the known stable/metastable compounds in the Sr–Pt–Bi system and crystal structure predictions, the thermodynamic...
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Overview of Approaches for Compensating Inherent Metamaterials Losses
PublicationMetamaterials are synthetic composite structures with extraordinary electromagnetic properties not readily accessible in ordinary materials. These media attracted massive attention due to their exotic characteristics. However, several issues have been encountered, such as the narrow bandwidth and inherent losses that restrict the spectrum and the variety of their applications. The losses have become the principal limiting factor...
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Analiza właściwości rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublicationRozszerzony obserwator prędkości został zaproponowany przez prof. Krzemińskiego i jest oparty na rozszerzonym modelu maszyny indukcyjnej, gdzie wprowadzona został nowa zmienna ζ. Jest to nowe podejście do estymacji zmiennych stanu maszyny indukcyjnej i nie wszystkie problemy zostały do tej pory rozwiązane. Zaproponowano wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień obserwatora. W celu redukcji nakładów obliczeniowych...
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Połączenie G3 dwóch kierunków prostych z użyciem krzywej NURBS
PublicationW artykule przedstawiono nową metodę projektowania układu geometrycznego toru kolejowego opartą na zastosowaniu krzywych NURBS (Non-Uniform Rational B-Spline) do opisu krzywizny. Punkty kontrolne krzywej NURBS wyznaczane są w procesie optymalizacji za pomocą algorytmu genetycznego. Jako kryterium optymalizacji przyjęto minimalizację oddziaływań dynamicznych występujących w układzie tor-pojazd przy spełnieniu warunków geometrycznych...
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Designing acoustic scattering elements using machine learning methods
PublicationIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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Metaheuristic algorithms for optimization of resilient overlay computing systems
PublicationThe idea of distributed computing systems has been gaining much interest in recent years owing to the growing amount of data to be processed for both industrial and academic purposes. However, similar to other systems, also distributed computing systems are vulnerable to failures. Due to strict QoS requirements, survivability guarantees are necessary for provisioning of uninterrupted service. In this article, we focus on reliability...
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Multi-objective optimization of the cavitation generation unit structure of an advanced rotational hydrodynamic cavitation reactor
PublicationHydrodynamic cavitation (HC) has been widely considered a promising technique for industrial-scale process intensifications. The effectiveness of HC is determined by the performance of hydrodynamic cavitation reactors (HCRs). The advanced rotational HCRs (ARHCRs) proposed recently have shown superior performance in various applications, while the research on the structural optimization is still absent. The present study, for the...
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Genetic Hybrid Predictive Controller for Optimized Dissolved-Oxygen Tracking at Lower Control Level
PublicationA hierarchical two-level controller for dissolvedoxygenreference trajectory tracking in activated sludge processeshas been recently developed and successfully validated on a realwastewater treatment plant. The upper level control unit generatestrajectories of the desired airflows to be delivered by theaeration system to the aerobic zones of the biological reactor. Anonlinear model predictive control algorithm is applied to designthis...
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METODA WIELOKRYTERIALNEJ OCENY PRZEBUDOWY UKŁADÓW TOROWYCH NA SZLAKACH
PublicationRozprawa doktorska dotyczy zagadnienia projektowania układów geometrycznych toru kolejowego w procesie modernizacji linii kolejowych. Scharakteryzowano główne cechy dotyczące tej tematyki w oparciu o literaturę polską i zagraniczną, w tym przepisy branżowe. Przedstawiono czynniki wpływające na projektowanie modernizacji linii kolejowych. Określono wartości dopuszczalne parametrów kinematycznych i geometrycznych. Specyfika omawianego...
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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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Analyzing Wind Energy Potential Using Efficient Global Optimization: A Case Study for the City Gdańsk in Poland
PublicationWind energy (WE), which is one of the renewable energy (RE) sources for generating electricity, has been making a significant contribution to obtaining clean and green energy in recent years. Fitting an appropriate statistical distribution to the wind speed (WS) data is crucial in analyzing and estimating WE potential. Once the best suitable statistical distribution for WS data is determined, WE potential and potential yield could...
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Review of Methods for Diagnosing the Degradation Process in Power Units Cooperating with Renewable Energy Sources Using Artificial Intelligence
PublicationThis work is based on a literature review (191). It mainly refers to two diagnostic methods based on artificial intelligence. This review presents new possibilities for using genetic algorithms (GAs) for diagnostic purposes in power plants transitioning to cooperation with renewable energy sources (RESs). The genetic method is rarely used directly in the modeling of thermal-flow analysis. However, this assignment proves that the...
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Uniwersalna metoda projektowania regulacji osi toru z wykorzystaniem pomiarów satelitarnych i optymalizacji
PublicationW 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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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Complex multidisciplinary optimization of turbine blading systems
PublicationThe 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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Genetic Programming for Interaction Efficient Supporting in Volunteer Computing Systems
PublicationVolunteer computing systems provide a middleware for interaction between project owners and great number volunteers. In this chapter, a genetic programming paradigm has been proposed to a multi-objective scheduler design for efficient using some resources of volunteer computers via the web. In a studied problem, genetic scheduler can optimize both a workload of a bottleneck computer and cost of system. Genetic programming has been...
