Expert Systems with Applications: An International Journal

One important task in the study of information cascade is to predict the future recipients of a message given its past spreading trajectory. While the network structure serves as the backbone of the spreading, an accurate prediction ...

• A new framework combines network structure and temporal information.
• A new ...

• A new interdisciplinary metaheuristic derived from engineering field is proposed.

The proportional, integral, and derivative differential evolution algorithm (PID-DE) is proposed as a new type of interdisciplinary metaheuristic evolutionary algorithm in this paper. The inspiration of PID-DE is derived from the ...

• Introduce the hybrid model CEEMDAN-LSTM to forecast RV of stock price index.
• ...

The realized volatility (RV) financial time series is non-linear, volatile, and noisy. It is not easy to accurately forecast RV with a single forecasting model. This paper adopts a hybrid model integrating Long Short-Term Memory (LSTM) ...

Due to their faster convergence rate than gradient descent algorithms and less computational cost than second order algorithms, conjugate gradient (CG) algorithms have been widely used in machine learning. This paper considers ...

• The efficacy of conjugate gradient with noisy gradients is verified.
• The linear ...

• Key question is how to identify the best location for an EoL ALiB recovery center.

With the emergence of battery-based electric vehicles, transportation systems gradually leave using fossil fuel-based combustion engines. Due to their reasonable performance, Lithium-ion batteries have become one of the major batteries ...

• A novel soft computing application for risk assessment in socio-technical systems is proposed.

Work in socio-technical systems (STS) exhibits dynamic and complex behaviors, becoming difficult to model, evaluate and predict. This study develops an integrated soft computing approach for nonlinear risk assessment in STS: the ...

• A two-stage solution approach is proposed for a multi-floor facility layout problem.

The multi-floor facility layout problem (MFLP) is one of the most important and complex facility layout problems that has many applications in designing the facilities of manufacturing and service sectors. In this study, a hybrid ...

Demand prediction for humanitarian logistics is a complex problem with immediate real-world consequences. This paper examines fuel demand during two regional humanitarian crisis events and the supply chain operated by the US Government ...

• Demand prediction for highly dynamic and short events.
• Application of robust ...

Reliability and dependability are critical demands of the fourth industrial revolution that Real-time Ethernet (RTE) networks have to meet. The use of anomaly detection and prevention techniques can further enhance existing RTE ...

• An Anomaly detection method for RTE-based networks using One-Class SVM is proposed.

• Deep learning model was developed for cough detection useful in pandemic situation.

Coughing is a typical symptom of COVID-19. To detect and localize coughing sounds remotely, a convolutional neural network (CNN) based deep learning model was developed in this work and integrated with a sound camera for the ...

• An intelligent method is proposed for better decision-making on the control quality of welds.

The accuracy of diagnosis performed by human operators is closely related to different factors such as fatigue and subjectivity. The solution can be in developing intelligent systems that aid humans in decision-making. In that sense, ...

The emergence of machine learning (ML) and deep learning (DL) techniques opens a huge opportunity for their implementation in industry. One of the tasks for which these techniques have the greatest potential is visual inspection, since ...

• This paper analyzes the effect of data augmentation on the performance of a CNN model.

Mineral named entity recognition (MNER) is the extraction for the specific types of entities from unstructured Chinese mineral text, which is a prerequisite for building a mineral knowledge graph. MNER can also provide important data ...

• Present a BERT-based model for Chinese mineral named entity recognition.
• ...

• A whole new data weighting method for fuzzy clustering is proposed.
• ...

In conventional fuzzy C-means clustering algorithms, each data and each feature are treated equally, the clustering performance is sensitive to the noise points; in existing weighting clustering algorithms, few studies have focus on ...

• We develop metamodels to compute a search and rescue mission success probability.

We present a metamodeling approach, based on supervised learning, to estimate the probability of success of maritime search and rescue operations. The objective is to improve search planning in a context where lives are at risk and ...

• Computing on edge end improves the efficiency and reliability of data analysis.

Crowd stampedes and incidents are critical threats to public security that have caused countless deaths during the past few decades. To avoid crowd stampedes, real-time crowd density estimation can help monitor crowd movements, and ...

• The proposed algorithm performs contaminant identification by unsupervised learning.

Contaminants in surface electromyography (sEMG) recordings might configure an issue if not kept at lower levels since they can impair the extraction of information. In this context, several approaches have been ...

Ovarian cancer is one of the most serious cancers that threaten women around the world. Epithelial ovarian cancer (EOC), as the most commonly seen subtype of ovarian cancer, has rather high mortality rate and poor prognosis among ...

• EOCSA is the first to use deep learning to process WSIs for EOC survival analysis.

Machine learning techniques have recently become the norm for detecting patterns in financial markets. However, relying solely on machine learning algorithms for decision-making can have negative consequences, especially in a critical ...

• Machine learning approach powered by eXplainable Artificial Intelligence techniques.

A crucial challenge in digital image forensics is to identify the source camera model used to generate given images. This is of prime importance, especially for Law Enforcement Agencies in their investigations of Child Sexual Abuse ...

• We propose a camera model identification using ConvNets based on homogeneous patches.

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• A new decision making method for selection problems under uncertainty is proposed.

The use of renewable energy technologies is a key factor for sustainable development but their selection from several alternatives is a difficult task that relies on the careful assessment of relevant criteria. While Multiple Criteria ...

Dry-cured ham is a traditional Mediterranean meat product consumed throughout the world. This product is very variable in terms of composition and quality. Consumer’s acceptability of this product is influenced by different factors, in ...

• Interested regions for each muscle inside the ham slice are automatically located.

• A Generator of Global Hypotheses that implicitly neglects improbable assignments.

The presence of crowds, crossing people, occlusions, and individuals entering and leaving the monitored scenario turns the automatization of Multi-Object Tracking into a demanding task. Due to the difficulties in dealing with those ...

In this paper, we introduce a novel family of multivariate fuzzy neural network interpolation operators activated by sigmoidal functions belonging to the new class of multivariate sigmoidal functions. To present an alternative way to ...

• A novel family of multivariate fuzzy neural network interpolation.
• Alternative ...

In consumer credit scoring practice, there is often an imbalanced distribution in accepted borrowers, which means there are far fewer defaulters than borrowers who pay on time. This makes it difficult for traditional models to ...

• We propose a CWGAN-GP-Based Multi-task Learning Model for credit scoring.
• ...

Recommender Systems (RS) are established to deal with the preferences of users to enhance their experience and interest in innumerable online applications by streamlining the stress persuaded by the reception of ...

• The accuracy of the proposed model was calculated as high as 0.9.
• A novel 1-...

Smartphones have become an integral part of our daily lives thanks to numerous reasons. While benefitting from what they offer, it is critical to be aware of the existence of malware in the Android ecosystem and be away from them. To ...

• Performance measurement complexities during relief operations are key motivations.

Performance measurement activities (PMA) in the humanitarian supply chain (HSC) face several issues. Many of these issues are avoidable and inter-related, subsequently producing undesirable cascading effects. HSC Stakeholders are ...

Artificial intelligence (AI) is fast becoming a general purpose technology with outstanding impacts in industries worldwide, thus supporting the Industry 4.0 revolution. In particular, the energy sector is one of those that has taken ...

• A data-driven benchmarking process of building energy performance is proposed.
• ...