Results 41 to 50 of about 16,908,993 (362)

Artificial Neural Network (ANN) Based Fast and Accurate Inductor Modeling and Design

open access: yesIEEE Open Journal of Power Electronics, 2020
This paper analyzes the potential of Artificial Neural Networks (ANNs) for the modeling and optimization of magnetic components and, specifically, inductors.
T. Guillod   +2 more
semanticscholar   +1 more source

Review of Face Detection Systems Based Artificial Neural Networks Algorithms [PDF]

open access: yes, 2014
Face detection is one of the most relevant applications of image processing and biometric systems. Artificial neural networks (ANN) have been used in the field of image processing and pattern recognition.
AL-Allaf, Omaima N. A.
core   +2 more sources

Intelligent optical performance monitor using multi-task learning based artificial neural network

open access: yes, 2018
An intelligent optical performance monitor using multi-task learning based artificial neural network (MTL-ANN) is designed for simultaneous OSNR monitoring and modulation format identification (MFI).
Shu, * Liang   +5 more
core   +1 more source

Enhancing mechanical performance of MWCNT filler with jute/kenaf/glass composite: a statistical optimization study using RSM and ANN

open access: yesMaterials technology (New York, N.Y.)
Fibre sequencing greatly affects bending and hardness of fibre-reinforced composites. Fiber-matrix bonding, orientation, and sequencing boost composite strength, especially when nanoparticles are added to improve mechanical properties. Lining fibres with
S. Arunachalam   +5 more
semanticscholar   +1 more source

A Comparative Study of PSO-ANN, GA-ANN, ICA-ANN, and ABC-ANN in Estimating the Heating Load of Buildings’ Energy Efficiency for Smart City Planning

open access: yesApplied Sciences, 2019
Energy-efficiency is one of the critical issues in smart cities. It is an essential basis for optimizing smart cities planning. This study proposed four new artificial intelligence (AI) techniques for forecasting the heating load of buildings’ energy ...
L. Le, Hoang Nguyen, J. Dou, Jian Zhou
semanticscholar   +1 more source

پیش‌بینی ضریب پخش رطوبت موثر و انرژی مصرفی ویژه بادمجان در خشک‌کن پیوسته با استفاده از روش‌های جدید [PDF]

open access: yesمجله پژوهش‌های علوم و صنایع غذایی ایران, 2018
در این پژوهش، به‌منظور برآورد خواص خشک‌کردن بادمجان در یک خشک‌کن پیوسته از روش شبکه‌های عصبی مصنوعی (ANN)، الگوریتم بهینه‌سازی توده ذرات (PSO) و الگوریتم گرگ خاکستری (GWO) استفاده شد.
محمد کاوه   +3 more
doaj   +1 more source

Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)

open access: yes, 2018
Landslide is a natural hazard that results in many economic damages and human losses every year. Numerous researchers have studied landslide susceptibility mapping (LSM), each attempting to improve the accuracy of the final outputs.
B. Kalantar   +4 more
semanticscholar   +1 more source

Modelling of Nicotiana Tabacum L. Oil Biodiesel Production: Comparison of ANN and ANFIS

open access: yes, 2021
Among the modern computational techniques, the Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are preferred because of their ability to deal with non-linear modeling and complex stochastic dataset.
O. Samuel   +5 more
semanticscholar   +1 more source

Soft computing techniques for analysing the mechanical properties of egg shell powder-based concrete

open access: yesAdvances in Civil and Architectural Engineering
The construction industry is increasingly focused on sustainability to reduce environmental impact. Researchers are actively exploring alternative materials to replace clinker-based binders. This study specifically investigates the use of eggshell powder
Sanjay Sharma   +3 more
doaj   +1 more source

On the annihilators and attached primes of top local cohomology modules [PDF]

open access: yes, 2014
Let \frak a be an ideal of a commutative Noetherian ring R and M a finitely generated R-module. It is shown that {\rm Ann}_R(H_{\frak a}^{{\dim M}({\frak a}, M)}(M))= {\rm Ann}_R(M/T_R({\frak a}, M)), where T_R({\frak a}, M) is the largest submodule of M
Atazadeh, Ali   +2 more
core   +2 more sources

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