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Decision making process using deep learning
PublicationEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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ANALIZA I PROJEKTOWANIE UKŁADÓW STEROWANIA STERAMI STRUMIENIOWYMI STATKÓW Z ZASTOSOWANIEM SYSTEMU Z BAZĄ WIEDZY
PublicationŚwiatowa literatura dostarcza przykładów wskazujących na aktualność tematyki związanej z wykorzystaniem elementów sztucznej inteligencji w zastosowaniach morskich. Komisja Europejska finansuje projekty mające na celu poprawę konkurencyjności przemysłu okrętowego. W rozprawie podjęto tematykę związaną ze wspomaganiem projektowania podsystemów elektroenergetycznych statków. W rozprawie udowodniono przyjętą na wstępie tezę pracy:...
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TDOA versus ATDOA for wide area multilateration system
PublicationThis paper outlines a new method of a location service (LCS) in the asynchronous wireless networks (AWNs) where the nodes (base stations) operate asynchronously in relation to one another. This method, called asynchronous time difference of arrival (ATDOA), enables the calculation of the position of the mobile object (MO) through the measurements taken by a set of non-synchronized fixed nodes and is based on the measurement of...
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Big Data Paradigm Developed in Volunteer Grid System with Genetic Programming Scheduler
PublicationArtificial intelligence techniques are capable to handle a large amount of information collected over the web. In this paper, big data paradigm has been studied in volunteer and grid system called Comcute that is optimized by a genetic programming scheduler. This scheduler can optimize load balancing and resource cost. Genetic programming optimizer has been applied for finding the Pareto solu-tions. Finally, some results from numerical...
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The Use of an Autoencoder in the Problem of Shepherding
PublicationThis paper refers to the problem of shepherding clusters of passive agents consisting of a large number of objects by a team of active agents. The problem of shepherding and the difficulties that arise with the increasing number of data describing the location of agents have been described. Several methods for reducing the dimensionality of data are presented. Selected autoencoding method using a Restricted Boltzmann Machine is...
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Genetic variations as predictors of dispositional and dyadic empathy - a couple study
PublicationBiological drivers of empathy have been explored in an interdisciplinary manner for decades. Research that merges the psychological and genetic perspectives of empathy has recently gained interest, and more complex designs and analyses are needed. Empathy is a multidimensional construct that might be regarded both dispositionally (as a personality trait) and contextually (experienced and/or expressed in a particular relationship/situation)....
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Conditions for increasing the recognition of degradation in thermal-flow diagnostics, taking into account environmental legal aspects
PublicationThe ever-increasing demand for electricity and the need for conventional sources to cooperate with renewable ones generates the need to increase the efficiency and safety of the generation sources. Therefore, it is necessary to find a way to operate existing facilities more efficiently with full detection of emerging faults. These are the requirements of Polish, European and International law, which demands that energy facilities...
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublicationIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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Using similar classification tasks in feature extractor learning
PublicationThe article presents and experimentally verify the idea of automatic construction of feature extractors in classification problems. The extractors are created by genetic programming techniques using classification examples taken from other problems then the problem under consideration.
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Relationship between Telomere Length, TERT Genetic Variability and TERT, TP53, SP1, MYC Gene Co-Expression in the Clinicopathological Profile of Breast Cancer
PublicationThe molecular mechanisms of telomerase reverse transcriptase (TERT) upregulation in breast cancer (BC) are complex. We compared genetic variability within TERT and telomere length with the clinical data of patients with BC. Additionally, we assessed the expression of the TERT, MYC, TP53 and SP1 genes in BC patients and in BC organoids (3D cell cultures obtained from breast cancer tissues). We observed the same correlation in the...
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On a Method of Efficiency Increasing in Kaplan Turbine
PublicationThis paper presents a method of increasing efficiency in Kaplan-type turbine. The method is based on blade profile optimisation together with modelling the interaction between rotor and stator blades. Loss coefficient was chosen as the optimisation criterion, which is related directly to efficiency. Global optimum was found by means of Genetic Algorithms, and Artificial Neural Networks were utilised for approximations to reduce...
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Solving highly-dimensional multi-objective optimization problems by means of genetic gender
PublicationPaper presents a computational optimization study using a genetic gender approach for solving multi-objective optimization problems of detection observers. In this methodology the information about an individual gender of all the considered solutions is applied for the purpose of making distinction between different groups of objectives. This information is drawn out of the fitness of individuals and applied during a current parental...
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Solving highly-dimensional multi-objective optimization problems by means of genetic gender
PublicationPaper presents a computational optimization study using a genetic gender approach for solving multi-objective optimization problems of detection observers. In this methodology the information about an individual gender of all the considered solutions is applied for the purpose of making distinction between different groups of objectives. This information is drawn out of the fitness of individuals and applied during a current parental...
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Pathogenesis of psoriasis in the “omic” era. Part II. Genetic, genomic and epigenetic changes in psoriasis
PublicationPsoriasis is a multifactorial disease in which genetic, environmental and epigenetic factors regulating gene expression play a key role. In the “genomic era”, genome-wide association studies together with target genotyping platforms performed in different ethnic populations have found more than 50 genetic susceptible markers associated with the risk of psoriasis which have been identified so far. Up till now, the strongest association...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublicationA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...