Search results for "evolutionary computation"
showing 10 items of 113 documents
Characterization and Modelization of Surface Net Radiation through Neural Networks
2010
Artificial neural networks have shown to be a powerful tool for system modeling in a wide range of applications. In this chapter, the focus is on neural network applications to obtain qualitative/quantitative relationships between meteorological and soil parameters and net radiation, the latter being a significant term of the surface energy balance equation. By using a Multilayer Perceptron model an artificial neural network based on the above mentioned parameters, net radiation was estimated over a vineyard crop. A comparison has been made between the estimates provided by the Multilayer Perceptron and a linear regression model that only uses solar incoming shortwave radiation as input par…
Industrial Scaled Automated Structural Testing with the Evolutionary Testing Tool
2010
Evolutionary testing has been researched and promising results have been presented. However, evolutionary testing has remained predominately a research-based activity not practiced within industry. Although attempts have been made, such as Daimler's Evolutionary Structural Test (EST) prototype, until now, no such tool has been suitable for industrial adoption. The European project EvoTest (IST-33472) team has been working from 2006 till2009 to improve this situation. This paper describes the final version of the Evolutionary Testing Framework (ETF) resulting from the EvoTest project. In specific we will present the EvoTest Structural Testing tool for fully automatic structural testing that …
The computational power of continuous time neural networks
1997
We investigate the computational power of continuous-time neural networks with Hopfield-type units. We prove that polynomial-size networks with saturated-linear response functions are at least as powerful as polynomially space-bounded Turing machines.
Computer-Aided Diagnosis System with Backpropagation Artificial Neural Network—Improving Human Readers Performance
2016
This article presents the results of a study into possibility of artificial neural networks (ANNs) to classify cancer changes in mammographic images. Today’s Computer-Aided Detection (CAD) systems cannot detect 100 % of pathological changes. One of the properties of an ANN is generalized information —it can identify not only learned data but also data that is similar to training set. The combination of CAD and ANN could give better result and help radiologists to take the right decision.
Multilayer neural networks: an experimental evaluation of on-line training methods
2004
Artificial neural networks (ANN) are inspired by the structure of biological neural networks and their ability to integrate knowledge and learning. In ANN training, the objective is to minimize the error over the training set. The most popular method for training these networks is back propagation, a gradient descent technique. Other non-linear optimization methods such as conjugate directions set or conjugate gradient have also been used for this purpose. Recently, metaheuristics such as simulated annealing, genetic algorithms or tabu search have been also adapted to this context.There are situations in which the necessary training data are being generated in real time and, an extensive tr…
"Table 4" of "Elliptic flow of charged particles in Pb-Pb collisions at 2.76 TeV"
2014
Integrated elliptic flow at sqrt(sNN) = 2.76 TeV for centrality 20-30%.
Forward Kinematic Modelling with Radial Basis Function Neural Network Tuned with a Novel Meta-Heuristic Algorithm for Robotic Manipulators
2022
The complexity of forward kinematic modelling increases with the increase in the degrees of freedom for a manipulator. To reduce the computational weight and time lag for desired output transformation, this paper proposes a forward kinematic model mapped with the help of the Radial Basis Function Neural Network (RBFNN) architecture tuned by a novel meta-heuristic algorithm, namely, the Cooperative Search Optimisation Algorithm (CSOA). The architecture presented is able to automatically learn the kinematic properties of the manipulator. Learning is accomplished iteratively based only on the observation of the input–output relationship. Related simulations are carried out on a 3-Degrees…
Publication Network Analysis of an Academic Family in Information Systems
2011
The study of scientific collaboration through network analysis can give interesting conclusions about the publication habits of a scientific community. Co-authorship networks represent scientific collaboration as a graph: nodes correspond to authors, edges between nodes mark joint publications (Newman 2001a,b). Scientific publishing is decentralized. Choices of co-authors and research topics are seldomly globally coordinated. Still, the structure of co-authorship networks is far from random. Co-authorship networks are governed by principles that are similar in other complex networks such as social networks (Wasserman and Faust 1994), networks of citations between scientific papers (Egghe an…
Towards Automatic Testing of Reference Point Based Interactive Methods
2016
In order to understand strengths and weaknesses of optimization algorithms, it is important to have access to different types of test problems, well defined performance indicators and analysis tools. Such tools are widely available for testing evolutionary multiobjective optimization algorithms. To our knowledge, there do not exist tools for analyzing the performance of interactive multiobjective optimization methods based on the reference point approach to communicating preference information. The main barrier to such tools is the involvement of human decision makers into interactive solution processes, which makes the performance of interactive methods dependent on the performance of huma…
Evolutionary approach to coverage testing of IEC 61499 function block applications
2015
The paper addresses the problem of coverage testing of industrial automation software represented in the IEC 61499 standard, one of the recent standards for distributed control system design. Contrary to model-based testing (MBT), the paper focuses on implementation coverage, not model coverage. An approach based on evolutionary algorithms is presented which generates coverage test suites for both basic and composite IEC 61499 function blocks. It employs two third-party tools, FBDK and EvoSuite. The evaluation of the approach was performed on a set of control applications for two lab-scale demonstration plants. Results show that the approach is applicable and shows good performance at least…