Integrating metaheuristics and artificial neural networks for improved stock price prediction
Stock market price is one of the most important indicators of a country's economic growth.
That's why determining the exact movements of stock market price is considerably regarded …
That's why determining the exact movements of stock market price is considerably regarded …
Fuzzy, neural network and expert systems methodologies and applications-a review
R Ul Amin, L Aijun, MM Ali - Journal of Mobile Multimedia, 2015 - dl.acm.org
The rapid growth in the field of artificial intelligence from past one decade has a significant
impact on various application areas ie health, security, home appliances among many. In …
impact on various application areas ie health, security, home appliances among many. In …
Neural network-based overallocation for improved energy-efficiency in real-time cloud environments
This paper introduces a dynamic resource provisioning mechanism for over allocating the
capacity of Cloud data centers based on customer resource utilization patterns. The …
capacity of Cloud data centers based on customer resource utilization patterns. The …
Real-time edge-enhanced dynamic correlation and predictive open-loop car-following control for robust tracking
We present a robust framework for a real-time visual tracking system, based on a BPNN-
controlled fast normalized correlation (BCFNC) algorithm and a predictive open-loop car …
controlled fast normalized correlation (BCFNC) algorithm and a predictive open-loop car …
Online adaptive radial basis function networks for robust object tracking
Visual tracking has been a challenging problem in computer vision over the decades. The
applications of visual tracking are far-reaching, ranging from surveillance and monitoring to …
applications of visual tracking are far-reaching, ranging from surveillance and monitoring to …
Distributed classification of traffic anomalies using microscopic traffic variables
S Thajchayapong, ES Garcia-Trevino… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
This paper proposes a novel anomaly classification algorithm that can be deployed in a
distributed manner and utilizes microscopic traffic variables shared by neighboring vehicles …
distributed manner and utilizes microscopic traffic variables shared by neighboring vehicles …
Smart lightning detection system for smart-city infrastructure using artificial neural network
Smart city infrastructure for lightning detection is one of the most important parameters for
building protection. To get outcomes within a short frame of time having high accuracy …
building protection. To get outcomes within a short frame of time having high accuracy …
[PDF][PDF] Efficient object tracking using optimized K-means segmentation and radial basis function neural networks
In this paper, an improved method for object tracking is proposed using Radial Basis
Function Neural Networks. Optimized k-means color segmentation is employed for detecting …
Function Neural Networks. Optimized k-means color segmentation is employed for detecting …
The application of machine learning in the corona era, with an emphasis on economic concepts and sustainable development goals
MS Farahani, A Esfahani… - International journal of …, 2022 - scipublications.com
The aim of this article is to examine the impacts of Coronavirus Disease-19 (Covid-19)
vaccines on economic condition and sustainable development goals. In other words, we are …
vaccines on economic condition and sustainable development goals. In other words, we are …
Real-time FPGA-based object tracker with automatic pan-tilt features for smart video surveillance systems
The design of smart video surveillance systems is an active research field among the
computer vision community because of their ability to perform automatic scene analysis by …
computer vision community because of their ability to perform automatic scene analysis by …