AI2A

This paper first mathematically models the UAV swarm online cooperative path planning problem based on the prerequisite assumptions of transparent posture and dynamic mission environment. Then the receding horizon control (RHC) and 2D-equal-step path ...

For speech anti-spoofing, the ability of countermeasures (CMs) to cope with unseen attacks has been under scrutiny. Since the previous LA attack was mainly for ASV, which required that the spoofed speech be clean enough to be parsed properly by the ASV ...

The Deep Q_Network (DQN) algorithm in reinforcement learning is introduced to main engine fault diagnosis to improve the accuracy and efficiency of fault diagnosis by using the optimized DQN network algorithm to compensate for the lack of data imbalance ...

In recent years, the solid oxide fuel cell (SOFC)-based direct current (DC) micro-grid is considered for the power supply worldwide, due to the advantages of the environmentally friendly and high energy conversion efficiency. However, the control scheme ...

At present, the direct current (DC) micro-grid based on the solid oxide fuel cell (SOFC) can supply the power to the external load independently. Despite an adequate and steady supply of the electricity to the external load, the high efficiency and ...

Agent motion model is the research basis of agent motion control. At present, due to the high cost and time consumption of using physical platforms, utilizing the particle motion equation or other dynamic equations to construct the agent motion model is ...

Abstract: Today, the traditional control algorithm of the manipulator is difficult to meet in the complex and changing working environment, and the development of artificial intelligence has achieved remarkable results in the field of manipulator ...

Geological disasters result in significant human and property losses. It is imperative to identify areas prone to geological disasters for prevention and monitoring purposes. Identifying disaster-prone areas can be approached as a machine-learning ...

The conductor is responsible for controlling speed, emotion, instruments, and other musical information in music performances. Using hand gestures, facial expressions, and body movements, the conductor communicates with each member of the band; the ...

Abstract: In the data stream learning scenario, the whole picture of the data can't be observed, and the data may change dynamically, thus increasing the complexity and imbalance of the data. Aiming at the characteristics of data class changes (...

In the classification of benign and malignant breast tumors, in addition to the extraction of features, the selection of classifier is also an important factor affecting the accuracy of classification. At present, the ensemble classifier has limitations ...

To address the problems of difficulty in determining the truncation distance, single definition of local density and low robustness of non-centroid assignment strategy and chain reaction in density peaking clustering algorithm (DPC), this paper proposes ...

Enhancing the utilization of computing resources is a crucial technical challenge within the realm of deep learning model deployment and application. It holds significant importance in effectively leveraging various deep learning models. However, when ...

The entire life cycle of an engine is an asymmetric process, and the characteristics of its internal components are different. It is of great significance to extract engine degradation features and build models for improving the RUL prediction of the ...

In recent years, self-driving delivery vehicles have been used more and more widely. The route planning of courier vehicles can be abstracted as the traveling salesman problem (TSP). For the courier vehicle path optimization problem, an improved ...

China has made great progress in poverty alleviation in past 40 years. However, older Chinese rural residents, who have been identified as a doubly vulnerable group, still experience much different kinds of deprivations. This study firstly evaluated the ...

This paper analyzes the invulnerability of two kinds of networks with different degrees of distribution. According to their topology, four attack strategies and two metrics were selected. The most effective attack strategy and the most appropriate ...

Anomaly detection for network attacks has always been a very important part of intrusion detection. The current research focus is anomaly detection based on deep learning, which has two main problems. One is the lack of a large amount of labeled data in ...

In recent years, the maritime industry is experiencing a deep integration with advanced wireless communication technologies. Unmanned aerial vehicles (UAVs) play a key role in data collection for marine scenarios due to their high maneuverability. ...

High-dimensional data is becoming increasingly common, and the biomedical field is no exception with the rapid development of technology. There are various methods to deal with high-dimensional gene expression data, but all of them have some ...

Financial distress prediction is an important and challenging issue in the financial field. Now, many methods have been proposed to forecast company bankruptcy and financial crisis, and many studies show that artificial intelligence is better than ...

Abstract: Molecular property prediction is a fundamental research problem in the fields of drug discovery, chemical synthesis prediction. To establish a universal molecular property prediction model, this study proposed six molecular properties ...

The courier industry in China has grown quickly due to the rise of online shopping. However, courier notes can unavoidably become smudged or damaged during the delivery process, making it difficult to read the printed Chinese address information or ...

Accurate energy consumption prediction can provide insights to make better informed decisions on energy purchase and generation. It also can prevent overloading and make it possible to store energy more efficiently. In this work, we propose a new deep ...

Due to severe signal obstruction, the global navigation satellite system is unable to work indoors. Visible light positioning, as an alternative technology for indoor positioning, has gained widespread attention in recent years due to its low cost and ...

Abstract—Based on neural network end-to-end speech synthesis systems, high-quality speech can be synthesized when there is sufficient training data. However, it is difficult for languages with small datasets to synthesize speech with high quality and ...

Nested named entity recognition (NER) is an important and challenging task in information extraction. One effective approach is to detect regions in sentences that are later classified by neural networks. Since pre-trained language models (PLMs) were ...

Dialogue systems are a valuable technology in the field of natural language processing to improve work, learning, and daily life. Currently, dialogue systems are employed as an educational technology for mentoring, evaluation, and personalized ...