Results 21 to 30 of about 63,611 (263)

Hidden Markov Model for Stock Selection

Risks, 2015
The hidden Markov model (HMM) is typically used to predict the hidden regimes of observation data. Therefore, this model finds applications in many different areas, such as speech recognition systems, computational molecular biology and financial market ...
Nguyet Nguyen, Dung Nguyen
doaj   +1 more source

Hidden Markov Model for Stock Trading

International Journal of Financial Studies, 2018
Hidden Markov model (HMM) is a statistical signal prediction model, which has been widely used to predict economic regimes and stock prices. In this paper, we introduce the application of HMM in trading stocks (with S&P 500 index being an example ...
Nguyet Nguyen
doaj   +1 more source

Recycling of Thermoplastics with Machine Learning: A Review

Advanced Functional Materials, EarlyView.
This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque, Florian Stephan, Annalena Pongratz, Christian Brütting, Katharina Krause, Holger Ruckdäschel   +5 more
wiley   +1 more source

Feedforward Factorial Hidden Markov Model

Mathematics
This paper introduces a novel kind of factorial hidden Markov model (FHMM), specifically the feedforward FHMM (FFHMM). In contrast to traditional FHMMs, the FFHMM is capable of directly utilizing supplementary information from observations through ...
Zhongxing Peng, Wei Huang, Yinghui Zhu
doaj   +1 more source

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

Advanced Robotics Research, EarlyView.
A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo, Jiahui Zhang, Yimin Han, Ji Ma, Minghao Lu, Ioannis Havoutis, Peng Lu   +6 more
wiley   +1 more source

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Advanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +3 more
wiley   +1 more source

Analysis of multimodal Bayesian nonparametric autoregressive hidden Markov models for process monitoring in robotic contact tasks

International Journal of Advanced Robotic Systems, 2019
Robot introspection aids robots to understand what they do and how they do it. Previous robot introspection techniques have often used parametric hidden Markov models or supervised learning techniques, implying that the number of hidden states or classes
Hongmin Wu, Yisheng Guan, Juan Rojas
doaj   +1 more source

Global Stock Selection with Hidden Markov Model

Risks, 2020
Hidden Markov model (HMM) is a powerful machine-learning method for data regime detection, especially time series data. In this paper, we establish a multi-step procedure for using HMM to select stocks from the global stock market.
Nguyet Nguyen, Dung Nguyen
doaj   +1 more source

A Systematic Approach to Analyze T Cell Migration: Application to Mouse Melanoma Tumors

Advanced Therapeutics, EarlyView.
The results show that a minimum of two migration speeds can be rigorously identified from the data with cells switching between a fast, persistent migratory state, and a slow, random migration state. These results will help in identifying genetic factors that influence rapid migration, among other applications, such as quality control for CAR‐T cell ...
Nikolaos Memmos, Jason S. Mitchell, Brian T. Fife, David Masopust, David J. Odde   +4 more
wiley   +1 more source

Effect of Additional Terminal Residues on the Folding and Unfolding Dynamics of Cold Shock Protein

Advanced Science, EarlyView.
Enhancing protein stability through N‐ and C‐terminal modifications presents a safe and cost‐effective strategy. We investigated this by combining single‐molecule magnetic tweezers experiments and molecular dynamics simulations to study the folding and unfolding dynamics of CSP with various appended residues (LE‐CSP‐GS, KL‐CSP‐GS, KL‐CSP‐LE).
Dan Hu, Yang Wang, Huanjie Jiang, Hai Pan, Yunqiang Bian, Weitong Ren, Hu Chen, Zilong Guo, Yanwei Wang   +8 more
wiley   +1 more source