Search results for: ENSEMBLE FORECAST
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Inflation Forecast or Forecast(s) Targeting?
PublicationThe paper refers to L.E.O. Svensson’s concept of inflation forecast targeting (IFT) and its implementation by central banks of Sweden, Norway and the Czech Republic. The study focuses on (1) inflation forecasts published by selected central banks, i.e.headline inflation and core or monetary policy-relevant (MPR) inflation, which are made on the assumption of endogenous instrument rate, (2) one-year consumer...
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Ensemble Classifier for Mining Data Streams
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Equilibrium price - modelling, forecast and application
PublicationNowoczesną gospodarkę charakteryzuje wzrastające znaczenie cen. Znajomość ogólnych zasad mechanizmu kształtującego ceny oraz analizy cen umożliwiają przedsiębiorstwom przewidzenie ceny równowagi i podjęcie przynoszącej zyski decyzji, zwłaszcza na rynku oligopolu homogenicznego, gdzie przedsiębiorcy muszą brać pod uwagę reakcję konkurencji. Przedstawiony w artykule, dynamiczny model ekonometryczny cen benzyny, na rynku paliw płynnych...
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CONSUMERS’ APPROACH TO THE CREDIBILITY OF THE INFLATION FORECASTS PUBLISHED BY CENTRAL BANKS: A NEW METHODOLOGICAL SOLUTION
PublicationModern monetary policy focuses on credibility and shaping inflation expectations. In keeping with the concept of inflation forecast targeting, the inflation forecasts published by central banks play a crucial role in the instrument rate decision-making process and may be treated as a specific intermediate target. This study proposes an inflation forecast credibility index, the scope of which is narrowed to non-specialists’ approach...
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Agent-Based Data Reduction Using Ensemble Technique
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EBE: elastic blob ensemble for coarse human tracking
PublicationProponujemy nowy probabilistyczny algorytm śledzenia oparty na elastycznym zespole kropelkowym (EBE), który ma zastosowanie przy śledzeniu obiektów elastycznych. Wynikiem jest wskazówka nt. zgrubnego ruchu w postaci lokalizacji i orientacji obiektu wraz z lokalizacją kropelki. Głównym założeniem jest to, że orientacja całego obiektu nie zmienia się znacznie między sąsiednimi klatkami. Dyskretna przestrzeń rozwiązań jest tworzona...
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Electrochemistry from first-principles in the grand canonical ensemble
PublicationProgress in electrochemical technologies, such as automotive batteries, supercapacitors, and fuel cells, depends greatly on developing improved charged interfaces between electrodes and electrolytes. The rational development of such interfaces can benefit from the atomistic understanding of the materials involved by first-principles quantum mechanical simulations with Density Functional Theory (DFT). However, such simulations are...
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The point forecast of the situation of the examined company on the market
PublicationOkreślono sytuację badanego przedsiębiorstwa na rynku za pomocą analizy portfolio, w aspektach wzrostu rynku oraz względnego udziału badanego przedsiębiorstwa w rynku. Analiza objęła zarówno okres retrospektywny jak i prognozowany.
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GIS Solution for Weather Forecast Data Analysis
PublicationIn this paper authors present the GIS system for the analysis of the numerical weather prediction data. This kind of data has multidimensional character (three dimensions and time) and its analysis should consider all the available factors. Proposed GIS system consists of RASDAMAN application with implemented OLAP cube mechanism, which enables the user to process data in the spatial-time domain. It also simplifies the meteorological...
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Diabetes Forecast
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Heterogeneous Ensemble with Combined Dimensionality Reduction for Social Spam Detection
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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SMOTE-Based Homogeneous Ensemble Methods for Software Defect Prediction
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Ensemble-Based Logistic Model Trees for Website Phishing Detection
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Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublicationClass-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...
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Estimation of a Stochastic Burgers' Equation Using an Ensemble Kalman Filter
PublicationIn this work, we consider a difficult problem of state estimation of nonlinear stochastic partial differential equations (SPDE) based on uncertain measurements. The presented solution uses the method of lines (MoL), which allows us to discretize a stochastic partial differential equation in a spatial dimension and represent it as a system of coupled continuous-time ordinary stochastic differential equations (SDE). For such a system...
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Reliability of quality forecast for hybrid metal-working machinery
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REVIEW OF WEATHER FORECAST SERVICES FOR SHIP ROUTING PURPOSES
PublicationWeather data is nowadays used in a variety of navigational and ocean engineering research problems: from the obvious ones like voyage planning and routing of sea-going vessels, through the analysis of stability-related phenomena, to detailed modelling of ships’ manoeuvrability for collision avoidance purposes. Apart from that, weather forecasts are essential for passenger cruises and fishing vessels that want to avoid the risk...
