Results 31 to 40 of about 7,740,955 (377)
A Variational Beam Model for Failure of Cellular and Truss‐Based Architected Materials
Advanced Engineering Materials, EarlyView., 2023 Herein, a versatile and efficient beam modeling framework is developed to predict the nonlinear response and failure of cellular, truss‐based, and woven architected materials. It enables the exploration of their design space and the optimization of their mechanical behavior in the nonlinear regime. A variational formulation of a beam model is presented
Konstantinos Karapiperis +3 more
wiley +1 more source
STRATEGI TRADING MATA UANG ASING (VALUTA ASING / FOREIGN EXCHANGE)
Journal of Management Small and Medium Enterprises (SME's), 2019 Regardless of the risks, Forex business is a profitable business instrument. Foreign currency exchange is a trade transaction of a country currency against other currencies (currency pair) that involves major financial markets in the world for 24 hours,
Anthon Mesakh +2 more
doaj +1 more source
Predictive Trading Strategy for Physical Electricity Futures
Energies, 2020 This article presents an original predictive strategy, based on a new mid-term forecasting model, to be used for trading physical electricity futures.
C. Monteiro +2 more
semanticscholar +1 more source
Advanced Engineering Materials, EarlyView., 2023 A numerical scheme is presented to design a lattice support for metallic components additively built via laser powder bed fusion. Results show that thermal‐induced distortion can be respectively reduced by 69%, 58%, and 50% in comparison to a uniform lattice, a fully solid support, and a truss‐based lattice support.
Jiazheng Hu +2 more
wiley +1 more source
Reinforcement Learning for Stock Prediction and High-Frequency Trading With T+1 Rules
IEEE Access, 2023 The high-frequency trading framework for the price trend prediction model and trading strategy has been a popular approach for T+0 trading in the stock market.
Weipeng Zhang +4 more
doaj +1 more source
Financial Trading Strategy System Based on Machine Learning
, 2020 The long-term and short-term volatilities of financial market, combined with the complex influence of linear and nonlinear information, make the prediction of stock price extremely difficult. This paper breaks away from the traditional research framework
Yanjun Chen +3 more
semanticscholar +1 more source
, 2022 In this bachelor thesis, we show how four different machine learning methods (Long Short-Term Memory, Random Forest, Support Vector Machine Regression, and k-Nearest Neighbor) perform compared to already successfully applied trading strategies such as Cross Signal Trading and a conventional statistical time series model ARMA-GARCH.
Jevtic, Danijel +2 more
openaire +2 more sources
Deep reinforcement learning for automated stock trading: an ensemble strategy
International Conference on AI in Finance, 2020 Stock trading strategies play a critical role in investment. However, it is challenging to design a profitable strategy in a complex and dynamic stock market. In this paper, we propose an ensemble strategy that employs deep reinforcement schemes to learn
Hongyang Yang +3 more
semanticscholar +1 more source
Equilibrium Price and Optimal Insider Trading Strategy Under Stochastic Liquidity with Long Memory [PDF]
Applied Mathematics and Optimization, 2019 In this paper, the Kyle model of insider trading is extended by characterizing the trading volume with long memory and allowing the noise trading volatility to follow a general stochastic process.
Ben-Zhang Yang, Xin‐Jiang He, N. Huang
semanticscholar +1 more source
Frontiers in Nutrition, 2022 IntroductionThe virtuality, concealment, uncertainty and complexity of online trading make the online food trading market have security risks, while the lack of information, information asymmetry and imperfect market system make the “lemon problem” in ...
Fang Su +5 more
doaj +1 more source