Search results for "HM"
showing 10 items of 10594 documents
Extreme Learning Machines for Data Classification Tuning by Improved Bat Algorithm
2018
Single hidden layer feed forward neural networks are widely used for various practical problems. However, the training process for determining synaptic weights of such neural networks can be computationally very expensive. In this paper we propose a new learning algorithm for learning the synaptic weights of the single hidden layer feedforward neural networks in order to reduce the learning time. We propose combining the upgraded bat algorithm with the extreme learning machine. The proposed approach reduces the number of evaluations needed to train a neural network and efficiently finds optimal input weights and the hidden biases. The proposed algorithm was tested on standard benchmark clas…
Kinematic synthesis of a new 3D printing solution
2016
Low-cost production of metal parts is a challenge nowadays in the Additive Manufacturing world and new methods are being developed. The MIM technique is an innovative approach for 3D printing. This method requires a machine with suitable kinematics capable of generating the adequate movements. The object of this article is the kinematic synthesis of a 5Dofs robot, based on two PKM machines, for additive manufacturing in order to compliant with the requirements of this new technology. Robot kinematics have been optimized by genetic algorithm in order to cover the required workspace and the design of the robot and outline of the control system are also given.
Collision detection for 3D rigid body motion planning with narrow passages
2017
In sampling-based 3D rigid body motion planning one of the major subroutines is collision detection. Especially for problems with narrow passages many samples have to be checked by a collision detection algorithm. In this application, the runtime of the motion planning algorithm is dominated by collision detection and the samples have the very specific characteristic that many of them are in collision and have small penetration volumes. In our work, we introduce a data structure and an algorithm that makes use of this characteristic by combining well-known data structures like a distance field and an octree with the swap algorithm by Llanas et al. For 3D rigid body motion planning with narr…
Additively manufactured textiles and parametric modelling by generative algorithms in orthopaedic applications
2020
Purpose The purpose of this paper is to implement a new process aimed at the design and production of orthopaedic devices fully manufacturable by additive manufacturing (AM). In this context, the use of generative algorithms for parametric modelling of additively manufactured textiles (AMTs) also has been investigated, and new modelling solutions have been proposed. Design/methodology/approach A new method for the design of customised elbow orthoses has been implemented. In particular, to better customise the elbow orthosis, a generative algorithm for parametric modelling and creation of a flexible structure, typical of an AMT, has been developed. Findings To test the developed modelling a…
Adjusted bat algorithm for tuning of support vector machine parameters
2016
Support vector machines are powerful and often used technique of supervised learning applied to classification. Quality of the constructed classifier can be improved by appropriate selection of the learning parameters. These parameters are often tuned using grid search with relatively large step. This optimization process can be done computationally more efficiently and more precisely using stochastic search metaheuristics. In this paper we propose adjusted bat algorithm for support vector machines parameter optimization and show that compared to the grid search it leads to a better classifier. We tested our approach on standard set of benchmark data sets from UCI machine learning repositor…
Algebraic parameter estimation of a multi-sinusoidal waveform signal from noisy data
2013
International audience; In this paper, we apply an algebraic method to estimate the amplitudes, phases and frequencies of a biased and noisy sum of complex exponential sinusoidal signals. Let us stress that the obtained estimates are integrals of the noisy measured signal: these integrals act as time-varying filters. Compared to usual approaches, our algebraic method provides a more robust estimation of these parameters within a fraction of the signal's period. We provide some computer simulations to demonstrate the efficiency of our method.
Algebraic parameter estimation of a biased sinusoidal waveform signal from noisy data
2012
International audience; The amplitude, frequency and phase of a biased and noisy sum of two complex exponential sinusoidal signals are estimated via new algebraic techniques providing a robust estimation within a fraction of the signal period. The methods that are popular today do not seem able to achieve such performances. The efficiency of our approach is illustrated by several computer simulations.
Global sensitivity analysis in welding simulations -- what are the material data you really need ?
2011
In this paper, the sensitivity analysis methodology is applied to numerical welding simulation in order to rank the importance of input variables on the outputs of the code like distorsions or residual stresses. The numerical welding simulation uses the finite element method, with a thermal computation followed by a mechanical one. Classically, a local sensitivity analysis is performed, hence the validity of the results is limited to the neighbourhood of a nominal point, and cross effects cannot be detected. This study implements a global sensitivity analysis which allows to screen the whole material space of the steel family mechanical properties. A set of inputs of the mechanical model-ma…
Identification of Objects Based on Generalized Amplitude-Phase Images Statistical Models
2017
The article presents the dynamical objects identification technology based on statistical models of amplitude-phase images (APIm) – multidimensional data arrays (semantic models) and statistical correlation analysis methods using the generalized discrete Hilbert transforms (DHT) – 2D Hilbert (Foucault) isotropic (HTI), anisotropic (HTA) and total transforms – AP-analysis (APA) to calculate the APIm. The identified objects are modeled with 3D airplanes templates rotated in space around the center of Cartesian coordinate system. The DHT domain system of coordinates displaying the plane projections (2D flat images) remains to be space-invariant. That causes the anisotropic properties of APIm a…
Tolerating malicious monitors in detecting misbehaving robots
2008
This paper considers a multi–agent system and focuses on the detection of motion misbehavior. Previous work by the authors proposed a solution, where agents act as local monitors of their neighbors and use locally sensed information as well as data received from other monitors. In this work, we consider possible failure of monitors that may send incorrect information to their neighbors due to spontaneous or even malicious malfunctioning. In this context, we propose a distributed software architecture that is able to tolerate such failures. Effectiveness of the proposed solution is shown through preliminary simulation results.