Search results for "decision tree"
showing 10 items of 170 documents
Towards online bearing fault detection using envelope analysis of vibration signal and decision tree classification algorithm
2017
Online bearing fault detection is an important method for monitoring the health status of bearings in critical machines. This work proposes a classification algorithm, which can be extended towards an online bearing fault detection. The objective is to detect and classify the bearing faults in early stages. The overall design aspects of the online bearing fault detection and classification system are discussed. The proposed method is validated using experimental data, and a high accuracy of the fault classification was observed. Therefore, the proposed method can be applied for an online early fault detection and classification system.
Land cover classification of VHR airborne images for citrus grove identification
2011
Abstract Managing land resources using remote sensing techniques is becoming a common practice. However, data analysis procedures should satisfy the high accuracy levels demanded by users (public or private companies and governments) in order to be extensively used. This paper presents a multi-stage classification scheme to update the citrus Geographical Information System (GIS) of the Comunidad Valenciana region (Spain). Spain is the first citrus fruit producer in Europe and the fourth in the world. In particular, citrus fruits represent 67% of the agricultural production in this region, with a total production of 4.24 million tons (campaign 2006–2007). The citrus GIS inventory, created in…
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 …
Modeling the Mechanical Behavior of the Breast Tissues Under Compression in Real Time
2017
This work presents a data-driven model to simulate the mechanical behavior of the breast tissues in real time. The aim of this model is to speed up some multimodal registration algorithms, as well as some image-guided interventions. Ten virtual breast phantoms were used in this work. Their deformation during a mammography was performed off-line using the finite element method. Three machine learning models were trained with the data from those simulations. Then, they were used to predict the deformation of the breast tissues. The models were a decision tree and two ensemble methods (extremely randomized trees and random forest). Four experiments were designed to assess the performance of th…
Towards Responsible AI for Financial Transactions
2020
Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The application of AI in finance is increasingly dependent on the principles of responsible AI. These principles-explainability, fairness, privacy, accountability, transparency and soundness form the basis for trust in future AI systems. In this empirical study, we address the first p…
Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications
2019
Medical applications challenge today's text categorization techniques by demanding both high accuracy and ease-of-interpretation. Although deep learning has provided a leap ahead in accuracy, this leap comes at the sacrifice of interpretability. To address this accuracy-interpretability challenge, we here introduce, for the first time, a text categorization approach that leverages the recently introduced Tsetlin Machine. In all brevity, we represent the terms of a text as propositional variables. From these, we capture categories using simple propositional formulae, such as: if "rash" and "reaction" and "penicillin" then Allergy. The Tsetlin Machine learns these formulae from a labelled tex…
Finding k -dissimilar paths with minimum collective length
2018
Shortest path computation is a fundamental problem in road networks. However, in many real-world scenarios, determining solely the shortest path is not enough. In this paper, we study the problem of finding k-Dissimilar Paths with Minimum Collective Length (kDPwML), which aims at computing a set of paths from a source s to a target t such that all paths are pairwise dissimilar by at least \theta and the sum of the path lengths is minimal. We introduce an exact algorithm for the kDPwML problem, which iterates over all possible s-t paths while employing two pruning techniques to reduce the prohibitively expensive computational cost. To achieve scalability, we also define the much smaller set …
Plaid model for microarray data: an enhancement of the pruning step
2010
Microarrays have become a standard tool for studying gene functions. For example, we can investigate if a subset of genes shows a coherent expression pattern under different conditions. The plaid model, a model-based biclustering method, can be used to incorporate the addiction structure used for the microarray experiment. In this paper we describe an enhancement for the plaid model algorithm based on the theory of the false discovery rate.
TREEZZY2, a Fuzzy Logic Computer Code for Fault Tree and Event Tree Analyses
2004
In conventional approach to reliability analysis using logical trees methodologies, uncertainties in system components or basic events failure probabilities are approached by assuming probability distribution functions. However, data are often insufficient for statistical estimation, and therefore it is required to resort to approximate estimations. Moreover, complicate calculations are needed to propagate uncertainties up to the final results. In our work, in order to take account of the uncertainties in system failure probabilities, the methodology based on fuzzy sets theory is used both in fault tree and event tree analyses. This paper just presents our work in this issue, which resulted…
Polish is quantitatively different on quartzite flakes used on different worked materials.
2020
Metrology has been successfully used in the last decade to quantify use-wear on stone tools. Such techniques have been mostly applied to fine-grained rocks (chert), while studies on coarse-grained raw materials have been relatively infrequent. In this study, confocal microscopy was employed to investigate polished surfaces on a coarse-grained lithology, quartzite. Wear originating from contact with five different worked materials were classified in a data-driven approach using machine learning. Two different classifiers, a decision tree and a support-vector machine, were used to assign the different textures to a worked material based on a selected number of parameters (Mean density of furr…