St-trader: A spatial-temporal deep neural network for modeling stock market movement
X Hou, K Wang, C Zhong, Z Wei - IEEE/CAA Journal of …, 2021 - ieeexplore.ieee.org
Stocks that are fundamentally connected with each other tend to move together. Considering
such common trends is believed to benefit stock movement forecasting tasks. However, such …
such common trends is believed to benefit stock movement forecasting tasks. However, such …
An aggregative learning gravitational search algorithm with self-adaptive gravitational constants
The gravitational search algorithm (GSA) is a meta-heuristic algorithm based on the theory
of Newtonian gravity. This algorithm uses the gravitational forces among individuals to move …
of Newtonian gravity. This algorithm uses the gravitational forces among individuals to move …
Scribble-supervised video object segmentation
P Huang, J Han, N Liu, J Ren… - IEEE/CAA Journal of …, 2021 - ieeexplore.ieee.org
Recently, video object segmentation has received great attention in the computer vision
community. Most of the existing methods heavily rely on the pixel-wise human annotations …
community. Most of the existing methods heavily rely on the pixel-wise human annotations …
Information-theory-based nondominated sorting ant colony optimization for multiobjective feature selection in classification
Feature selection (FS) has received significant attention since the use of a well-selected
subset of features may achieve better classification performance than that of full features in …
subset of features may achieve better classification performance than that of full features in …
An α–β-divergence-generalized recommender for highly accurate predictions of missing user preferences
To quantify user–item preferences, a recommender system (RS) commonly adopts a high-
dimensional and sparse (HiDS) matrix. Such a matrix can be represented by a non-negative …
dimensional and sparse (HiDS) matrix. Such a matrix can be represented by a non-negative …
Generalized nesterov's acceleration-incorporated, non-negative and adaptive latent factor analysis
A non-negative latent factor (NLF) model with a single latent factor-dependent, non-negative
and multiplicative update (SLF-NMU) algorithm is frequently adopted to extract useful …
and multiplicative update (SLF-NMU) algorithm is frequently adopted to extract useful …
Nonlinear energy sink with limited vibration amplitude
In the research of applying nonlinear energy sinks for vibration reduction, usually the
vibration amplitude of nonlinear energy sinks is not limited. Since the linear stiffness of the …
vibration amplitude of nonlinear energy sinks is not limited. Since the linear stiffness of the …
Mixed-integer programming model and hybrid driving algorithm for multi-product partial disassembly line balancing problem with multi-robot workstations
To address the problem of considerable waste electromechanical product generation, a
partial disassembly line balancing problem with multi-robot workstations that can …
partial disassembly line balancing problem with multi-robot workstations that can …
Improving dendritic neuron model with dynamic scale-free network-based differential evolution
Some recent research reports that a dendritic neuron model (DNM) can achieve better
performance than traditional artificial neuron networks (ANNs) on classification, prediction …
performance than traditional artificial neuron networks (ANNs) on classification, prediction …
A novel shuffled frog-leaping algorithm with reinforcement learning for distributed assembly hybrid flow shop scheduling
Distributed hybrid flow shop scheduling (DHFS) problem has attracted much attention in
recent years; however, DHFS with actual processing constraints like assembly is seldom …
recent years; however, DHFS with actual processing constraints like assembly is seldom …