638 Result(s)
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Article
Lu**g Sun
Engineering
Artificial Intelligence
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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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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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Open AccessA novel method for measuring center-axis velocity of unmanned aerial vehicles through synthetic motion blur images
Accurate velocity measurement of unmanned aerial vehicles (UAVs) is essential in various applications. Traditional vision-based methods rely heavily on visual features, which are often inadequate in low-light ...
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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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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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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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Performance-based Assistance Control for Upper Limb Robotic Mirror Therapy
As an effective therapy for treating unilateral neglect, Mirror Therapy (MT) is employed in the upper limb motor function rehabilitation of hemiplegic patients. However, traditional MT has a serious limitation...
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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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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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Reconstructing 3D Biomedical Architectural Order at Multiple Spatial Scales with Multimodal Stack Input
Microscopy, crucial for exploring biological structures, often uses polarizing microscopes to observe tissue anisotropy and reconstruct label-free images. However, these images typically show low contrast, and...
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MAPFUNet: Multi-attention Perception-Fusion U-Net for Liver Tumor Segmentation
The second-leading cause of cancer-related deaths globally is liver cancer. The treatment of liver cancers depends heavily on the accurate segmentation of liver tumors from CT scans. The improved method based ...
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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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Open AccessDynamic Color Regulation of the Lycaenid Butterfly Wing Scales
Butterfly coloration originates from the finely structured scales grown on the underlying wing cuticle. Most researchers who study butterfly scales are focused on the static optic properties of cover scales, w...
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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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Complex Pythagorean Hesitant Fuzzy Aggregation Operators Based on Aczel-Alsina t-Norm and t-Conorm and Their Applications in Decision-Making
Aggregation operators are used for aggregating the collection of finite information into a singleton set. The Aczel-Alsina t-norm and t-conorm are very useful for constructing any kind of new aggregation opera...
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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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Apply Fuzzy Mask to Improve Monocular Depth Estimation
A fuzzy mask applied to pixel-wise dissimilarity weighting is proposed to improve the monocular depth estimation in this study. The parameters in the monocular depth estimation model are learned unsupervised t...
