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Search results for: storm overflow · multinomial logistic regression · rainfall genesis · iman- conover method
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Application of Multinomial Logistic Regression to Model the Impact of Rainfall Genesis on the Performance of Storm Overflows: Case Study
PublicationIn this study, a mathematical model was proposed to analyze the performance of storm overfows. The model included the infuence of rainfall genesis on the duration of storm overfow, its volume, and the maximum instantaneous fow. The multinomial logistic regression model, which has not been used so far to model objects located in a stormwater system, was proposed to simulate the duration of storm overfow. The Iman–Conover method,...
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Simulation of the number of storm overflows considering changes in precipitation dynamics and the urbanisation of the catchment area: a probabilistic approach
PublicationThis paper presents a probabilistic methodology that allows the study of the interactions between changes in rainfall dynamics and impervious areas in urban catchment on a long- and short-term basis. The proposed probabilistic model predict future storm overflows while taking into account the dynamics of changes in impervious areas and rainfall. In this model, a logistic regression method was used to simulate overflow resulting...
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Advanced sensitivity analysis of the impact of the temporal distribution and intensity of rainfall on hydrograph parameters in urban catchments
PublicationKnowledge of the variability of the hydrograph of outflow from urban catchments is highly important for measurements and evaluation of the operation of sewer networks. Currently, hydrodynamic models are most frequently used for hydrograph modeling. Since a large number of their parameters have to be identified, there may be problems at the calibration stage. Hence, sensitivity analysis is used to limit the number of parameters....
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Development of cluster analysis methodology for identification of model rainfall hyetographs and its application at an urban precipitation field scale
PublicationDespite growing access to precipitation time series records at a high temporal scale, in hydrology, and particularly urban hydrology, engineers still design and model drainage systems using scenarios of rainfall temporal distributions predefined by means of model hyetographs. This creates the need for the availability of credible statistical methods for the development and verification of already locally applied model hyetographs....
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Lung perfusion parameters in the diagnosis of diabetic pulmonary microangiopathy
PublicationThis paper presents the role of perfusion computed tomography (pCT) in the diagnosis of diabetic pulmonary microangiopathy. Our previous works have shown that perfusion parameters are useful in the diagnosis of diabetic pulmonary microangiopathy. In this article we focus on conditions that are necessary for such the diagnosis and introduce method of classification no microangiopathy vs. microangiopathy based on logistic regression....
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Integrated model for the fast assessment of flood volume: Modelling – management, uncertainty and sensitivity analysis
PublicationThe specific flood volume is an important criterion for assessing the performance of sewage networks. It has been shown that its value is greatly influenced by the layout of the sewers in the catchment area, which is usually expressed by a fractal dimension. Currently, only mechanistic models (such as SWMM) enable the determination of the impact of the layout of the sewers on flooding volume, but they require additional and robust...
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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublicationThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational 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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Comparison of low-temperature cracks intensity on pavements with high modulus asphalt concrete and conventional asphalt concrete bases
PublicationHigh modulus asphalt concrete (HMAC) base courses provide very good resistance to rutting and fatigue but they can increase the risk of low-temperature cracking as compared with conventional asphalt concrete (AC). The article presents the comparison of these two road materials in terms of low-temperature cracking. The statistical method based on the ordered logistic regression model was used. The analysis was based on results of...
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Approval of an Arrangement in the Restructuring Proceedings and the Financial Condition of Companies Listed on the Stock Exchanges in Warsaw. Is There Any Relationship?
PublicationThis paper attempts to identify the financial indicators differentiating companies that are insolvent or at risk of insolvency and have successfully entered into an arrangement with their creditors from those that have not. In addition, a two-factor model for predicting the odds of an arrangement has been proposed. The research was conducted using a population of companies listed on stock exchanges in Warsaw that initiated restructuring...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment 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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Organisational Competence vs Transferability of Knowledge in Cluster Organisations and Technology Parks
PublicationPurpose. The main paper aims to evaluate the impact of organisational competence on knowledge and information flows within cluster organisations and technology parks, with particular emphasis on innovative content knowledge. The paper addresses the research question: “What set of competencies of cooperating companies allows access to information and knowledge in cluster and parks structures?" Methodology. The authors report their...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study
PublicationBackground: Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA)...