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This papers proposes two novel approaches for the identification of Takagi-Sugeno fuzzy models with time variant and invariant features. The proposed Mixed Fuzzy Clustering algorithm is proposed for determining the parameters of Takagi-Sugeno fuzzy models in two different ways: (1) the antecedent fuzzy sets are determined based on the partition matrix generated by the Mixed Fuzzy Clustering algorithm;...
This work proposes a methodology for predicting the typical daily load profile of electricity usage based on static data obtained from surveys. The methodology intends to: (1) determine consumer segments based on the metering data using the k-means clustering algorithm, (2) correlate survey data to the segments, and (3) develop statistical and machine learning classification models to predict the...
A modelling method for a complex wind turbine tower manufacturing plant is proposed, through the specification of the major assumptions in the model. Using this methodology a DES model was developed, and a sensitivity analysis to some of the main process variables accounted for in the model is presented. From this study several versions of the model were developed, and their results are compared against...
This paper proposes a novel feature selection approach formulated based on the Fish School Search (FSS) optimization algorithm, intended to cope with premature convergence. In order to use this population based optimization algorithm in feature selection problems, we propose the use of a binary encoding scheme for the internal mechanisms of the fish school search, emerging the binary fish school search...
The aim of this work is to identify groups of patients with similar patterns that are related to a higher risk of readmission to an Intensive Care Unit (ICU). Patients readmissions to ICUs are introduced as a problem associated with increased mortality, morbidity and costs, which complicates the performance of a good clinical management and medical diagnosis. To approach the readmissions classification...
Shock is a life-threatening medical condition requiring the administration of powerful drugs - vasopressors. Early identification of these patients is a worthy goal in order to timely prepare them for therapy.
The amount of data generated in the intensive care environment nowadays prohibits the storage of all the information available. The validation process is time consuming, since nurses have to check every certain periods the data acquired from bedside monitors in order to assess their validity and integrity. This work presents an automatic method for data validation in the intensive care environment,...
Laboratory testing is a frequent activity for patients in intensive care units (ICU). Recent studies demonstrate that frequent laboratory testing does not necessarily relate to better outcomes. We hypothesize that unnecessary laboratory testing can be reduced by predicting which tests are unlikely to influence clinical management. Reducing unnecessary tests could reduce morbidity and hospitalization...
Vasopressors belong to a powerful class of drugs used in the management of systemic shock in ill patients. The administration of a vasopressor involves the non-trivial process of inserting a central venous catheter. This procedure carries with it inherent risks which are increased when done under urgency such as in the case of unexpected systemic shock. The ability to predict the transition to vasopressor...
Real-world databases often contain missing data and existing correction algorithms deliver varying performance. Also, most modeling techniques are not suitable to deal with them automatically. In this study we examine different approaches to predicting septic shock in the presence of missing data. Some preprocessing techniques for managing missing data include disregarding data, or replacing it with...
Real word data sets often contain many missing elements. Most algorithms that automatically develop a rule-based model are not well suited to deal with incomplete data. The usual technique is to disregard the missing values or substitute them by a best guess estimate, which can bias the results. In this paper we propose a new method for estimating the parameters of a Takagi-Sugeno fuzzy model in the...
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