582 Result(s)
within
Lu**g Sun
Engineering
Artificial Intelligence
Control, Robotics, Mechatronics
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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...
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Model analysis and application case for complex multi-system evolutionary optimization
A complex system is made up of multiple related and coupled subsystems. Each subsystem has its own set of multiple constraints and objectives, and is commonly found in real-world applications. Biogeography-bas...
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An evolutionary feature selection method based on probability-based initialized particle swarm optimization
Feature selection is a common data preprocessing technique that aims to construct better models by selecting the most predictive features. Existing particle swarm optimization-based feature selection algorithm...
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Article
Open AccessDynamic multi-label feature selection algorithm based on label importance and label correlation
Multi-label distribution is a popular direction in current machine learning research and is relevant to many practical problems. In multi-label learning, samples are usually described by high-dimensional featu...
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An enhanced teaching–learning-based optimization for the flexible job shop scheduling problem considering worker behaviours
In actual workshop scheduling, processing time is influenced by worker behaviours, such as learning, forgetting, fatigue and recovery. However, in the traditional workshop scheduling considering workers, these...
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Article
Open AccessA Multiple Environment Available Path Planning Based on an Improved A* Algorithm
The objective of the path planning for a mobile robot is to generate a collision-free path from a starting position to a target position, aiming to realize a higher quality of path planning, an improved A* alg...
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Article
Time series clustering of dynamical systems via deterministic learning
A recent deterministic learning theory has achieved locally-accurate identification of unknown system dynamics. This article presents a novel application of deterministic learning theory to unsupervised learni...
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Article
Sequential attention layer-wise fusion network for multi-view classification
Graph convolutional network has shown excellent performance in multi-view classification. Currently, to output a fused node embedding representation in multi-view scenarios, existing researches tend to ensure ...
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Research on load excitation identification method of multi-connected air conditioning compressor based on RBF network with multi-strategy fusion SSA
The load excitation of the multi-connected air conditioning compressor is the major source of vibration in the entire air conditioning pipeline system, which imposes a direct impact on the vibration noise and ...
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Article
Channel spatio-temporal convolutional network for pedestrian trajectory prediction
Pedestrian trajectory prediction is a crucial technology for agents to assist human beings, which remains highly challenging due to the complex interactions between pedestrians and the environment. However, pr...
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Semi-supervised filter feature selection based on natural Laplacian score and maximal information coefficient
As a crucial preprocessing step in data mining, feature selection aims to obtain an excellent feature set, so as to improve the accuracy of classifiers and reduce the training time. This task is non-trivial, e...
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Article
Open AccessFuzzy Neural Network Model for Intelligent Course Development in Music and Dance Education
Interactions are mandatory for online or offline music and dance education to improve understandability and learning efficacy. The course designed for such artistic education incorporates multi-point interacti...
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Article
Autoencoder evolutionary algorithm for large-scale multi-objective optimization problem
Multi-objective optimization problems characterized by a substantial number of decision variables, which are also called large-scale multi-objective optimization problems (LSMOPs), are becoming increasingly pr...
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Research on boundary-aware waters segmentation network for unmanned surface vehicles in complex inland waters
A speedy and reliable system detecting safe waters is essential to enable autonomous navigation of unmanned surface vessels (USVs). However, existing detection methods are prone to misidentifying trees and bui...
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Article
CausalFD: causal invariance-based fraud detection against camouflaged preference
Fraudsters engage in diverse patterns and deceptive interactions, allowing them to move effortlessly within online networks. However, current fraud detection methods heavily rely on correlated experiences and ...
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A multi-strategy spider wasp optimizer based on grou** and dimensional symmetry method with a time-varying weight
Metaheuristic algorithms offer numerous advantages, such as their ability to address a wide range of problems without the need for specific problem formulations or gradient information. They have demonstrated ...
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Article
Double-quantitative multi-granularity kernel fuzzy rough sets model and its application in rheumatoid arthritis risk assessment
The medical big data of combined Chinese and western medicine diagnosis and treatment (CCWMDT) is difficult to be used effectively in clinical medical decision-making because of its complex structure and multi...
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Article
Multi-class feature selection via Sparse Softmax with a discriminative regularization
Feature selection plays a critical role in many machine learning applications as it effectively addresses the challenges posed by “the curse of dimensionality” and enhances the generalization capability of tra...
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Towards platform profit-aware fairness in personalized recommendation
The remarkable progress of machine learning has had a significant impact on decision-making, thus fairness is an important topic. Existing fair recommendation methods generally design a constraint framework be...
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Article
Learning enhancing modality-invariant features for visible-infrared person re-identification
To solve the task of visible-infrared person re-identification, most existing methods embed all images into a unified feature space through shared parameters, and then use a metric learning loss function to le...
