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Search results for: algorithms performance
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A Human Behaviour Model Agent for Testing of Voluntary Computing Systems
PublicationPaper presents a design and performance of a voluntary-based distributed computing system testing agent, implementing a human behaviour model. The agent, nicknamed iRobot, was designed and implemented to enable controlled, large scale testing of core algorithms of Comcute - a new voluntary distributed computing platform complementary to BOINC. The main agent design goals were: emulation of human behaviour when browsing web pages,...
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NVRAM as Main Storage of Parallel File System
PublicationModern cluster environments' main trouble used to be lack of computational power provided by CPUs and GPUs, but recently they suffer more and more from insufficient performance of input and output operations. Apart from better network infrastructure and more sophisticated processing algorithms, a lot of solutions base on emerging memory technologies. This paper presents evaluation of using non-volatile random-access memory as a...
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Active learning on stacked machine learning techniques for predicting compressive strength of alkali-activated ultra-high-performance concrete
PublicationConventional ultra-high performance concrete (UHPC) has excellent development potential. However, a significant quantity of CO2 is produced throughout the cement-making process, which is in contrary to the current worldwide trend of lowering emissions and conserving energy, thus restricting the further advancement of UHPC. Considering climate change and sustainability concerns, cementless, eco-friendly, alkali-activated UHPC (AA-UHPC)...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Model Management for Low-Computational-Budget Simulation-Based Optimization of Antenna Structures Using Nature-Inspired Algorithms
PublicationThe primary objective of this study is investigation of the possibilities of accelerating nature-inspired optimization of antenna structures using multi-fidelity EM simulation models. The primary methodology developed to achieve acceleration is a model management scheme which the level of EM simulation fidelity using two criteria: the convergence status of the optimization algorithm, and relative quality of the individual designs...
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Study of the Effectiveness of Model Order Reduction Algorithms in the Finite Element Method Analysis of Multi-port Microwave Structures
PublicationThe purpose of this paper is to investigate the effectiveness of model order reduction algorithms in finite element method analysis of multi-port microwave structures. Consideration is given to state of the art algorithms, i.e. compact reduced-basis method (CRBM), second-order Arnoldi method for passive-order reduction (SAPOR), reduced-basis methods (RBM) and subspace-splitting moment-matching MOR (SSMM-MOR)
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Generalized Formulation of Response Features for Reliable Optimization of Antenna Input Characteristics
PublicationElectromagnetic (EM)-driven parameter adjustment has become imperative in the design of modern antennas. It is necessary because the initial designs rendered through topology evolution, parameter sweeping, or theoretical models, are often of poor quality and need to be improved to satisfy stringent performance requirements. Given multiple objectives, constraints, and a typically large number of geometry parameters, the design closure...
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Deduplication of Position Data and Global Identification of Objects Tracked in Distributed Vessel Monitoring System
PublicationVessel monitoring systems (VMS) play a very important role in safety navigation. In most cases, their structure is distributed and they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Such approach results in several objects identification and position data duplication problems, which need to be solved in order to ensure the correct performance of a given VMS....
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublicationRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Expedited Optimization of Passive Microwave Devices Using Gradient Search and Principal Directions
PublicationOver the recent years, utilization of numerical optimization techniques has become ubiquitous in the design of high-frequency systems, including microwave passive components. The primary reason is that the circuits become increasingly complex to meet ever growing performance demands concerning their electrical performance, additional functionalities, as well as miniaturization. Nonetheless, as reliable evaluation of microwave device...
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A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublicationOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
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An electronic nose for quantitative determination of gas concentrations
PublicationThe practical application of human nose for fragrance recognition is severely limited by the fact that our sense of smell is subjective and gets tired easily. Consequen tly, there is considerable need for an instrument that can be a substitution of the human sense of smell. Electronic nose devices from the mid 1980s are used in growing number of applications. They comprise an array of several electrochemical gas sensors...
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Robustness analysis of watermarking-based dtd algorithm under time-variable echo conditions
PublicationA novel double-talk detection (DTD) algorithm based on techniques similar to those used for audio signal watermarking was introduced by the authors. The application of the described DTD algorithm within acoustic echo cancellation system is presented. The problem of DTD robustness to time-varying conditions of acoustic echo path is discussed and explanation as to why such conditions occur in practical situations is provided. The...
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Approximate Criteria for the Evaluation of Truly Multi-Dimensional Optimization Problems
PublicationIn this paper we propose new improved approximate quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO). In the performed comparative study we take into account the various EMO algorithms of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces. It is well known that useful executive criteria, such as those based on the true Pareto...
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Modeling of small molecule's affinity to phospholipids using IAM-HPLC and QSRR approach enhanced by similarity-based machine algorithms
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<title>Decomposition of MATLAB script for FPGA implementation of real time simulation algorithms for LLRF system in European XFEL</title>
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Mobility Management Solutions for IP Networks Comparative Analysis of IP-based Mobility Protocols and Handover Algorithms Invited Paper
PublicationA rapid growth of IP-based networks and services hascreated a vast collection of resources and functionalities availableto users by means of a uniform method of access offered by the IPprotocol. At the same time, advances in the design of mobileelectronic devices allowed them to reach a utility levelcomparable to desktop computers, while still retaining theirmobility advantage. Unfortunately, the base IP protocol does notperform...
