Expert Systems with Applications: An International Journal

High-dose single exposures of long-wavelength ultraviolet-A (UV-A) radiation may trigger severe biological and skin tissue damage in humans and animals, as well as photosynthetic damage in plants. In humans, the highly abundant UV-A is also ...

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• An interpretable AI method is designed to predict solar ultraviolet-A radiation.
• Deep learning ensemble approach is adopted to enhance forecasting performance.
• The model is optimized with neighborhood component analysis and ...

Artificial bee colony (ABC) algorithm has shown good performance on many optimization problems. However, these problems mainly focus on single-objective and ordinary multi-objective optimization problems (MOPs). For many-objective optimization ...

• Two archives namely convergence archive (CA) and diversity archive (DA) are introduced into ABC.
• Based on CA and DA, different search strategies are designed to enhance convergence or diversity.
• A new probability selection strategy ...

Nowadays, factors such as global climate change, environmental damage, and the impact of human activities have led to an increase in natural disasters, and the frequency of natural disaster problems is increasing, which poses a great threat to ...

• Propose effective methods for conflict evidence fusion based on differential evolution.
• Consider volunteers’ preferences, competencies and victims’ satisfaction in volunteer assignments.
• Use linguistic type-2 fuzzy sets and ...

Phishing websites distribute unsolicited content and are frequently used to commit email and internet fraud. Detecting them before any user information is submitted is critical. Several efforts have been made to detect these phishing websites in ...

• WebPhish employs both raw URL and HTML content to detect phishing web pages.
• WebPhish uses character-level embeddings to enable the feature vectors to generalize to new data.
• Extensive experiments conducted on a real-world dataset ...

Computer-aided diagnosis for low-dose computed tomography (CT) based on deep learning has recently attracted attention as a first-line automatic testing tool because of its high accuracy and low radiation exposure. We propose a method based on a ...

• We proposed VMPR-UAD for anomaly detection and localization in 3D chest low-dose CT.
• VMPR-UAD utilized multi-view projection as a pre-processing technique.
• VMPR-UAD enabled 3D visualization of anomalies through post-processing ...

Nesterov accelerated gradient (NAG) method is an efficient first-order algorithm for optimization problems. To ensure the convergence, it usually takes a relatively conservative constant as the stepsize. However, the choice of stepsize has a ...

• Adaptive stepsize design methods without manual tuning are proposed for CNAG.
• Stepsize is obtained by estimating the norm of approximate Hessian matrix.
• Theoretical analysis is presented to support the validity of the design ...

Nowadays, users across the globe interact with one another for information exchange, communication, and association on various online social media. However, some individuals exploit these venues for malicious practices like hate speech and ...

• Proposed an ensemble DL multilingual model for hate speech & cyberbully detection.
• Model combines bagging, stacking, and super learning methods to improved results.
• Model adopts a light weight heterogeneous fusion and bagging-...

Energy-saving, one of the most significant strategies for green manufacturing, has become the focus of more and more scholars and enterprise managers. Hence, this work addresses the minimization of energy and cost requirements on mixed-model ...

• Define the MALBP-MW by a MILP model to minimize the energy and cost requirements.
• Design a new decoding with idle time reduction and a collaborative initialization.
• Propose four problem-specific evolutionary operators for MOCEA.

Graph neural networks have demonstrated significant power in learning graph representations for homogeneous networks. However, real-world network data can often be denoted by heterogeneous networks with different types of nodes and edges, such as ...

• The hypergraph can preserve high-order proximity and capture semantic interactions.
• Our model integrates multiple motif-based hypergraphs to cover all nodes in HIN.
• Attention mechanism aggregates node features based on importance ...

• Unsupervised outlier detection with GAN networks.
• The GANs prefer to fit the normal object distributions to minimize error.
• The fake data generated by the GAN are used to train the autoencoder.
• A trained autoencoder can detect ...

Outlier detection, also known as anomaly detection, has been a persistent and active research area for decades due to its wide range of applications in various fields. Many well-established methods have difficulty fitting the distribution of high-...

This paper proposes a novel approach named adaptive multi-scale attention convolution neural network (AmaCNN) to accurately detect cross-domain faults with very few labelled data. In AmaCNN, multi-scale feature fusion CNN (MSFFCNN) with a multi-...

With the development of intelligent logistics technology, some companies began to use robots instead of humans to load cargo. This paper studies a novel container loading problem based on robotic loader system (CLP-RLS). Different from the ...

• A novel container loading problem based on robotic loader system is studied.
• A tree search approach based on wall-building is proposed to solve this problem.
• The effectiveness of the proposed approach is verified through real-case ...

The objective of this paper is to contribute to the sharing, transfer, and secured indexing of large color images. Watermarking and digital encryption have emerged as alternative and complementary solutions to ensure authorized access, facilitate ...