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Tree-based homogeneous ensemble model with feature selection for diabetic retinopathy prediction
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Multidimensional Feature Selection and Interaction Mining with Decision Tree Based Ensemble Methods
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
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Segmentation-Based BI-RADS Ensemble Classification of Breast Tumours in Ultrasound Images
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Study of preference for surround microphone techniques, used in the recording of choir and instrumental ensemble
PublicationThe aim of this paper is to describe the process of choosing the best surround microphone technique for recording of choir with an instrumental ensemble. First, examples of multichannel microphone techniques including those used in the recording are described. Then, the assumptions and details of music recording in Radio Gdansk Studio are provided as well as the process of mixing of the multichannel recording. The extensive subjective...
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Forecasts of the managed futures market – an empirical analysis
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Ensemble Online Classifier Based on the One-Class Base Classifiers for Mining Data Streams
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Comparison of single best artificial neural network and neural network ensemble in modeling of palladium microextraction
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The forecasts-based instrument rule and decision making. How closely interlinked? The case of Sweden
PublicationResearch background: The Central Bank of Sweden declared in years 1999–2006 the implementation of the Svensson’s concept of inflation forecast targeting (IFT). It means that the repo rate decision-making process depends on the inflation forecasts. The concept evolved from the strict IFT with the decision-making algorithm called ‘the rule of thumb’ to the flexible IFT. Purpose of the article: The aim of...
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Effect of Active Mining Impact On Properties with Engineering Structures – Forecast and Final Result Discrepancies
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Accurate modeling of layout parasitic to forecast EMI emitted from a DC-DC converter.
PublicationThis paper illustrates how to account for all parasitic due to the layout of a power converter (inductive and capacitive), in order to forecast electromagnetic interferences (EMI). The method is generic, and is validated here in the simple example of a DC-DC converter, realized on different technologies: insulated metal substrate (IMS), printed circuit board (PCB). In addition, several layouts aspects will be investigated. Conclusions...
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Can Inflation Forecast and Monetary Policy Path be Really Useful? The Case of the Czech Republic
PublicationProducing and revealing inflation forecast is belie ved to be the best way of implementing a forward-looking monetary policy. The article focuses on inflation forecast targeting (IFT) at the Czech National Bank (CNB) in terms of its efficiency in shaping consumers’ inflation expectations. The goal of the study is to verify the accuracy of the inflation forecasts, and their influence on inflation...
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High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model
PublicationDue to climate change and associated longer and more frequent droughts, the risk of forest fires increases. To address this, the Institute of Meteorology and Water Management implemented a system for forecasting fire weather in Poland. The Fire Weather Index (FWI) system, developed in Canada, has been adapted to work with meteorological fields derived from the high-resolution (2.5 km) Weather Research and Forecasting (WRF) model....
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublicationThe 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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Prediction of consumer electricity needs based on Internet weather forecasts
PublicationElectrical energy is considered both as an important driver for producing and transporting goods in companies, as well as a good in itself which requires planning and management for generating and delivering it to consumers in proper time and amounts. Weather information can be considered to convey part of the data on energy delivery needs of consumers. Free meteorological data sources on the Web do not offer consistent data to...
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Forest Degradation Prevention
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Effect of Forecast Climate Changes on Water Needs of Giant Miscanthus Cultivated in the Kuyavia Region in Poland
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublicationMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublicationThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Short clinically-based prediction model to forecast transition to psychosis in individuals at clinical high risk state
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Impact of Investments and R&D Costs in Renewable Energy Technologies on Companies’ Profitability Indicators: Assessment and Forecast
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublicationTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Białowieża Forest: A new threat
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ADAPTIVE PREDICTIONS OF THE EURO/ZŁOTY CURRENCY EXCHANGE RATE USING STATE SPACE WAVELET NETWORKS AND FORECAST COMBINATIONS
PublicationThe paper considers the forecasting of the euro/Polish złoty (EUR/PLN) spot exchange rate by applying state space wavelet network and econometric forecast combination models. Both prediction methods are applied to produce one-trading-day- ahead forecasts of the EUR/PLN exchange rate. The paper presents the general state space wavelet network and forecast combination models as well as their underlying principles. The state space...
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Weighted Ensemble with one-class Classification and Over-sampling and Instance selection (WECOI): An approach for learning from imbalanced data streams
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INFLUENCE OF TIME ON THE BEARING CAPACITY OF PRECAST PILES
PublicationOne of the most popular types of foundations in layered subsoil with very differentiated soil shear strengths are precast piles. One of the reasons is a fact that we can well control the driving process during the installation of these piles. The principles of the assessment of bearing capacity and settlements of the piles given by Eurocode 7, concentrate on two main methods, i.e. Static Pile Load Tests (SPLT) and Dynamic Driving...