Applied Intelligence

Adverse drug reactions (ADRs), which are harmful physical reactions of patients to drug treatments, are inherent to the nature of drugs; the reactions can occur with any drug and are becoming a leading cause of patient morbidity and mortality ...

At present, the intelligent decision model of unmanned systems can only be applied to virtual scenes, which makes it difficult to migrate to real scenes because the image gap between virtual scenes and real scenes is relatively large. The main ...

Excellent performance has been demonstrated in implementing challenging agricultural production processes using modern information technology, especially in the use of artificial intelligence methods to improve modern production environments. ...

Visual dialog task entails an agent to answer a series of questions based on an image and the dialog history. Biases are often observed when the agent over relies on the dialog history. Thus, balanced usage of dialog history is crucial. Existing ...

In multi-label learning, considering the relative importance between labels can yield better performance than considering the equal importance. To explore relative labeling importance, many existing algorithms introduce the global label ...

The K-means algorithm is widely applied for clustering, and its clustering effect is influenced by its initialization. However, most existing works focus on the initialization of K and centers in Euclidean spaces, but few works in the literature ...${\mathbb{}}^{}$

Considering autonomous navigation of an unmanned ground vehicle (UGV) in off-road environments, it faces various problems, such as semantic perception and motion planning. This paper proposes an intelligent approach to perception and planning for ...

This paper describes the experimental studies of ensembles of binary classifiers conformed of individual support vector machines. The GenBoost-SVM method is proposed to construct such ensembles. Our ensembles considered an adaptive boosting ...

Wearing a safety helmet can reduce the accident rate in production and construction, and it is a necessary part of safety production management. At present, the effective supervision of helmet wearing still relies on manual on-site work, which is ...

It is necessary to consider the trust relationship among experts in the process of group decision-making, however the trust network and preference information among experts may be incomplete. Therefore, this paper proposes an incomplete ...

Due to the growth of online review data, detecting fake or fraudulent reviews is becoming an urgent issue. One barrier to effective detection of fake reviews/reviewers is the great difficulty of collecting ground-truth data—fake reviews are hard ...

Multivariate time series long-term forecasting has always been the subject of research in various fields such as economics, finance, and traffic. In recent years, attention-based recurrent neural networks (RNNs) have received attention due to ...

Knowledge graph completion (KGC) can be interpreted as the task of missing inferences to real-world facts. Despite the importance and abundance of temporal knowledge graphs, most of the current research has been focused on reasoning on static ...

Most data-driven structural damage detection methods are built upon the assumption that enough labeled data is available and both training and test data have the same underlying distribution, which limit their successful applications in practical ...

Missing data are very common in environmental monitoring activities. Traditional interpolation methods often view the problem from either spatial or temporal perspective and do not make good use of valuable related information, thereby leading to ...$$

Knowledge discovery combined with network structure is an emerging field of network data analysis and mining. Three-way concept analysis is a method that can fit the human mind in uncertain decisions and analysis. In reality, when three-way ...

Accurate crowd counting is still challenging due to the variations of crowd heads. Most of crowd counting methods adopt multi-branch networks to extract multi-scale information. However, these networks are too complex to be optimized. To solve ...

The estimation of distribution algorithm (EDA) has recently emerged as a promising alternative to the traditional evolutionary algorithms for solving combinatorial optimization problems. In this paper, an estimation of distribution algorithm with ...

Recently, an exciting experimental conclusion in Li et al. (Knowl Inf Syst 62(2):611–637, 1) about measures of uncertainty for knowledge bases has attracted great research interest for many scholars. However, these efforts lack solid theoretical ...

Various optimization problems with multiple decision variables and complex constraints, which exist widely in the real world, are difficult to be solved by traditional methods. Brain storm optimization (BSO) algorithm, an advanced swarm ...

Deep neural networks (DNNs) are prone to produce incorrect prediction results under the attack of adversarial samples. To cope with this problem, some defense methods are presented. However, most of them are based on adversarial training, which ...

Achieving accurate, fast, and interpretable time series classification (TSC) has attracted considerable attention from the data mining community over the past decades. In this paper, we propose an efficient algorithm, called Compressed Random ...

Retinal hemorrhage detection is of great significance for clinical diagnosis and disease control. However, most of the traditional methods need to obtain candidate lesions firstly, and then determine the true lesions. To address this problem, we ...

Finding the optimal game strategy is a difficult problem in unmanned aerial vehicle (UAV) swarm confrontation. As an effective solution to the sequential decision-making problem, multi-agent reinforcement learning (MARL) provides a promising way ...

Commonsense knowledge is a crucial resource to help the machine understand the human world. However, the conventional methods of extracting commonsense knowledge with isA relation (or isA commonsense knowledge) from text corpora generally do not ...

As a novel approach to enhance information security, physical-layer key generation is based on the channel reciprocity and spatial decorrelation of the wireless channels between two legitimate sides. Due to the half-duplex mode of communication ...

With the development of 3D technologies, 3D model recognition has attracted substantial attention in various areas, such as automatic driving, virtual/augmented reality, and computer-aided design. Many researchers are devoted to 3D model ...

Deep clustering using a deep neural network (DNN) is widely used for simultaneously learning feature representation and clustering. The existing constrained deep clustering methods utilize prior knowledge for improving deep clustering. However, ...

Automated valet parking (AVP) is one of the most advanced technologies for improving parking efficiency and security. However, in an AVP system, the traditional vehicle-side greedy search strategy for available parking spaces is likely to achieve ...

In existing infrared and visible image fusion algorithms, it is usually difficult to maintain a good balance of meaningful information between two source images, which easily leads to the omission of important fractional information in a ...