Search results for "decision tree"

Boosting Design Space Explorations with Existing or Automatically Learned Knowledge

2012

During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with heuristic algorithms are a helpful approach to find the best settings for these parameters according to multiple objectives, e.g. performance, energy consumption, or real-time constraints. But if the setup is slightly changed and a new DSE has to be performed, it will start from scratch, resulting in very long evaluation times. To reduce the evaluation times we extend the NSGA-II algorithm in this article, such that automatic DSEs can be supported with a set of transformation rules defined in a highly readable format, the fuz…

Assembly Assistance System with Decision Trees and Ensemble Learning

2021

This paper presents different prediction methods based on decision tree and ensemble learning to suggest possible next assembly steps. The predictor is designed to be a component of a sensor-based assembly assistance system whose goal is to provide support via adaptive instructions, considering the assembly progress and, in the future, the estimation of user emotions during training. The assembly assistance station supports inexperienced manufacturing workers, but it can be useful in assisting experienced workers, too. The proposed predictors are evaluated on the data collected in experiments involving both trainees and manufacturing workers, as well as on a mixed dataset, and are compared …

2020

Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms. For this goal, due to the importance of various geo-environmental and soil properties in the evolution and creation of piping erosion, 18 variables were considered for modeling the piping erosion susceptibility in the Zarandieh watershed. A total of 152 points of piping erosion were recognized in the study area that…

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

2019

Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural ne…

Analysing urban development with decision tree based cellular automata. Toward an automatic transition rule creation process.

2016

International audience

Maintenance therapy in gastro-oesophageal reflux disease.

2005

Gastro-oesophageal reflux disease (GORD) is a chronic condition. Symptom control and the maintenance of healing of erosive oesophagitis, if present, are important topics. In patients responding to a proton pump inhibitor (PPI) and showing no treatment symptoms it is appropriate to consider long-term treatment strategies, whether continuous, intermittent or on demand. Maintenance PPI therapy is well tolerated for up to 10 years of continuous use. Furthermore, tachyphylaxis does not occur during long-term maintenance PPI therapy. Previous concerns about risks of long-term PPI therapy in Heliobacter pylori-negative or H. pylori-positive patients have not materialized, while no cases of intesti…

Jason Intentional Learning: An Operational Semantics

2013

This paper introduces an operational semantics for defining Intentional Learning on Jason, the well known Java-based implementation of AgentSpeak(L). This semantics enables Jason to define agents capable of learning the reasons for adopting intentions based on their own experience. In this work, the use of the term Intentional Learning is strictly circumscribed to the practical rationality theory where plans are predefined and the target of the learning processes is to learn the reasons to adopt them as intentions. Top-Down Induction of Logical Decision Trees (TILDE) has proved to be a suitable mechanism for supporting learning on Jason: the first-order representation of TILDE is adequate t…

Cost-Effectiveness Analysis of Different Testing Strategies that Use Antibody Levels to Detect Chronic Hepatitis C in Blood Donors.

2016

Aim. We conducted a cost-effectiveness analysis of seven hepatitis C virus (HCV) testing strategies in blood donors. Methods. Three of the seven strategies were based on HCV diagnosis and reporting guidelines in Mexico and four were from previous and current recommendations outlined by the CDC. The strategies that were evaluated determine antibody levels according to the signal-to-cut-off (S/CO) ratio and use reflex Immunoblot (IMB) or HCV RNA tests to confirm true positive (TP) cases of chronic HCV infection. Costs were calculated from the perspective of the Mexican Institute of Social Security (IMSS). A decision tree model was developed to estimate the expected number of true positive cas…

STRATEGY TO INCREASE THE FARM COMPETITIVENESS

2014

Italy’s wine-growing production structure is highly pulverized. So, for many wine-growing farms loweri ng the production cost represents the only way of gain ing a competitive advantage. Production at average unit costs lower than competitors allows to improve prof itability. Among farming operations, winter pruning and tying of productive vine-branches require a high hu man labor. For this reason the paper presents the r esults of research conducted on a sample of Sicilian wine- producing farms in order to study the cost-effectiv eness to make the pruning and the subsequent ligation of productive branches with tools that facilitate the work. The economic analysis, after the determination o…

Load management for voltage security using probabilistic fuzzy decision tree method

2016

During contingency, load management is most important in planning, monitoring and controlling of power system. In transmission system, there is limit for controlling the reactive power in large size power network. In order to manage heavy loading on transmission, load management is necessary to avoid voltage collapse. This paper presents a methodology for load management considering voltage security assessment using probabilistic fuzzy decision tree (PFDT) technique. By using probabilistic fuzzy decision tree method, the load management is calculated in optimal manner in real time and insecure operating conditions are observed. With the help of this method, a real time load management plan …