Applied Intelligence （APIN） - September 2019, issue 9 论文列表
| 点击这里查看 Applied Intelligence 的JCR分区、影响因子等信息 |
| 卷期号： September 2019, issue 9 |
| 发布时间： |
| 卷期年份： 2019 |
| 卷期官网： https://link.springer.com/journal/10489/volumes-and-issues/49-9 |
本期论文列表
Intelligent scheduling with deep fusion of hardware-software energy-saving principles for greening stochastic nonlinear heterogeneous super-systems
A regularized approach for supervised multi-view multi-manifold learning from unlabeled data
Graph-based dynamic ensemble pruning for facial expression recognition
A novel shot boundary detection system using hybrid optimization technique
Incremental regularized Data Density-Based Clustering neural networks to aid in the construction of effort forecasting systems in software development
An intelligent intrusion detection system
On entropy function and reliability indicator for D numbers
Multimodal data fusion framework based on autoencoders for top-N recommender systems
Enhancing sentence embedding with dynamic interaction
A study on the role of flexible preferences in group recommendations
Low-time complexity and low-cost binary particle swarm optimization algorithm for task scheduling and load balancing in cloud computing
SAAGs: Biased stochastic variance reduction methods for large-scale learning
A discrete gravitational search algorithm for the blocking flow shop problem with total flow time minimization
Decision support system for arrhythmia prediction using convolutional neural network structure without preprocessing
Two-time scale learning automata: an efficient decision making mechanism for stochastic nonlinear resource allocation
Histopathological image classification using enhanced bag-of-feature with spiral biogeography-based optimization
A new bio inspired technique based on octopods for spam filtering
A spatial and temporal features mixture model with body parts for video-based person re-identification
Multi-objective evolutionary optimization using the relationship between F1 and accuracy metrics in classification tasks
Design and analysis of distributed load management: Mobile agent based probabilistic model and fuzzy integrated model