Determining the optimal quantity of crops is crucial for establishing a sustainable cultivation pattern when multiple potential crops are available. To address this issue, we propose a novel hybrid multi-attribute optimization model (MAOM) based ...

Several giant water diversion projects go through large expansive soil areas in China. It is challenging to ensure the slope stability of the deep excavated expansive soil canal segments due to its undesirable geologic, and physical and ...

Zero-shot image retrieval involves retrieving images of unseen classes using a query image of the same class. To determine whether a given image is of the same class as the query image, a universal threshold of similarity measures is needed, as ...

• A novel Consistent Penalizing Field Loss is proposed for zero-shot image retrieval.
• No-gradient weighting mechanism explicitly separates the weighting and loss items.
• A dice-like mechanism leverages the loss elements of positive ...

Accurate solar irradiance forecasting with fine spatiotemporal correlations is essential for photovoltaic power generation. However, current spatiotemporal methods are unable to extract spatial features appropriately, leading to rough prediction ...

Outstanding steps towards intelligent transportation systems with autonomous vehicles have been taken in the past few years. Nevertheless, the safety issue in autonomous vehicles is critical and remains to be fully solved. Sensor data provide ...

Users from different cultures and backgrounds often feel comfortable expressing their thoughts on trending topics by generating content in their regional languages. Recently, there has been an explosion in multilingual information, and a massive ...

• We recommend multilingual personalized hashtags for low-resource Indic languages.
• We devised a novel way of attending to users’ topical and linguistic preferences.
• We capture relatedness among languages of same family using a graph ...

In the development of a new product, concept generation is a crucial stage, as it determines much of the cost of the product lifetime. The process of generating concepts that meet customer requirements, however, can be challenging due to ...

• We established a cognitive analysis-based approach for deriving key concepts.
• This approach can identify the most important concepts in the product design.
• We verified the approach in an analogy-based verbal protocol analysis ...

Forest fires pose a significant threat to both the economy and ecology, causing extensive damage. Smoke serves as a crucial indicator of forest fires, often appearing before the actual fire. However, existing methods for smoke recognition are ...

Recently the interval forecasting of carbon price is investigated by advanced research since it can better quantify the uncertainty and reliability of the forecast value in comparison with point forecasting. However, this kind of model is always ...

• Online monitoring system was built and monitored weld bead size using OGM(1,N).
• The OGM(1,N) was trained with small number of samples with zero training time.
• Weld bead was controlled by the proposed methodology.
• A suitable ...

In the directed energy deposition process, online monitoring of weld bead geometry can give real-time information to researchers and manufacturers to understand and control the metal deposition layer by layer. In the current work, an optimization ...

Many Multi-Armed Bandit (MAB) based workers selection schemes have been proposed to select high-quality workers to enhance the quality of tasks. However, in Mobile Crowd Sensing (MCS), a complex mutual effect exists among task requestors, the MCS ...

Drone technology, also known as Unmanned Aerial Vehicles (UAVs), has advanced rapidly in the last decade owing to the huge number of users. This approach has an immense opportunity in areas like healthcare, agriculture, and forestry. However, the ...

• UAV technology has seen rapid development in recent years.
• Lack of security solutions in UAVs leads to vulnerabilities in digital image transmission.
• Image Watermarking is a viable solution for digital image transmission in UAV ...

With the advancement of the 5G networks, edge computing (EC) assisted Internet of Things (IoT) based applications demand real-time computation and high-volume data-intensive services. Due to the heterogeneity and limited resources of the edge ...

• A Quantum-Inspired PSO is proposed to address IoT service placement.
• Quantum particle is designed to represent complete IoT service placement solution.
• The decoding of quantum particle is done using a novel double-hashing ...

Relevance-based ranking is a popular ingredient in recommenders, but it frequently struggles to meet fairness criteria because social and cultural norms may favor some item groups over others. For instance, some items might receive lower ratings ...

• A novel integer linear programming model to produce fair recommendation lists.
• Our post processing approach provides minimum exposure guarantees.
• We introduce and analyze two fairness raking-based constraints.
• We attest the ...

The Dung beetle optimization algorithm is a kind of group intelligence optimization algorithm proposed by Jiankai Xue in 2022, which has the characteristics of strong optimization-seeking ability and fast convergence but suffers from the defect ...

• Good point set strategy for initializing populations.
• Multi-strategy fusion balancing pre-global exploration and post-local search.
• Quantum computing interferes with t-distribution variation strategies.

The accumulation of large amounts of historical data has led to the wide application of ensemble learning over the past few decades, but the balance between the individual accuracy of base classifiers (BCs) and the diversity among these BCs is ...