Expert Systems with Applications: An International Journal

Many vision-based methods for printed label defect detection have been proposed to replace inefficient manual inspection. However, due to the existence of artifacts and noise regions, it usually leads to a large number of misjudgments. ...

• Propose an effective latent defect candidate extraction algorithm to eliminate artifacts caused by local deformation.

• A novel probabilistic dual hesitant fuzzy entropy is proposed.
• Some novel ...

Sustainable suppliers selection is a typical multi-attribute decision-making (MADM) problem. MADM is a common problem in the field of decision-making, which is full of uncertainty and fuzziness. As a novel extension of fuzzy set (FS), ...

Physiological studies have shown that facial changes can be seen as a biomarker to analyze the severity of depression. Therefore, this study proposes a Depressioner model to predict the depression level by examining facial changes. Our ...

• A Graph Convolution Embedding (GCE) block is for channel relationship extraction.

• A new learning algorithm for fuzzy cognitive maps is proposed.
• An approach for ...

A Fuzzy Cognitive Map (FCM) is a powerful technique for modeling and analyzing complex systems. In this study, we propose a novel learning algorithm that, unlike existing FCM-based learning algorithms, ensures matching the desired ...

Feature selection techniques have been presented to allow us to choose a small subset of the original components’ relevant features by removing irrelevant or redundant features. Feature selection is essential for many reasons such as ...

• Improve the balance between the local and global search.
• Introducing a new ...

Data uncertainty has been taken into a consideration for mining and discovery of its hidden knowledge in a variety of applications. Due to the fact that the nature of closed sequences is closely related to possible world, more recent ...

• Compared with basic PFCSM-FF, PFCSM-CF enhances the efficiency by avoiding invalid computation.

• Novel strategic servitization design model for smart intralogistics and production.

As to a new smart factory model, the make-to-order (MTO) strategy challenges small and medium-sized manufacturing enterprises. It enables quick response manufacturing (QRM) while responding to diversified, dynamic, and low-volume ...

Support Vector Machines are models widely used in supervised classification. The classical model minimizes a compromise between the structural risk and the empirical risk. In this paper, we consider the Support Vector Machine with ...

• The SVM with feature selection problem is considered from a bi-objective perspective.

Drone delivery is a fast and innovative method for delivering parcels, food, and medical supplies. Furthermore, this low-contact delivery mode contributes to reducing the spread of pandemic and vaccine-preventable diseases. Focusing on ...

• Creates stochastic scheduling and allocation problems with multiple classes of demand.

• A dynamic two-stage SBM model with non-discretionary variables is proposed.
• ...

With the influence of climate changes resulting in more extremely days, we might expect to face a rise in associated coal productivity losses and land destruction. Numerous studies have focused on measuring the efficiency of coal ...

While the asset usually pays discrete fixed-amount dividend in real markets, it is still an open problem on how to accurately and efficiently value barrier options under such circumstances where the underlying price process becomes ...

• Barrier option pricing is studied under nonlinear dynamics with discrete dividends.

• Game method is used in interval cross evaluation.
• Build a variety of evaluation ...

Cross-efficiency evaluation is an effective method for the ranking of decision-making units (DMUs) in data envelopment analysis, which is the performed method for peer-evaluation and self-evaluation. In most cross-efficiency evaluation ...

We may not know the entire feature space in advance for real-world applications, and features can exist in a stream mode, called streaming features. Online streaming feature selection aims to select optimal streaming features on the ...

• We summarize online streaming feature selection into three main components.
• ...

• New and accessible approach for immersive multi-sensory design in architecture.

Multi-Sensory Design is an experimental project that explores the potential and limitations of immersive environments as a means to support the incorporation of intangible sensory aspects of place integrated into the design process. ...

In an evolving competitive environment, characterized by an increasing competition and a rapid market change, companies strive to reach their competitive advantage by monitoring and processing the information related to such ...

• The interest of anticipating competitors’ decisions in a context of uncertainty.

• An agent’s emotion, time belief and opponent’s concession behavior are assessed.

Emotional persuasion driven by agent-based decision-making has shown greater prospects for negotiation between business partners. However, the interactive assessment of emotional persuasion, one of the essential preconditions for ...

• A two-stage customer behavior analysis methodology is proposed.
• The methodology ...

Exploring and forecasting customers’ behavior via time series analysis techniques has gained much attention in recent years. In this context, distance-based time series clustering methods are widely utilized to divide customers into ...

In the medical domain there exists a terminological gap between patients and caregivers and the healthcare professionals. This gap may hinder the success of the communication between healthcare consumers and professionals in the field, ...

• We propose a method to map lay expressions into the Human Phenotype Ontology.
• ...

• Data mining algorithms are explored to predict the adoption speed of pets.
• ...

Many animals are put up for adoption. In turn, having many available animals can overburden shelters if this number rises above a shelter’s maximum capacity. Pet adoption websites need to identify which characteristics or general ...

We propose a bi-objective algorithm based on the k-nearest neighbors (biokNN) method to perform imputation of missing values for data with multilevel structures with continuous variables. We define the imputation method as a bi-...

• A new imputation method for multilevel data was proposed.
• The method was ...

Due to its practicality, hybrid flowshop scheduling problem (HFSP) with productivity objective has been extensively explored. However, studies on HFSP considering green objective in distributed production environment are quite limited. ...

• Considering green scheduling in distributed hybrid flowshop environment.
• ...

This work presents a new approach to maximize financial market investment returns. It incorporates two Evolutionary Algorithms (EAs) combined with fundamental and technical investment strategies. The first EA (simple) maintains its ...

• Evolutionary Algorithms with self-adaptive capabilities show improved returns.
• ...

• Take the local dimming as a multi-objective optimization problem.
• Build the ...

The advent of the digital era dramatically enriches the information obtained by people through vision and urges people to put forward higher requirements for image display quality. The luminance dynamic range is an essential factor ...

In this paper, the bounded support asymmetric generalized Gaussian mixture model (BAGGMM) is proposed for data modeling as an alternative to unbounded mixture models for the cases when the data lies in the bounded support region. The ...

• Bounded support asymmetric generalized Gaussian mixture model (BAGGMM) is proposed.

• A reputation-based consensus model (FRCM) for fair selection of nodes' transactions.

Fair selection of community members’ transactions in blockchain-based technologies, especially in finance, is essential and vital. Therefore, in this paper, a novel consensus model for fair selection of community members’ transactions ...

Sequential pattern mining (SPM) discovers, from event transactions recorded along time, patterns of events fulfilling a sequential order. In this work, we introduce a new efficient sequential pattern mining algorithm called VEPRECO. ...

• This work presents VEPRECO, a new efficient Sequential Pattern Mining algorithm.

• A mathematical formulation for electric vehicle production routing problem.
• ...

Advanced decision-making models have been recently developed to integrate various aspects of a supply chain, i.e., production, distribution, shipping, and routing. These have resulted in higher productivity and significant cost saving. ...

This paper proposes a decentralized feedback mechanism to help large-scale decision makers (DMs) reach consensus considering the limited compromise behavior of subgroups. First, a novel decentralized opinion interaction mechanism is ...

• A decentralized feedback mechanism is developed for large-scale group consensus.

This work creates and makes publicly available the most comprehensive dataset to date regarding climate change and human opinions via Twitter. It has the heftiest temporal coverage, spanning over 13 years, includes over 15 million ...

• Create the most extensive dataset for climate change and human opinions via Twitter.