Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- research-articleNovember 2023
H-Storm: A Hybrid CPU-FPGA Architecture to Accelerate Apache Storm
AbstractThe era of big data has led to the exponential growth of the amount of real-time data. Nowadays, traditional centralized solutions and parallelism techniques in distributed systems cannot satisfy the processing requirements of emerging ...
- research-articleFebruary 2024
Multi-step-ahead stock price prediction using recurrent fuzzy neural network and variational mode decomposition
AbstractFinancial time series prediction has attracted considerable interest from scholars, and several approaches have been developed. Among them, decomposition-based methods have achieved promising results. Most decomposition-based methods approximate ...
Highlights- Two novel time series prediction methods, DCT-MFRFNN and VMD-MFRFNN, are proposed.
- For the first time, the gradient descent method is used to train MFRFNN.
- HSI, SSE, and S&P500 financial time series are used as the benchmark.
- ...
- research-articleOctober 2022
MFRFNN: Multi-Functional Recurrent Fuzzy Neural Network for Chaotic Time Series Prediction
Neurocomputing (NEUROC), Volume 507, Issue CPages 292–310https://doi.org/10.1016/j.neucom.2022.08.032AbstractChaotic time series prediction, a challenging research topic in dynamic system modeling, has drawn great attention from researchers around the world. In recent years extensive researches have been done on developing chaotic time series ...
- research-articleOctober 2022
Classification of Breast Tumors Based on Histopathology Images Using Deep Features and Ensemble of Gradient Boosting Methods
Computers and Electrical Engineering (CENG), Volume 103, Issue Chttps://doi.org/10.1016/j.compeleceng.2022.108382AbstractBreast cancer is the most common cancer among women worldwide. Early-stage diagnosis of this disease can significantly improve the efficiency of treatment. Computer-Aided Diagnosis (CAD) Systems are adopted widely in this regard due to ...
Graphical abstractDisplay Omitted
Highlights- A novel deep feature transfer learning model, called IRv2-CXL, is proposed.
- ...
- research-articleJune 2022
Semantic schema based genetic programming for symbolic regression
AbstractDespite the empirical success of Genetic programming (GP) in various symbolic regression applications, GP is not still known as a reliable problem-solving technique in this domain. Non-locality of GP representation and operators causes ...
Highlights- In contrast to natural evolution, genetic programming evolution is not gradual.
- research-articleJanuary 2022
A Novel Framework Based on Deep Learning and ANOVA Feature Selection Method for Diagnosis of COVID-19 Cases from Chest X-Ray Images
Background and Objective. The new coronavirus disease (known as COVID-19) was first identified in Wuhan and quickly spread worldwide, wreaking havoc on the economy and people’s everyday lives. As the number of COVID-19 cases is rapidly increasing, a ...
- research-articleSeptember 2018
A Survey of Distributed Stream Processing Systems for Smart City Data Analytics
SCIOT '18: Proceedings of the international conference on smart cities and internet of thingsArticle No.: 12, Pages 1–7https://doi.org/10.1145/3269961.3282845The widespread grow of big data and the evolution of Internet of Things (IoT) technologies enable cities to obtain valuable intelligence from a large amount of real-time produced data. In a Smart City various IoT devices generate data continuously which ...