Evaluating performance of AI operators using roofline model

Applied Intelligence - Artificial Intelligence algorithms have shown performance advantages in a wide range of application domains. However, the increasing demand for hardware resources raises...     

A comprehensive model and computational methods to improve Situation Awareness in Intelligence scenarios

Applied Intelligence - This paper presents a comprehensive model for representing and reasoning on situations to support decision makers in Intelligence analysis activities. The main result...     

Big data-driven large-scale group decision-making under uncertainty (BiGDM-U)

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Editorial for the 30th anniversary special issue

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Editorial: special issue on multi-view learning

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Editorial for the COVID special issue

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Correction to: Differentiation of COVID-19 conditions in planar chest radiographs using optimized convolutional neural networks

Applied Intelligence - Figure 4 in the original article unfortunately contained an error.     

Spatial-temporal attention network for multistep-ahead forecasting of chlorophyll

Applied Intelligence - The multistep-ahead prediction of chlorophyll provides an effective means for early warning of red tide. However, since multistep-ahead forecasting presents challenges, such...     

Identification of protein-nucleotide binding residues via graph regularized k-local hyperplane distance nearest neighbor model

Applied Intelligence - Accurate identification of protein-nucleotide binding residues is crucial for the study of drug structure and protein functional annotation. The study of protein-nucleotide...     

A survey of group decision making methods in Healthcare Industry 4.0: bibliometrics,applications, and directions

Applied Intelligence - Healthcare Industry 4.0 refers to intelligent operation processes in the medical industry. With the development of information technology, large-scale group decision making...     

An overview of probabilistic preference decision-making based on bibliometric analysis

Applied Intelligence - Probabilistic preference decision-making (PPDM) is a branch of uncertain decision-making, which identifies decision-makers’ preferences with probability to deal with...     

Modeling adaptive empathy based on neutral assessment: a way to enhance the prosocial behaviors of socialized agents under the premise of self-security

Applied Intelligence - Ethical concerns over artificial intelligence (AI) have recently drawn extensive interest in both academia and industry. According to behavioral economics and...     

Social velocity based spatio-temporal anomalous daily activity discovery of social media users

Applied Intelligence - Anomalous daily activities are the activities that do not fit into normal daily behavior of social media users. Discovering anomalous daily activities is important for...     

Co-clustering based classification of multi-view data

Applied Intelligence - Multi-view learning is an attractive area of research where data is represented using multiple views, each containing some useful information. Many multi-view learning...     

A semi-supervised transferable LSTM with feature evaluation for fault diagnosis of rotating machinery

Applied Intelligence - Aiming at the issue of impracticality or costliness of collecting enough labeled signals under all working conditions, the performance of a method usually suffers a...     

A novel binary farmland fertility algorithm for feature selection in analysis of the text psychology

Applied Intelligence - Feature selection plays a key role in data mining and machine learning algorithms to reduce the processing time and increase the accuracy of classification of high...     

Parameter identification of robot manipulators with unknown payloads using an improved chaotic sparrow search algorithm

Applied Intelligence - Parameter identification is essential for the model-based high-accuracy control of robot manipulators. The objective of this work is to develop a swarm intelligence-based...     

The design of error-correcting output codes algorithm for the open-set recognition

Applied Intelligence - The Open-Set recognition is an important topic in the pattern recognition research field. Different from the close-set recognition task, in the open-set recognition problem,...     

Machine learning techniques to predict different levels of hospital care of CoVid-19

Applied Intelligence - In this study, we analyze the capability of several state of the art machine learning methods to predict whether patients diagnosed with CoVid-19 (CoronaVirus disease 2019)...     

MXQN:Mixed quantization for reducing bit-width of weights and activations in deep convolutional neural networks

Applied Intelligence - Quantization, which involves bit-width reduction, is considered as one of the most effective approaches to rapidly and energy-efficiently deploy deep convolutional neural...