Search results for "machine learning."
showing 10 items of 1455 documents
Linear vs. non-linear classification of winners, drawers and losers at FIFA World Cup 2014
2017
Purpose: Tactical analyses to distinguish between football teams that were more or less successful have been conducted up to now only by means of linear methods (like discriminant analysis). Concer...
Influence of raw data analysis for the use of neural networks for win farms productivity prediction
2011
In the last decade wind energy had a strong growth because of cost effectiveness of the technology and the high remunerative of investments.
Multipactor prediction with multi-carrier signals: Experimental results and discussions on the 20-gap-crossing rule
2014
This work analyzes the 20-gap crossing rule from a theoretical point of view. It has been found that, depending on some signal parameters, the 20-gap-crossing rule yields predictions laying between two limit cases: It may be either excessively conservative or closer to breakdown value with little (or nonexistent) margin. Such limit cases have been experimentally assessed with two test campaigns in C and Ku-bands. © 2014 European Association on Antennas and Propagation.
CAD-Based Training of an Expert System and a Hidden Markov Model for Obstacle Detection in an Industrial Robot Environment
2012
Abstract Deploying industrial robots in harsh outdoor environments require additional functionalities not currently provided. For instance, movement of standard industrial robots are pre-programmed to avoid collision. In dynamic and less structured environments, however, the need for online detection and avoidance of unmodelled objects arises. This paper focus on online obstacle detection using a laser sensor by proposing three different approaches, namely a CAD-based Expert System (ES) and two probabilistic methods based on a Hidden Markov Model (HMM) which requires observation based training. In addition, this paper contributes by providing a comparison between the CAD-based ES and the tw…
A Hybrid Machine Learning and Knowledge Based Approach to Limit Combinatorial Explosion in Biodegradation Prediction
2016
One of the main tasks in chemical industry regarding the sustainability of a product is the prediction of its environmental fate, i.e., its degradation products and pathways. Current methods for the prediction of biodegradation products and pathways of organic environmental pollutants either do not take into account domain knowledge or do not provide probability estimates. In this chapter, we propose a hybrid knowledge-based and machine learning-based approach to overcome these limitations in the context of the University of Minnesota Pathway Prediction System (UM-PPS). The proposed solution performs relative reasoning in a machine learning framework, and obtains one probability estimate fo…
SmartLeg: An intelligent active robotic prosthesis for lower-limb amputees
2011
In recent years, there has been a worldwide interest in improvement of mobility of people with lower limb amputation. In spite of significant development of new technologies during the last decade, commercial below-knee and above-knee prostheses are still energetically passive devices. However, many locomotive functions, like walking up stairs and slopes, need significant power in knee and ankle joints. The additional power for doing previously mentioned activities needs to be achieved by means of external energy sources, which should be integral prosthetic components. This paper presents preliminary investigations towards an active robotic prosthesis that could potentially enable people wi…
Pattern recognition in cyclic and discrete skills performance from inertial measurement units
2014
The aim of this study is to compare and validate an Inertial Measurement Unit (IMU) relative to an optic system, and to propose methods for pattern recognition to capture behavioural dynamics during sport performance. IMU validation was conducted by comparing the motions of the two arms of a compass, which was equipped with IMUs and reflective landmarks detected by a multi-camera system. Spearman’s rank correlation tests showed good correlations between the IMU and multi-camera system, especially when the angles were normalized. Bland-Altman plot, root mean square and the normalized pairwise variability index showed low differences between the two systems, confirming the good accuracy level…
A Memetic Differential Evolution in Filter Design for Defect Detection in Paper Production
2007
This article proposes a Memetic Differential Evolution (MDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. The MDE is an adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution (DE) with the exploitative features of two local searchers. The local searchers are adaptively activated by means of a novel control parameter which measures fitness diversity within the population. Numerical results show that the DE framework is efficient for the class of problems under study and employment of exploitative local searchers is helpful in supporting the DE explorative mechanism in avoid…
Emergent behaviors and scalability for multi-agent reinforcement learning-based pedestrian models
2017
This paper analyzes the emergent behaviors of pedestrian groups that learn through the multiagent reinforcement learning model developed in our group. Five scenarios studied in the pedestrian model literature, and with different levels of complexity, were simulated in order to analyze the robustness and the scalability of the model. Firstly, a reduced group of agents must learn by interaction with the environment in each scenario. In this phase, each agent learns its own kinematic controller, that will drive it at a simulation time. Secondly, the number of simulated agents is increased, in each scenario where agents have previously learnt, to test the appearance of emergent macroscopic beha…
Three-dimensional cardiac computational modelling: methods, features and applications
2015
[EN] The combination of computational models and biophysical simulations can help to interpret an array of experimental data and contribute to the understanding, diagnosis and treatment of complex diseases such as cardiac arrhythmias. For this reason, three-dimensional (3D) cardiac computational modelling is currently a rising field of research. The advance of medical imaging technology over the last decades has allowed the evolution from generic to patient-specific 3D cardiac models that faithfully represent the anatomy and different cardiac features of a given alive subject. Here we analyse sixty representative 3D cardiac computational models developed and published during the last fifty …