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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