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Dynamic Route Discovery Using Modified Grasshopper Optimization Algorithm in Wireless Ad-Hoc Visible Light Communication Network
PublicationIn 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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Computer vision techniques applied for reconstruction of seafloor 3D images from side scan and synthetic aperture sonars data
PublicationThe Side Scan Sonar and Synthetic Aperture Sonar are well known echo signal processing technologies that produce 2D images of the seafloor. Both systems combines a number of acoustic pings to form a high resolution image of seafloor. It was shown in numerous papers that 2D images acquired by such systems can be transformed into 3D models of seafloor surface by algorithmic approach using intensity information, contained in a grayscaled...
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Comparable analysis of PID controller settings in order to ensure reliable operation of active foil bearings
PublicationIn comparison to the traditional solutions, active bearings offer great operating flexibility, ensure better operating conditions over a wider range of rotational speeds and are safe to use. In order to ensure optimum bearing performance a bearing control system is used that adapts different geometries during device operation. The selection of optimal controller parameters requires the use of modern optimization methods that make...
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Expedited Feature-Based Quasi-Global Optimization of Multi-Band Antenna Input Characteristics with Jacobian Variability Tracking
PublicationDesign of modern antennas relies—for reliability reasons—on full-wave electromagnetic simulation tools. In addition, increasingly stringent specifications pertaining to electrical and field performance, growing complexity of antenna topologies, along with the necessity for handling multiple objectives, make numerical optimization of antenna geometry parameters a highly recommended design procedure. Conventional algorithms, particularly...
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Ochrona odbiorników GNSS przed zakłóceniami celowymi
PublicationArtykuł dotyczy zastosowania algorytmów przestrzennego cyfrowego przetwarzania sygnałów dla potrzeb selektywnej eliminacji sygnałów zakłócających pracę odbiorników nawigacji satelitarnej GNSS. Omówiono podatność tych odbiorników na ataki elektroniczne typu zagłuszanie oraz spoofing. Polegają one na celowej emisji sygnałów niepożądanych w paśmie pracy systemu. Następnie przedstawiono koncepcję przeciwdziałania tego rodzaju zakłóceniom...
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Multi-Taper-Based Automatic Correction of Non-Anechoic Antenna Measurements
PublicationPrototype measurements belong to the key steps in the development of antenna structures. Although accurate validation of their far-field performance can be realized in dedicated facilities, such as anechoic chambers, the high cost of their construction and maintenance might not be justified if the main goal of measurements is to support teaching or low-budget research. Instead, they can be performed in non-anechoic conditions and...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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<title>Cavity simulator and controller for VUV free electron laser SIMCON 2.1, part I: algorithms and SIMCON system</title>
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Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
PublicationAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state-of-the-art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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On ''cheap smoothing'' opportunities in identification of time-varying systems
PublicationIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate into the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Despite the possible performance improvements, the existing smoothing...
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Recognition of hazardous acoustic events employing parallel processing on a supercomputing cluster . Rozpoznawanie niebezpiecznych zdarzeń dźwiękowych z wykorzystaniem równoległego przetwarzania na klastrze superkomputerowym
PublicationA method for automatic recognition of hazardous acoustic events operating on a super computing cluster is introduced. The methods employed for detecting and classifying the acoustic events are outlined. The evaluation of the recognition engine is provided: both on the training set and using real-life signals. The algorithms yield sufficient performance in practical conditions to be employed in security surveillance systems. The...
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Face detection in image sequences using a portable thermal camera
PublicationFace detection is often a first step in quantitative analysis of face images. It is an important research area for visible images and recently also for thermography. Due to technological developments thermal cameras may be embedded into wearable devices to provide remote healthcare. In this paper, we compared three algorithms for face detection in thermal images by testing execution time, accuracy, symmetry ratio and false-positives....
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Data fusion of GPS sensors using Particle Kalman Filter for ship dynamic positioning system
PublicationDepending on standards and class, dynamically positioned ships make use of different numbers of redundant sensors to determine current ship position. The paper presents a multi-sensor data fusion algorithm for the dynamic positioning system which allows it to record the proper signal from a number of sensors (GPS receivers). In the research, the Particle Kalman Filter with data fusion was used to estimate the position of the vessel....
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Mobile Cloud computing architecture for massively parallelizablegeometric computation
PublicationCloud Computing is one of the most disruptive technologies of this century. This technology has been widely adopted in many areas of the society. In the field of manufacturing industry, it can be used to provide advantages in the execution of the complex geometric computation algorithms involved on CAD/CAM processes. The idea proposed in this research consists in outsourcing part of the load to be com- puted in the client machines...
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Self-optimizing generalized adaptive notch filters - comparison of three optimization strategies
PublicationThe paper provides comparison of three different approaches to on-line tuning of generalized adaptive notch filters (GANFs) the algorithms used for identification/tracking of quasi-periodically varying dynamic systems. Tuning is needed to adjust adaptation gains, which control tracking performance of ANF algorithms, to the unknown and/or time time-varying rate of system nonstationarity. Two out ofthree compared approaches are classical...
