29,694 Result(s)
within
English
Engineering
Computational Intelligence
Yi** **
Article
-
Article
Game-theoretic multi-agent motion planning in a mixed environment
The motion planning problem for multi-agent systems becomes particularly challenging when humans or human-controlled robots are present in a mixed environment. To address this challenge, this paper presents an...
-
Article
A general framework for improving cuckoo search algorithms with resource allocation and re-initialization
Cuckoo search (CS) has currently become one of the most favorable meta-heuristic algorithms (MHAs). In this article, a simple yet effective framework is proposed for CS algorithms to reinforce their performanc...
-
Article
Tensor discriminant analysis on grassmann manifold with application to video based human action recognition
Representing videos as linear subspaces on Grassmann manifolds has made great strides in action recognition problems. Recent studies have explored the convenience of discriminant analysis by making use of Gras...
-
Article
ConDA: state-based data augmentation for context-dependent text-to-SQL
The context-dependent text-to-SQL task has profound real-world implications, as it facilitates users in extracting knowledge from vast databases, which allows users to acquire the information interactively for...
-
Article
Fast Shrinking parents-children learning for Markov blanket-based feature selection
High-dimensional data leads to degraded performance of machine learning algorithms and weak generalization of models, so feature selection is of great importance. In a Bayesian network (BN), the Markov blanket...
-
Article
Open AccessDistributed order estimation for continuous-time stochastic systems
In this paper, we investigate the distributed estimation problem of continuous-time stochastic dynamic systems over sensor networks when both the system order and parameters are unknown. We propose a local inf...
-
Article
Combining core points and cluster-level semantic similarity for self-supervised clustering
Contrastive learning utilizes data augmentation to guide network training. This approach has attracted considerable attention for clustering, object detection, and image segmentation. However, previous studies...
-
Article
Drfnet: dual stream recurrent feature sharing network for video dehazing
The primary effects of haze on captured images/frames are visibility degradation and color disturbance. Even though extensive research has been done on the tasks of video dehazing, they fail to perform better ...
-
Article
Open AccessSliced Wasserstein adversarial training for improving adversarial robustness
Recently, deep-learning-based models have achieved impressive performance on tasks that were previously considered to be extremely challenging. However, recent works have shown that various deep learning model...
-
Article
Online distributed optimization with stochastic gradients: high probability bound of regrets
In this paper, the problem of online distributed optimization subject to a convex set is studied via a network of agents. Each agent only has access to a noisy gradient of its own objective function, and can c...
-
Article
Aspect category sentiment classification via document-level GAN and POS information
The purpose of aspect-category sentiment classification (ACSC) is to determine the sentiment polarity of the predefined aspect category from the texts. Current methods for ACSC have two main limitations. Since...
-
Article
Data-driven quantification and intelligent decision-making in traditional Chinese medicine: a review
Traditional Chinese medicine (TCM) originates from the practical experience of human beings’ constant struggle with nature. In five thousand years, TCM has gradually risen from empirical medicine to modern evi...
-
Article
BPSO-SLM: a binary particle swarm optimization-based self-labeled method for semi-supervised classification
The self-labeled methods have been favored by scholars in semi-supervised classification. Mislabeling is a great challenge for self-labeled methods and one of the reasons for mislabeling is that high-confidenc...
-
Article
\(\lambda \) -possibility-center based MCDM technique on the control of Ganga river pollution under non-linear pentagonal fuzzy environment
Indians regard the River Ganga as religious because it sustains the ecosystem and ecology. Over the past few decades, human activities have caused significant changes in the Ganga river system. Ganga pollution...
-
Article
Model-free method for LQ mean-field social control problems with one-dimensional state space
This paper presents a novel model-free method to solve linear quadratic (LQ) mean-field control problems with one-dimensional state space and multiplicative noise. The focus is on the infinite horizon LQ setti...
-
Article
Dual flow fusion graph convolutional network for traffic flow prediction
In recent decades, motor vehicle ownership has increased worldwide year by year, which causes that the accurate prediction of traffic flow on urban road networks becomes more important. However, the dual depen...
-
Article
Survey and open problems in privacy-preserving knowledge graph: merging, query, representation, completion, and applications
Knowledge Graph (KG) has attracted more and more companies’ attention for its ability to connect different types of data in meaningful ways and support rich data services. However, due to privacy concerns, dif...
-
Article
Road intersection detection using the YOLO model based on traffic signs and road signs
A road intersection is an area where more than two roads in different directions connect. It is a point of transition where the driver navigates and makes the decision, making it an area with a high risk for t...
-
Article
Online control for pressure regulation of oxygen mask based on neural network
The aviation oxygen mask, which has a small volume of less than 1 L and strong air tightness, imposes extremely high requirements on control performance of the oxygen regulator. Based on analyses of the operat...
-
Article
Unsupervised domain adaptation via feature transfer learning based on elastic embedding
Supervised classification algorithms usually require a large quantity of well-labeled samples for training to achieve satisfied performance. Nevertheless, it is prohibitively difficult to create such datasets ...
