GitHub

MSTA: Multi Strategy Trading Algorithm

Main guidelines: Why will the algo work? Let us not forget how hard it is to predict asset returns. Here we will try to gain an edge over the market by cleverly combining different signals coming from ...
IEEE

BPFNN: Bayesian Probabilistic Fuzzy Neural Networks for Uncertainty-Aware Clustering and ...

Abstract: This article introduces the Bayesian probabilistic fuzzy neural network (BPFNN), a unified architecture designed to overcome the challenges of conventional ...
IEEE

Python Integration with HFSS to Design Vivaldi Antipodal Antennas Via Genetic Algorithm

Abstract: This paper presents the design of a rectangular slotted antipodal Vivaldi antenna (AVA) incorporating ridged substrate integrated waveguide (RSIW) structures for ultra-wideband (UWB) ...
Scientific Research Publishing

Research on Structural Damage Identification Method Based on Convolutional Neural Network ()

1 College of Finance and Commerce, Guangzhou Railway Polytechnic, Guangzhou, China. 2 School of Intelligent Construction and Civil Engineering, Zhongyuan University of Technology, Zhengzhou, China. 3 ...
ahajournals.org

Prognostic Significance and Associations of Neural Network–Derived Electrocardiographic ...

Subtle, prognostically important ECG features may not be apparent to physicians. In the course of supervised machine learning, thousands of ECG features are identified. These are not limited to ...
Nature

Forecasting stock prices changes using long-short term memory neural network with symbolic ...

Sharma, A., Bhuriya, D. & Singh, U. Survey of stock market prediction using machine learning approach. 2017 International Conference of Electronics, Communication and ...
PNAS

Stochastic machine learning via sigma profiles to build a digital chemical space

The search for a method to convert the discrete set of all synthesizable molecules to a continuous mathematical space, navigable through simple optimization procedures, has been at the forefront of ...
Nature

Prediction of the shear capacity of ultrahigh-performance concrete beams using neural ...

Concrete is one of the most basic building materials with good compressive performance, but its shear strength and tensile strength are often low 1,2. With the development of super high-rise ...
C&EN

Exploring Optimal Reaction Conditions Guided by Graph Neural Networks and Bayesian Optimization

Department of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea Autonomous Materials Development LAB, Samsung Advanced Institute of ...
Frontiers

Neuroevolution Guided Hybrid Spiking Neural Network Training

Neuromorphic computing algorithms based on Spiking Neural Networks (SNNs) are evolving to be a disruptive technology driving machine learning research. The overarching goal of this work is to develop ...
Scientific Research Publishing

Wind Energy Prediction Using Machine Learning ()

1 Economic Cybernetics and Statistics Doctoral School, Bucharest University of Economic Studies, Bucharest, Romania. 2 Informatics and Economic Cybernetics Department, Bucharest University of Economic ...
GitHub

Artificial Intelligence By Example - Second Edition

This is the code repository for Artificial Intelligence By Example, Second Edition, published by Packt. It contains all the supporting project files necessary to work through the book from start to ...