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Estimation of parameters for the free-form machining with deep neural network
(IEEE, 2017)
Predictive Analytics is a crucial part of a Big Data application. Lately, developers have turned their attention to deep learning models due to their huge success in various implementations. Meanwhile, there is lack of ...
Automated generation of attack graphs using NVD
(Association for Computing Machinery, Inc., 2018)
Today’s computer networks are prone to sophisticated multi-step, multi-host attacks. Common approaches of identifying vulnerabilities and analyzing the security of such networks with naive methods such as counting the ...
Ontology-centric Data Modelling and Decision Support in Smart Grid Applications A Distribution Service Operator Perspective
(IEEE, 2014)
Conventional electricity distribution grids are getting smarter by coupling operation technologies with advanced information and communication technologies (ICT). This provides a better, reliable, cost effective and efficient ...
Feature diverse hierarchical classification of human gait with CW radar for assisted living
(Institution of Engineering and Technology, 2017-10-26)
Activity recognition and estimation of gait parameter are medically essential components of remote health monitoring systems that can improve quality of life, enable personalized treatments, acquire continual medical data ...
Load and PV Generation Forecast Based Cost Optimization for Nanogrids with PV and Battery
(Institute of Electrical and Electronics Engineers Inc., 2018-11-20)
Power system resiliency and robustness became major concerns of the system operators and researchers after the introduction of the smart grid concept. The improvements in the battery storage systems (BSS) and the photovoltaic ...
Deep Learning of Micro-Doppler Features for Aided and Unaided Gait Recognition
(IEEE, 2017)
Remote health monitoring is a topic that has gained increased interest as a way to improve the quality and reduce costs of health care, especially for the elderly. Falling is one of the leading causes for injury and death ...
An artificial neural network-based stock trading system using technical analysis and big data framework
(Association for Computing Machinery, Inc., 2017-04-13)
In this paper, a neural network-based stock price prediction and trading system using technical analysis indicators is presented. The model developed first converts the financial time series data into a series of buy-sell-hold ...
TN-RSI: Trend-Normalized RSI indicator for Stock Trading Systems with Evolutionary Computation
(ELSEVIER Science BV, 2014)
RSI is a commonly used indicator preferred by stock traders. However, even though it works well when the market is trendless, during bull or bear market conditions (when there is a clear trend) its performance degrades. ...
High quality clustering of big data and solving empty-clustering problem with an evolutionary hybrid algorithm
(IEEE, 2015)
Achieving high quality clustering is one of the most well-known problems in data mining. k-means is by far the most commonly used clustering algorithm. It converges fairly quickly, but achieving a good solution is not ...
Weather Data Analysis and Sensor Fault Detection Using An Extended IoT Framework with Semantics, Big Data, and Machine Learning
(IEEE, 2017)
In recent years, big data and Internet of Things (IoT) implementations started getting more attention. Researchers focused on developing big data analytics solutions using machine learning models. Machine learning is a ...
