MODELLING MICROWAVE DEVICES USING ARTIFICIAL NEURAL NETWORKS / MIKROBANGŲ ĮTAISŲ MODELIAVIMAS, TAIKANT DIRBTINIŲ NEURONŲ TINKLUS

Artificial neural networks (ANN) have recently gained attention as fast and flexible equipment for modelling and designing microwave devices. The paper reviews the opportunities to use them for undertaking the tasks on the analysis and synthesis. The article focuses on what tasks might be solved using neural networks, what challenges might rise when using artificial neural networks for carrying out tasks on microwave devices and discusses problem-solving techniques for microwave devices with intermittent characteristics. Santrauka Nagrinėjamos dirbtinių neuronų tinklų taikymo galimybės mikrobangų įtaisams tirti. Apžvelgiami eksperimentiniai ir teoriniai darbai. Pateikiama apibendrinta informacija apie uždavinius, sprendžiamus taikant neuronų tinklus, problemas, kylančias dirbtinius neuronų tinklus taikant mikrobangų uždaviniams spręsti, ir problemų sprendimo būdus. Pateikiama bendra neuronų tinklų struktūra ir konkretūs neuronų tinklų naudojimo pavyzdžiai.

Download Full-text

AN ARTIFICIAL NEURAL NETWORKS MODEL FOR THE ESTIMATION OF FORMWORK LABOUR / DIRBTINIŲ NEURONINIŲ TINKLŲ MODELIS, KURIO PASKIRTIS – SKAIČIUOTI KLOJINIAMS SKIRTO DARBO APIMTIS

Journal of Civil Engineering and Management ◽

10.3846/13923730.2011.594154 ◽

2011 ◽

Vol 17 (3) ◽

pp. 340-347 ◽

Cited By ~ 22

Author(s):

S. Umit Dikmen ◽

Murat Sonmez

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Problem Solving ◽

Human Brain ◽

Field Measurements ◽

Reinforced Concrete Frame ◽

Concrete Frame ◽

Frame Buildings ◽

Actual Field ◽

Artificial Neural

Artificial Neural Networks (ANN) is a problem solving technique imitating the basic working principles of the human brain. The formwork labour cost constitutes an important part within the costs of the reinforced concrete frame buildings. This study suggests a method based on artificial neural networks developed for estimating the required manhours for the formwork activity of such buildings. The introduced method has been verified in the study with reference to the test conducted involving two case studies. In all cases, the model produced results reasonably close to actual field measurements. The model is a simple and quick tool for the estimators and planners to aid them in their work. Santrauka Dirbtiniai neuroniniai tinklai (DNT) – tai problemų sprendimo metodas, imituojantis pagrindinius žmogaus smegenų veiklos principus. Statant gelžbetoninius karkasinius pastatus, nemažą sąnaudų dalį sudaro klojinių ruošimas. Šiame tyrime siūlomas dirbtiniais neuroniniais tinklais pagrįstas metodas, kurio paskirtis – apskaičiuoti, kiek žmogaus darbo valandų reikės ruošti klojinius tokiuose pastatuose. Pristatomas metodas tyrimo metu patikrintas remiantis bandymu, susijusiu su dviem atvejo tyrimais. Visais atvejais modelio pateikti rezultatai buvo gana artimi faktiniams matavimams. Modelis – tai paprastas ir greitai naudojamas įrankis, kuris pravers sąmatininkams ir planuotojams.

Download Full-text

Supervised Learning with Artificial Neural Networks

Biologically Inspired Artificial Intelligence for Computer Games ◽

10.4018/978-1-59140-646-4.ch003 ◽

2008 ◽

pp. 24-40

Author(s):

Darryl Charles ◽

Colin Fyfe ◽

Daniel Livingstone ◽

Stephen McGlinchey

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Problem Solving ◽

Supervised Learning ◽

Learning Algorithms ◽

Theory And Practice ◽

Delta Rule ◽

Neural Learning ◽

Artificial Neural

In this chapter we will look at supervised learning in more detail, beginning with one of the simplest (and earliest) supervised neural learning algorithms – the Delta Rule. The objectives of this chapter are to provide a solid grounding in the theory and practice of problem solving with artificial neural networks – and an appreciation of some of the challenges and practicalities involved in their use.

Download Full-text