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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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5G Millimeter Wave Network Optimization: Dual Connectivity and Power Allocation Strategy
PublicationThe fifth generation (5G) of mobile networks utilizing millimeter Wave (mmWave) bands can be considered the leading player in meeting the continuously increasing hunger of the end user demands in the near future. However, 5G networks are characterized by high power consumption, which poses a significant challenge to the efficient management of base stations (BSs) and user association. Implementing new power consumption and user...
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Evaluation of Workflow Runtime Platforms in Service Composition
PublicationTypically, workflow applications are constructed from basic functionalities that may be realized by alternative services deployed in heterogeneous runtime platforms. Depending on workflow structure and selection of services, the applications differ in attributes such as price, Quality of Service (QoS) and others. In the paper, we propose a method of evaluation of workflow runtime platforms using Data Envelopment Analysis. We present...
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Sensorless induction motor drive with voltage inverter and sine-wave filter
PublicationThis paper presents a speed sensorless control system of an induction motor with an output LC filter. It is known that the parameters design of the filter gives sine wave motor supply voltage but complicates control and estimation process. The reason is that the voltage drop and phase shift between filter input and output signals are imposed, and hence the motor voltages and currents differ from the inverter output waveforms. To...
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Application of Web-GIS and Cloud Computing to Automatic Satellite Image Correction
PublicationRadiometric calibration of satellite imagery requires coupling of atmospheric and topographic parameters, which constitutes serious computational problems in particular in complex geographical terrain. Successful application of topographic normalization algorithms for calibration purposes requires integration of several types of high-resolution geographic datasets and their processing in a common context. This paper presents the...
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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublicationNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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Optimization-Based High-Frequency Circuit Miniaturization through Implicit and Explicit Constraint Handling: Recent Advances
PublicationMiniaturization trends in high-frequency electronics have led to accommodation challenges in the integration of the corresponding components. Size reduction thereof has become a practical necessity. At the same time, the increasing performance demands imposed on electronic systems remain in conflict with component miniaturization. On the practical side, the challenges related to handling design constraints are aggravated by the...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground 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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Contactless Hearing Aid for Infants Employing Signal Processing Algorithms. [Bezkontaktowy aparat słuchowy dla niemowląt wykorzystujący algorytmy przetwarzania sygnału]
PublicationZaprojektowany bezkontaktowy aparat słuchowy umiejscawiany jest w łóżeczku niemowlęcia. Aparat składający się z matrycy 4 mikrofonów oraz prototypowej karty z procesorem DSP pracuje w polu swobodnym. Przetworzony sygnał mowy emitowany jest z wykorzystaniem miniaturowych głośników. Opracowane algorytmy pozwalają na elminację akustycznych sprzężeń zwrotnych, które mogą wystepować ze względu na niewielką odległość mikrofonów od głośników...
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<title>DOOCS and MatLab control environment for FPGA-based cavity simulator and controller in TESLA (SIMCON 2.1) part I: algorithms</title>
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Modified version of roulette selection for evolution algorithms - the fan selection.Zmodyfikowana wersja selekcji metodą ruletki dla algorytmów ewolucyjnych - selekcja ''wachlarzowa''.
PublicationW pracy przedstawiono zmodyfikowaną wersję selekcji metodą ruletki - selekcję ''wachlarzową''. Metoda ta polega na zwiększaniu prawdopodobieństw przeżycia lepszych osobników kosztem gorszych. Do testowania i oceny jakości proponowanej metody użyto funkcji testujących spotykanych w literaturze. Uzyskane wyniki selekcji wachlarzowej porównano z wynikami selekcji metodą ruletki i selekcji elitarystycznej.
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Artificial Intelligence in the Diagnosis of Onychomycosis—Literature Review
PublicationOnychomycosis is a common fungal nail infection that is difficult to diagnose due to its similarity to other nail conditions. Accurate identification is essential for effective treatment. The current gold standard methods include microscopic examination with potassium hydroxide, fungal cultures, and Periodic acid-Schiff biopsy staining. These conventional techniques, however, suffer from high turnover times, variable sensitivity,...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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A framework for automatic detection of abandoned luggage in airport terminal
PublicationA framework for automatic detection of events in a video stream transmitted from a monitoring system is presented. The framework is based on the widely used background subtraction and object tracking algorithms. The authors elaborated an algorithm for detection of left and removed objects based on mor-phological processing and edge detection. The event detection algorithm collects and analyzes data of all the moving objects in...
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Two Time-Scale Hierarchical Control of Integrated Quantity and Quality in Drinking Water Distribution Systems
PublicationThe paper considers a feedback optimising control of drinking water distribution systems (DWDS). Although the optimised pump and valves scheduling and disinfectant injection control attracted considerable attention over last two decades most of the contributions were limited to an open-loop optimisation repetitively performed during the DWDS operation. Also, while a strong interaction between the water quantity and quality exists...